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3 episodes with implementing ai
2 episodes with implementing ai
2 episodes with implementing ai
2 episodes with implementing ai
2 episodes with implementing ai
Episode SummaryIn this provocative and insightful episode, OnBase host Chris Moody reunites with Lukas Egger to discuss one of the most talked-about frontiers in business innovation: agentic AI. Lukas explores how companies can move beyond demos and hype to implement AI in ways that reshape business models and unlock new value creation.Key TakeawaysPrioritizing Agentic AI: Leaders must prioritize agentic AI for business preparedness due to the significant investment and potential for new value creation.Understanding Misconceptions: It's crucial to recognize the "Jagged Frontier of AI," where AI's capabilities are counterintuitive, and avoid the "Lego brick fallacy," which assumes AI can be simply plugged into existing processes.Lowering Cost of Failure: To confidently adopt AI, businesses must systematically lower the cost of failure, iterate quickly, and democratize the process.Data-Driven Insights: Robust data and real answers are essential for understanding the ROI and impact of AI changes on business processes, systems, and people.Competitive Advantage: Instead of focusing solely on common AI use cases, businesses should identify their unique, unfair advantages and engage in rapid iterations and customer conversations to discover differentiating functionalities.Integrated Innovation: Marketing, sales, and business development should be involved early in the AI innovation process to ensure that new solutions align with market needs and monetization strategies.Beyond Peacocking: Avoid simply "peacocking" with AI by replicating what others are doing; instead, focus on deep integration and solving real business problems.Best Moments 02:00 – Lukas describes his nonlinear path from philosophy and startups to enterprise innovation at SAP.05:00 – The promise of agentic AI: opening up new domains for value creation and strategic repositioning.10:00 – Breaking down misconceptions: why traditional planning fails in the face of fast-moving AI.15:00 – Lowering the cost of failure and why “small wins” are key to long-term adoption.20:00 – Avoiding AI homogeneity: how to resist the urge to copy competitors and build a real moat.26:00 – Implementing AI at scale in large organizations: the hidden value of domain expertise and transparency.32:00 – The behaviors leaders must change to avoid missing the AI wave entirely.38:00 – Why marketers and sales teams must embed in AI development—early and often.Shout-outsHelen and Dave Edwards, Co-Founders of Artificiality Institute who discuss the emotional components of AI technology.Peter Temes, Founder and President, ILO Institute, for his deep understanding of basicAbout the GuestLukas N.P. Egger leads the Innovation Office & Strategic Projects team at SAP Signavio, where he focuses on de-risking new product ideas and establishing best-in-class product discovery practices. With a successful track record in team building and managing challenging projects, Lukas has expertise in data-driven technology, cloud-native development, and has created and implemented a new product discovery methodology. Excelling at bridging the gap between technical and business teams, he has worked in AI, operations, and product management in fast-growth environments. As a founder, he has experience building lean and iterating quickly to create saleable software with limited resources while fostering loyalty. Lukas has movie credits for his work in Computer Graphics research, published a book on philosophy, and is passionate about the intersection of technology and people, regularly speaking on how to improve organizations.Connect with Lukas.
Listen now: subscribe and join 1,000s of IT Leaders changing the face of IT. ON THIS EPISODE: ➤ Strategic approaches to implementing AI in healthcare technology ➤ Effective methods for retaining top IT talent in today’s market ➤ Building successful hybrid work environments ➤ Bridging knowledge gaps between veteran and new-gen tech professionals ➤ Building...
In this episode of Great Question: A Manufacturing Podcast, Thomas Wilk, chief editor of Plant Services, is joined by Christine Nishimoto, director of asset management software at IBM, for an insightful discussion on how AI agents are reshaping data-driven asset management. Together, they explore the evolving role of artificial intelligence in improving productivity, sustainability, and safety across manufacturing sectors. From tackling long-standing data challenges to envisioning multi-agent systems that can automate complex workflows, the conversation highlights the transformative potential of AI tools in industrial environments. Christine also emphasizes the importance of transparency, data integrity, and regulatory compliance as organizations adopt these technologies. Key takeaways Clean, accessible, and accurate data is critical for effective AI-driven asset management. AI agents can automate multistep tasks like work order creation, boosting efficiency. Tailored AI tools must respect industry-specific privacy and compliance standards. Adoption of AI across sectors is accelerating, revealing untapped optimization potential.
Summary:In this episode of #thePOZcast, host Rona Pierce speaks with Matt Lavery, Director of Global Sourcing, Recruiting, and Onboarding at UPS. They discuss Matt's journey from a seasonal handler to a leadership role, the impact of AI and automation on hiring processes, and the importance of internal mobility and career progression within UPS. Matt shares insights on enhancing candidate experience, ethical considerations in AI usage, and valuable leadership lessons learned throughout his career.Takeaways- Matt Lavery's journey at UPS showcases the value of internal mobility.- AI and automation have significantly improved the hiring process at UPS.- Speed and transparency are key factors in candidate experience.- Understanding the problem is crucial before implementing AI solutions.- Leadership involves providing clarity and empowering teams.- UPS hires around 200,000 people annually, especially during peak seasons.- NPS scores indicate high candidate satisfaction with the hiring process.- Internal mobility pathways are essential for employee retention.- Technology can enhance the candidate experience and streamline processes.- Change management requires careful planning and communication. Chapters00:00 Introduction to the POScast and Guest Background01:21 Matt Lavery's Journey at UPS03:58 The Impact of AI and Automation on Hiring10:21 Enhancing Candidate Experience through Technology13:42 Internal Mobility and Career Progression at UPS17:50 Lessons Learned in Implementing AI in Hiring20:30 Leadership Insights and Hiring Myths22:12 Proud Moments and Closing Thoughts
On this episode of The Medical Alley Podcast, we present a recent webinar focused on how AI can improve patient engagement, enhance operational efficiency, and navigate key challenges like data privacy, algorithmic bias, and compliance.Featuring Life Link III's Kolby Kolbet, MSN, RN, FACHE, CMTE, FAASTN and MentorMate's Josh Marquart.Send us a message! Follow Medical Alley on social media on LinkedIn, Facebook, X and Instagram.
#399 In this episode, Brigham Dallas shares his unique entrepreneurial journey and the lessons learned while scaling Hello Sugar to a whopping 89 units. From employee retention strategies, the impact of company culture, to the advantages of technology such as AI in the workplace, Dallas shares it all. He also shares the critical role of leadership, savvy financial management, and the art of selecting the right partnerships and customers to nurture growth. Brigham reveals how refining branding and understanding the market led to skyrocketing engagement, and how rewarding employees can create a workplace where everyone thrives. (Original Air Date - 5/8/24) What we discuss with Brigham: + From College Dropout to Entrepreneur + Growing the business to 89 franchise units + Key Strategies for Workforce Optimization and Retention + Employee Retention and Leadership + Technologies Improving Operations + Balancing Financial Risk and Growth + Starting with minimal funds and scaling the business + Refining Brand Strategy and Franchising + Creating hiring protocols and refining brand concepts + Overcoming Operational Hurdles + Focusing on repeat customers and effective rebooking + Implementing AI for Customer Interaction + Reducing response time and human intervention requirements + Enhancements in Service Experience + The Psychological Aspects of Employee Rewards Thank you, Brigham! We want to extend our heartfelt thanks to Brigham for sponsoring today's podcast episode. Make sure to check out Hello Sugar here and to connect with Brigham, click here. For more information go to MillionaireUniversity.com To get access to our FREE Business Training course go to MillionaireUniversity.com/training. And follow us on: Instagram Facebook Tik Tok Youtube Twitter To get exclusive offers mentioned in this episode and to support the show, visit millionaireuniversity.com/sponsors. EXCLUSIVE NordVPN Deal ➼ https://nordvpn.com/millionaire. Try it risk-free now with a 30-day money-back guarantee! Want to hear from more incredible entrepreneurs? Check out all of our interviews here! Learn more about your ad choices. Visit megaphone.fm/adchoices
I'm joined by HR expert Jackie Koch, who brings a wealth of knowledge and experience from her extensive background in high-growth startups and HR consulting. We dive into one of the most challenging aspects of entrepreneurship: hiring. Whether you're debating whether to buy talent or build it within your organization, this conversation has invaluable insights for you. Jackie and I explore the pros and cons of both approaches, discuss the importance of aligning your expectations with your hiring decisions, and share practical advice on interviewing, onboarding, and creating a workplace culture that nurtures growth. We also touch on the significance of investing in tools and processes that set your hires up for success from day one. Don't miss this episode if you're looking to refine your hiring strategy and avoid costly mistakes. Tune in now and take the first step towards smarter hiring practices! What You'll hear in this episode: [00:50] Meet Jackie Koch: HR Expert and Business Bestie [01:40] The Importance of Hiring the Right People [02:55] Jackie's Background and Expertise [04:05] Challenges of Transitioning from Corporate to Startup [07:00] The Build vs. Buy Talent Dilemma [16:25] Benefits and Drawbacks of Buying Talent [22:15] Benefits and Drawbacks of Building Talent [24:40] The Challenge of Hiring the Right Talent [25:35] Building Talent: The Complexities and Importance [26:30] Mentoring and Coaching: A Foundational Component [26:45] Implementing AI and Training Systems [28:45] The Cost and Benefits of Building Talent [30:05] Transparency and Honesty in Hiring [35:30] Learning from Past Experiences [42:05] The Importance of Clear Job Descriptions [46:05] Resources for Improving Hiring Processes If you like this episode, check out: My 3 Favorite Interview Questions Authentic Hiring: Showcase Your Values How to Keep Employees Loyal Connect with Jackie: Check out the World's Greatest Boss Podcast https://www.peopleprinciples.co/podcast Learn more about hiring and HR templates peopleprinciples.co Connect with Jackie on LinkedIn https://www.linkedin.com/in/jackiemkoch/ Want to learn more so you can earn more? Visit keepwhatyouearn.com to dive deeper on our episodes Visit keepwhatyouearncfo.com to work with Shannon and her team Watch this episode and more here: https://www.youtube.com/channel/UCMlIuZsrllp1Uc_MlhriLvQ Connect with Shannon on IG: https://www.instagram.com/shannonkweinstein/ The information contained in this podcast is intended for educational purposes only and is not individual tax advice. Please consult a qualified professional before implementing anything you learn.
AI right? We love it. But how do we actually implement it effectively, efficiently and compliantly into our talent team and business? Sam Dhesi, CEO of Popp, fills us in.
Entrepreneur Carl Taylor joins Tyron Hyde on "Ten with Ty" to discuss wealth creation, business strategy, and work-life balance for dads. Carl shares insights on his entrepreneurial journey, the success of his digital marketing company, Automation Agency, and the benefits of investing in education and mentorship. He reveals his impressive returns from cryptocurrency investments and offers practical advice for achieving financial freedom. The episode also delves into the importance of setting boundaries to balance family life while running a successful business.Watch on YoutubeThroughout the episode, Carl provides an in-depth look at his journey from a teenage software coder to owning a successful marketing automation company, Automation Agency. He also discusses his mission to empower entrepreneur fathers through his Dadpreneur initiative, focusing on work-life balance and personal fulfilment.The conversation delves into Carl's wealth creation strategies, exploring unexpected successes such as his passive income achievements from a single blog post and investments in cryptocurrency. Emphasising the importance of strategic business operations, Carl discusses the advantages of automation and AI integration in business processes. The episode is filled with practical advice on investment strategies, the power of education and networking, and valuable lessons learned from navigating both successful and challenging business ventures.Key Takeaways:Carl Taylor successfully turned a 40-minute blog post into over $840,000 in passive income by leveraging affiliate marketing.Investing in education, mentorship, and networking can provide both substantial financial returns and invaluable professional relationships.Carl advocates the necessity of designing an ideal work-life balance, particularly for business-oriented fathers through his Dadpreneur initiative.Despite experiencing financial setbacks, strategic investments in cryptocurrency yielded Carl an impressive 5,392% return over 14 years.Implementing AI and automation in business enhances operational efficiency and can significantly reduce the time entrepreneurs spend on routine tasks.Notable Quotes:"I put about 40 minutes of time to record a video and write a blog Post back in 2014 sharing my views on a piece of software. And that one blog post has made me $840,000 in true passive income.""From a financial percentage return, [crypto] has been my absolute best investment.""So we help them (Dadpreneurs) build a business that doesn't rely on them, step out of the day-to-day through automation, team, etc, smart ways of working.""Financial freedom equals passive income, exceeding your expenses.""If you can't manage the money that you currently have, why would God or the universe give you more?"Resources:Carl Taylor: carltaylor.com.au IG @carltaylorAutomation Agency: automationagency.comDadpreneur: dadpreneur.comT. Harv Eker: "Secrets of a Millionaire Mind"Robert Kiyosaki: "Cash Flow" Board GameWatch YouTubeDownload Spotify Apple Tyron Hyde is the CEO of Washington Brown Quantity Surveyors
This is episode 2 of the series: Embracing AI in Healthcare: Enabling Nurses to be Nurses EpisodeEpisode 1: The Role of AI in NursingArtificial intelligence is reshaping healthcare by streamlining workflows and reducing administrative burdens, allowing nurses to focus more on patient care. This episode explores the current applications of AI in healthcare, its impact on patient outcomes, common misconceptions, and the importance of balancing AI's capabilities with human clinical judgment. While AI is a powerful tool, critical thinking and professional expertise remain essential in patient care.Episode 2: Implementing AI in Nursing WorkflowsSuccessfully integrating AI into nursing practice requires thoughtful implementation, leadership support, and effective training. This episode delves into how AI can enhance efficiency, improve patient outcomes, and support nurses in their roles while addressing key ethical considerations. By understanding best practices in AI adoption, nurses can leverage technology to optimize care while maintaining their central role in the patient experience. ---Nurses may be able to complete an accredited CE activity featuring content from this podcast and earn CE hours provided from Elite Learning by Colibri Healthcare. For more information, click hereAlready an Elite Member? Login hereLearn more about CE Podcasts from Elite Learning by Colibri HealthcareView Episode TranscriptView this podcast course on Elite LearningSeries: Embracing AI in Healthcare: Enabling Nurses to be Nurses Episode
This is episode 1 of the series: Embracing AI in Healthcare: Enabling Nurses to be Nurses EpisodeEpisode 1: The Role of AI in NursingArtificial intelligence is reshaping healthcare by streamlining workflows and reducing administrative burdens, allowing nurses to focus more on patient care. This episode explores the current applications of AI in healthcare, its impact on patient outcomes, common misconceptions, and the importance of balancing AI's capabilities with human clinical judgment. While AI is a powerful tool, critical thinking and professional expertise remain essential in patient care.Episode 2: Implementing AI in Nursing WorkflowsSuccessfully integrating AI into nursing practice requires thoughtful implementation, leadership support, and effective training. This episode delves into how AI can enhance efficiency, improve patient outcomes, and support nurses in their roles while addressing key ethical considerations. By understanding best practices in AI adoption, nurses can leverage technology to optimize care while maintaining their central role in the patient experience. ---Nurses may be able to complete an accredited CE activity featuring content from this podcast and earn CE hours provided from Elite Learning by Colibri Healthcare. For more information, click hereAlready an Elite Member? Login hereLearn more about CE Podcasts from Elite Learning by Colibri HealthcareView Episode TranscriptView this podcast course on Elite LearningSeries: Embracing AI in Healthcare: Enabling Nurses to be Nurses Episode
After a frustrating week of trying to wrangle AI outputs, we decided to explore the risks of overreliance on AI. It's good for us to question our tools. It enhances our processes and challenges us to find the right tools.Listen on Spotify | Listen on Apple Podcasts | Watch on YouTubeIn this episode, we say the quiet parts out loud. Not only are LLMs often feeding us incorrect information, but over-trusting these systems poses a serious risk.We can look at this Rolling Stone article headline and immediately laugh it off. It is insane to believe this will happen to anyone we know. However, in Mark Zuckerberg's vision of the AI future, your friends will be bots. The loneliness epidemic is real. One in three Americans feels lonely every week. Data from Harvard's Making Caring Common Project supports that loneliness is tied to increasing feelings of anxiety, not part of this country, and being about more than social isolation. 65% of respondents blame “our society,” pointing to a lack of confidence in our way of life and institutions.So, it should be no surprise that Harvard Business Review found that the top three use cases of 2025 involved loneliness and navigating life's stresses.AI could quickly become the next addiction for a world desperate for solutions. The fact that there's demand for robo-companionship shouldn't be treated as validation for building more tools to disassociate them from life. Let's go back to exploring this topic from the perspective of business users.Understanding GenAI's Productivity GainsAs we barrel into the AI-powered era, we can take one of two perspectives:* GenAI products are the next evolution of SaaS: Precise tools for specific workflows* LLMs are the next evolution of social media, where instead of degrading our interpersonal relationships, AI will addict us to easy and often incorrect informationThe majority of the research identified productivity gains and time savings, which would support the goal of GenAI as a professional advantage. But when you dig into the data, there are concerns.Many are funded by Microsoft, OpenAI, and Google, like this one showing that GitHub Copilot users completed tasks 55.8% faster than the control group. While that result was impressive, they were being assessed on their ability to complete a very basic task. The paper's results were boosted by showing that people with less experience benefit more from coding assistants, something that should worry anyone concerned about being replaced by cheaper talent who are boosted by AI.But these results were refuted in a separate study where no DevOps productivity gains were found from using the same GitHub Copilot. That study found the code quality to be poor, leading to a 41% increase in bugs!Remember that GitHub is owned by Microsoft and powered by OpenAI's foundation model, ChatGPT.This contradictory data highlights a paradox of GenAI: The technology is increasingly more successful at a basic task-level, but shouldn't be over-relied on to do our work for us. This Danish study hammers that point home: Time saved by AI offset by new work created. If we shake ourselves out of the AI hype stupor, we can critically examine the current state of LLMs more like SaaS tools. 95% of SaaS tools available won't help you and your business. Once you find the right tool for your hyper-specific use case, the AI product's success will depend on its implementation and the first-party data entered into it.Thanks for reading Design of AI: Strategies for Product Teams & Agencies! More Research about Using AIBehavioural research about AI should be considered a counterpoint to the benefits of AI. Yes, leveraging GenAI will have productivity gains in specific circumstances. But the technology also brings with it risks and considerations that built into the design and business case of “should we build this” discussions.* Increased AI use linked to eroding critical thinking skills* When experiencing time pressures, we're more susceptible to misinformation* AI systems are already capable of deceiving humans* People Facing Life-or-Death Choice Put Too Much Trust in AI* AI's Trust Problem: Twelve persistent risks of AI that are driving skepticismCatch up on Recent Design of AI Episodes31. AI is Disrupting Architecture and Lessons for Digital Product TeamsGuest Matthew Krissel (FAIA) explores how AI is reshaping architectural design and what digital product teams can learn about process, creativity, and scale from the built environment.30. Take Control of AI's Predictive Power – Tyler Hochman, ForethoughtTyler Hochman shares how businesses can operationalize AI for forecasting and insights by targeting high-value, repeatable problems and unlocking underutilized data.29. Trust is a Double‑edged Sword: AI will Transform Services – Sarah Gold, Projects by IFSarah Gold explains how AI changes our relationship with services and why it's urgent to rethink trust, transparency, and accountability in product design.28. AI will Transform Product Research – John Whalen, Author & PsychologistJohn Whalen outlines how AI can automate user research tasks and speed up insights while cautioning where human interpretation is still irreplaceable.27. Implementing AI in Creative Teams: Why Adoption Will Surge – Jan Emmanuele, WondercraftJan Emmanuele shares real-world strategies for rolling out AI in creative teams, tracking ROI, and overcoming fear and friction in adoption. 26. Designing a New Relationship with AI – Critical Mindset Shifts for Success – Sara ViennaSara Vienna emphasizes why designers must rethink their role and mindset in an AI-powered world—moving from tool experts to value creators.25. Faster, Cheaper, Better: AI's Transformation of Insights & Strategy – David BoyleDavid Boyle discusses how AI is reducing the cost and time of gathering insights while also introducing new pitfalls that only expert interpretation can avoid. 24. Adding AI to Miro – Case Study in Improving the UX of Existing Products – Ioana TeleanuIoana Teleanu discusses the strategic thinking behind introducing AI to Miro's design tools without compromising the user experience.23. AI in Healthcare: Challenges of Implementing in Complex Industries – Dr. Spencer DornDr. Dorn explores why healthcare has been both cautious and optimistic with AI, offering lessons for anyone deploying AI in regulated or high-stakes fields. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit designofai.substack.com
Five Things You Should Know as a Leader Implementing AIThere is no playbook... YetDo NOT be afraid to experimentAI technology advances quicklyAI will NOT solve everythingBe a responsible leader when implementing AIBONUS - Find the right coach / trainer when implementing AI. Do not go at it alone. You will waste too much time learning outdated materials. How to connect with AgileDad:- [website] https://www.agiledad.com/- [instagram] https://www.instagram.com/agile_coach/- [facebook] https://www.facebook.com/RealAgileDad/- [Linkedin] https://www.linkedin.com/in/leehenson/
Pam Didner, B2B marketing expert and author of The Modern AI Marketer, joins A. Lee Judge to break down why prompting, automation, and AI-driven workflows are now critical for marketers.She shares practical frameworks for individuals, teams, and enterprises - and explains why focusing on workflows (not tools) is the key to staying competitive.If you want real-world strategies to future-proof your marketing career in an AI-first world, this conversation is essential.Conversation points:Why prompting is now a core skill for marketers (not just a tech thing)How to automate repetitive marketing tasks with AIScaling AI across marketing teams without creating chaosWhy chasing AI news headlines wastes time, and what to focus on insteadHow Copilot, ChatGPT, and enterprise AI tools fit into future workflowsPractical frameworks for evolving your marketing career with AI0:00 - The AI News Overload & Introduction to Guest Pam Didner1:51 - Pam's New Book: AI for the Modern Marketer3:46 - B2B Focus & Who the Books Are For4:39 - Is Prompting Now a Core Marketing Skill?5:20 - Will Prompt Engineering Become a Marketing Job?8:12 - Scaling AI in Marketing: Individual, Team, and Enterprise Levels12:40 - Frameworks for Implementing AI & Marketing Workflow Automation15:41 - Automating Repetitive Tasks vs. Human Creativity19:25 - How to Keep Up (or Not) with the Rapid Pace of AI24:08 - Copilot vs. Other LLMs: Enterprise AI Tool Choices28:26 - Final Book Overview & Where to Connect with Pam A. Lee Judge is the creator and host of The Business of Marketing podcast.Please follow the podcast on your favorite podcast listening platform.This podcast is produced by Content Monsta - A leading producer of B2B Content.
Embracing AI Literacy in the Workplace: Insights from John Munsell
In this episode of Detection at Scale, Jack speaks with Jacob DePriest, VP of Security/CISO at 1Password, who shares insights from his 15-year journey from the NSA to leading security at GitHub through his current role. Jacob discusses his framework for assessing security programs with fresh eyes, emphasizing business objectives first, then addressing risks, and finally implementing the right security measures. He also explores how generative AI can enhance security operations while maintaining that human expertise remains essential for understanding threat intent. As 1Password transforms from a password manager to a multi-product security platform, Jacob outlines his approach to scaling security through engineering partnerships and automation, while offering practical leadership advice on building relationships, maintaining work-life balance, and aligning security initiatives with business goals. Topics discussed: Transitioning from engineering to security leadership and how that technical background provides empathy when implementing security controls. Approaching security program assessment by first understanding business objectives, then identifying risks, and finally implementing appropriate measures. Exploring 1Password's evolution from a password management product to a multi-product security company with extended access management. Balancing generative AI's capabilities with human expertise in security operations, recognizing AI's limitations in understanding intent. Leveraging AI to enhance incident response through automated summaries and context gathering to speed up triage processes. Implementing AI applications in GRC functions like vendor reviews and third-party questionnaires to increase efficiency and reduce tedium. Building sustainable security operations by ensuring security tools have proper access to data through education and partnership. Addressing the varying security postures across the vendor landscape through a risk-based approach focusing on access and visibility. Scaling security teams by clearly connecting their work to business objectives and ensuring team members understand why their tasks matter. Three pillars of security leadership: building a trusted network, establishing sustainable work-life balance, and connecting security to business goals. Listen to more episodes: Apple Spotify YouTube Website
In this engaging episode of the Events: Demystified Podcast, host Anca Platon Trifan dives deep into the world of AI with special guest Noah Riley, founder of AI Genius Automations. They explore how AI is transforming the way we work, think, and create, and provide practical advice for businesses and individuals looking to implement AI. Key topics discussed include the right mindset for adopting AI, practical applications of AI tools, and ensuring privacy and security in AI implementation. Discover how to leverage AI to streamline processes, improve efficiency, and reclaim valuable time. Stay tuned for real-world examples and expert insights, and don't miss the closing advice on staying curious and prioritizing effectively.00:00 Introduction to AI and the Podcast02:11 Meet Noah Riley: AI Visionary03:48 A Humorous Encounter: How We Met07:56 The Chess and Jiu Jitsu Analogy12:11 Noah's Journey: From Graphic Design to AI17:18 The Neuroscience of Design and Events18:49 AI Implementation Challenges and Mindset25:00 Privacy, Security, and AI Risks42:07 Practical AI Strategies for Businesses44:04 Exploring AI Solutions for Businesses44:28 Taking Risks with New Technology44:54 Implementing AI in Your Company46:00 Diving Deep into GPT Capabilities49:16 Practical AI Examples for Business Owners51:49 Custom GPTs and Their Benefits01:01:55 Automation Tools: Zapier vs. Make01:13:38 Balancing Multiple Interests and Priorities01:20:17 Final Thoughts and Advice on AI ImplementationGUEST BIONoah Riley is the founder and visionary leader of AI Genius Automations. His passion for AI goes beyond his profession, he views it as a transformative technology with the potential to create time and improve people's lives. This belief drives his dedication and passion to understanding AI and making its benefits accessible to individuals and businesses alike. Noah's enthusiasm for AI is contagious, and his ability to explain complex concepts in an approachable manner makes AI understandable, accessible, and appealing to diverse audiences. His unique blend of expertise and charisma makes learning about AI both informative and enjoyable. Under Noah's leadership, AI Genius Automations is at the forefront of AI innovation and application, providing cutting-edge solutions that help clients harness the power of AI to achieve their goals.Connect with our Guest at the links below:Noah Riley's LinkedIn https://www.linkedin.com/in/noahrileyaigeniusautomations/ Company Website https://aigeniusautomations.com/Company LinkedIn https://www.linkedin.com/company/aigeniusautomations/YouTube: www.youtube.com/@StaceyHankeTwitter: https://twitter.com/staceyhankeincInstagram: www.instagram.com/staceyhankeincConnect with your Podcast Host at the links below:Speaker website: https://ancaplatontrifan.me/LinkedIn: https://www.linkedin.com/in/ancatrifan/Instagram: https://www.instagram.com/anca.platon.trifanInstagram: https://www.instagram.com/fit.mindful.maven/Instagram: https://www.instagram.com/eventsdemystifiedpodcast/
Kevin Werbach speaks with Medha Bankhwal and Michael Chui from QuantumBlack, the AI division of the global consulting firm McKinsey. They discuss how McKinsey's AI work has evolved from strategy consulting to hands-on implementation, with AI trust now embedded throughout their client engagements. Chui highlights what makes the current AI moment transformative, while Bankwhal shares insights from McKinsey's recent AI survey of over 760 organizations across 38 countries. As they explain, trust remains a major barrier to AI adoption, although there are geographic differences in AI governance maturity. Medha Bankhwal, a graduate of Wharton's MBA program, is an Associate Partner, as well as Co-founder of McKinsey's AI Trust / Responsible AI practice. Prior to McKinsey, Medha was at Google and subsequently co-founded a digital learning not-for-profit startup. She co-leads forums for AI safety discussions for policy + tech practitioners, titled “Trustworthy AI Futures” as well as a community of ex-Googlers dedicated to the topic of AI Safety. Michael Chui is a senior fellow at QuantumBlack, AI by McKinsey. He leads research on the impact of disruptive technologies and innovation on business, the economy, and society. Michael has led McKinsey research in such areas as artificial intelligence, robotics and automation, the future of work, data & analytics, collaboration technologies, the Internet of Things, and biological technologies. Episode Transcript The State of AI: How Organizations are Rewiring to Capture Value (March 12, 2025) Superagency in the workplace: Empowering people to unlock AI's full potential (January 28, 2025) Building AI Trust: The Key Role of Explainability (November 26, 2024) McKinsey Responsible AI Principles
In this episode of Detection at Scale, Matthew Martin, Founder of Two Candlesticks, shares practical approaches for implementing AI in security operations, particularly for smaller companies and those in emerging markets. Matthew explains how AI chatbots can save analysts up to 45 minutes per incident by automating initial information gathering and ticket creation. Matthew's conversation with Jack explores critical implementation challenges, from organizational politics to data quality issues, and the importance of making AI decisions auditable and explainable. Matthew emphasizes the essential balance between AI capabilities and human intuition, noting that although AI excels at analyzing data, it lacks understanding of intent. He concludes with valuable advice for security leaders on business alignment, embracing new technologies, and maintaining human connection to prevent burnout. Topics discussed: Implementing AI chatbots in security operations can save analysts approximately 45 minutes per incident through automated information gathering and ticket creation. Political challenges within organizations, particularly around AI ownership and budget allocation, often exceed technical challenges in implementation. Data quality and understanding are foundational requirements before implementing AI in security operations to ensure effective and reliable results. The balance between human intuition and AI capabilities is crucial, as AI excels at data analysis but lacks understanding of intent behind actions. Security teams should prioritize making AI decisions auditable and explainable to ensure transparency and accountability in automated processes. Generative AI lowers barriers for both attackers and defenders, requiring security teams to understand AI capabilities and limitations. In-house data processing and modeling are preferable for sensitive customer data, with clear governance frameworks for privacy and security. Future security operations will likely automate many Tier 1 and Tier 2 functions, allowing analysts to focus on more complex issues. Security leaders must understand their business thoroughly to build controls that align with how the company generates revenue. Technology alone cannot solve burnout issues; leaders must understand their people at a human level to create sustainable efficiency improvements.
I'm Josh Kopel, a Michelin-awarded restaurateur and the creator of the Restaurant Scaling System. I've spent decades in the industry, building, scaling, and coaching restaurants to become more profitable and sustainable. On this show, I cut through the noise to give you real, actionable strategies that help independent restaurant owners run smarter, more successful businesses.In this episode, I break down how AI can be a game-changer for restaurant owners, not by replacing people, but by freeing them up to focus on what actually matters. We're talking automation, streamlined marketing, and strategic delegation—because the secret to scaling isn't working harder, it's working smarter. I'll walk you through how AI and well-crafted SOPs can help you reclaim your time, reduce the daily chaos, and set your restaurant up for long-term success. And here's the kicker—you don't have to overhaul everything overnight. Start small, build momentum, and watch how AI helps take your business to the next level.Takeaways:Money is the primary problem for restaurant owners.AI can help delegate tasks effectively.Overwhelm often comes from mismanaged tasks.Automated task audits can identify inefficiencies.AI can create structured SOPs from recorded tasks.Marketing consistency is key for restaurant success.AI can generate comprehensive marketing calendars.Engagement can increase with AI-driven marketing.Start with small AI implementations for better results.AI is a tool to amplify leadership in restaurants.Chapters00:00 Introduction to Restaurant Profitability02:06 Leveraging AI for Restaurant Efficiency05:49 Streamlining Marketing with AI10:03 Implementing AI in Manageable StepsIf you've got a marketing or profitability related question for me, email me directly at josh@joshkopel.com and include Office Hours in the subject line. If you'd like to scale the profitability of your restaurant in only 5 days, sign up for our FREE 5 Day Restaurant Profitability Challenge by visiting https://joshkopel.com.
Vin Vashishta and I chat about the current state of AI in business, the challenges of implementation, the pervasive hype surrounding AI technologies, influencers, and more.
In this episode of the Tech for Business podcast, Todd, the COO and CISO, along with Ann, a Quality Assurance Analyst, discuss the complexities and compliance challenges businesses face with AI. They elaborate on the evolution of AI, regulatory frameworks, privacy concerns, and the ethical implications of using AI. They also provide insights on how companies can prepare for emerging regulations and share practical steps for implementing AI responsibly. As AI adoption accelerates, understanding these factors becomes crucial for staying compliant and maintaining ethical standards in business operations.Resources: https://www.scrut.io/post/eu-artificial-intelligence-ai-act https://www.scrut.io/post/ai-compliance 00:00 Introduction to Compliance Challenges in AI00:57 The Evolution and Waves of AI02:35 Privacy and Security Concerns05:34 Historical Context and Ethical Considerations09:48 AI in Banking and Healthcare21:01 Implementing AI in Compliance23:12 Preparing for Future Regulations29:52 Final Thoughts and Future Discussions
Agent Marketer Podcast - Real Estate Marketing for the Modern Agent
Send us a textIn this episode of The MLO Project, Frazier and Michael dig into one of the biggest shifts in the mortgage industry right now: AI integration. From AI agents to automated consumer engagement, they break down how this tech is already changing the way leads are generated and converted.But here's the catch—automation can't replace connection. The hosts explore how to keep the human touch while using AI to scale smarter, not just faster.They also look ahead at where AI is taking mortgage services and why adapting early will give you the edge. Plus, a reminder that no one has to do it alone—this episode is a call to build a collaborative community that learns, shares, and grows together.Hit play and find out how to stay relevant, stand out, and use AI without losing the personal edge that actually closes deals.TakeawaysAI is becoming a significant part of the mortgage industry.Understanding how to use AI tools is crucial for loan officers.AI agents can enhance lead generation and consumer engagement.Maintaining a human touch is essential in AI interactions.The technology is not perfect; it requires strategic implementation.Loan officers must adapt to stay competitive in the evolving market.Continuous learning and adaptation are necessary to leverage AI effectively.Chapters00:00 Welcome to the MLO Project02:10 The Rise of AI in the Mortgage Industry04:18 Understanding AI Agents08:04 Implementing AI in Lead Generation11:31 The Role of AI in Consumer Engagement15:43 Navigating AI Limitations18:50 The Future of AI in Mortgage Services22:18 Building a Collaborative CommunityJoin our HighLevel Facebook GroupTMP is presented by: Empower LOConnect with us at mloproject@empowerlo.com
Marketing Expedition Podcast with Rhea Allen, Peppershock Media
Meet Sarah Noel Block, your Marketing Strategist friend. Sarah has rocked the content world for 16 years. She's supported big shots like apartments.com and Prudential, but her heart lies with small teams. As the creator of the StrategicSpark Workshop, the StrategicStory, and Tiny Marketing Framework, she's a master at helping tiny teams achieve big results. With an award-winning content platform under her belt and featured in Entrepreneur, Forbes, and Thrive, Sarah knows her stuff. Catch her speaking at conferences and dazzling audiences with her wisdom. She's like that favorite teacher who makes learning fun and impactful. Let Sarah guide your marketing journey and unlock the secrets to success.00:00 - 00:27 "The basis of the framework is streamline, systematize, automate, and outsource. So what we're talking about today is the streamline part of it, which is the lean marketing engine. So we'll get into that later, but systematize is, can you build templates around this? Can you create automations around this? Can you use AI for pieces of it? What can we use as an anchor that we can repurpose?” — Sarah Noel Block00:28 - 00:46 Welcome to Peppershock Media's Marketing Expedition Podcast00:47 - 01:34 Sarah's Background01:35 - 08:10 Marketing Essentials Moment: Developing Effective Creative Ads08:11 - 10:57 Welcome to the show, Sarah!10:58 - 12:18 The Lean Marketing System12:19 - 18:52 Implementing AI in Marketing18:53 - 22:31 Success Stories from the Lean Marketing Engine22:32 - 25:09 Understanding Gateway Offers25:10 - 28:16 The Importance of Client Fit28:17 - 29:16 Hello Audio is the best format for creating a connection between you and your audience and allows them to access your zone of genius at the click of a button.29:17 - 31:49 Building Trust with Clients31:50 - 33:12 Setting Expectations for Marketing33:13 - 38:53 The Role of Collaboration in Marketing38:54 - 39:33 Listen to the Tiny Marketing Podcast and Reach out to Sarah (https://www.sarahnoelblock.com/)39:34 - 40:58 Thank you so much, Sarah! Share this podcast, give us a review, and enjoy your marketing journey!40:59 - 41:45 Join the Marketing Expedition Community today! Like what you hear, but need more information?Meet with Rhea Allen#TinyMarketing #TinyMarketingPodcast #LeanMarketingSystem #AI #AIMarketingTools #MarketingEssentialsMoment #CreativeAds #GatewayOffers #BuildingTrust #Collaboration #FreshMarketingStrategy #MarketingTips Hosted on Acast. See acast.com/privacy for more information.
Highlights from this week's conversation include:Solomon's Background and Journey in Data (0:38)The Importance of a Triple Threat Data Person (5:14)Sports Sponsorship Analysis at Nielsen (7:31)Challenges of Implementing AI in Business (11:09)Understanding Data Delivery Models (14:18)Innovating Data Delivery (17:38)Modern Data Sharing Framework (19:09)Account Management in Data Sharing (23:43)Data Delivery Systems and Skill Sets (26:08)Practical Steps for Monetizing Data (29:02)Building Trust Through Branding (36:51)LinkedIn Personal Branding Tips (40:54)Mastering the Basics (44:16)Professional Development in Data (48:18)Deep Technical Skills (53:18)Active and Outcome-Focused Approach (55:25)Finding Top Data People and Parting Thoughts (56:44)The Data Stack Show is a weekly podcast powered by RudderStack, the CDP for developers. Each week we'll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.RudderStack helps businesses make the most out of their customer data while ensuring data privacy and security. To learn more about RudderStack visit rudderstack.com.
Learn AI in 5 Minutes Per Day: https://www.theaireport.ai/In this episode of The AI Report,Liam Lawson sits down with Bjion Henry, CEO of Navreo.ai, to explore the AI's impact in sales and lead generation in today's world. Discover how Navreo.ai transitioned from a general AI automation agency to a niche-focused leader in AI-driven sales strategies. Bijon also shares insights into automating outbound sales, the importance of personal branding, and the future of AI in business.Topics Covered:The evolution of Navreo.ai's business modelImplementing AI in sales processesStrategies for effective personal branding on LinkedInClient success stories and ideal business profilesBijon's entrepreneurial journey and lessons learnedOver 400,000 OpenAI, Apple & NASA professionals read The AI Report. We'll teach you how to leverage AI to make money/save time in just 5 minutes.Join our free community now: https://www.skool.com/the-ai-report-community/aboutConnect with Bijon: https://www.linkedin.com/in/bjionhenry/(00:00) Preview(00:57) Using AI to Book Meetings Without Growing Headcount(05:32) Navreo.ai's Niche-Focused Lead Gen(07:26) Navreo.ai's Two-Pillar Strategy (Coaching & Infrastructure)(15:46) Bijon's LinkedIn Growth Strategy (8k to 31k followers)(17:27) How Bijon Generated 700+ Calls a Year from LinkedIn Content(23:58) How to Create Viral LinkedIn Lead Magnets(27:46) Building Targeted Lead Lists at Scale with AI(30:46) AI-Powered Lead Qualification & Decision-Making(33:51) Advanced AI Email Personalization Tactics(37:04) The Benefits of AI Automation(39:42) Who Should Use Navreo.ai?(45:01) The Future of AI in Sales(47:23) Navreo.ai's Origin Story(51:52) Bijon's Entrepreneurial Journey & Key Business Lessons(01:03:34) Bijon's Core Motivation: From Validation to Passion
On a Southwest flight to Phoenix a passenger took off their clothes and screamed at the top of their lungs and walked up and down the aisle. A Canadian Olympian is added to an FBI most wanted list after allegedly smuggling drugs. McDonalds is going to start to use AI to reduce wait times for customers. A man who was shot out of a cannonball hit concrete and sustained multiple injuries.See omnystudio.com/listener for privacy information.
There are many reasons to debate the ethics and implications of AI. But while we do that, hundreds of the world's biggest brands are rushing to implement the technology into creative and coding workflows. At a time when shareholders are being unforgiving and policy making is volatile, business leaders are looking to AI to gain any advantage possible.Jan Emmanuele is one of the experts that these Fortune 500 corporations rely on to identify and build GenAI creative workflow augmentations and automations. He works for Superside —whom you might remember from our episode with Philip Maggs (Listen here)— because they're on the leading edge of creating an LLM that interprets your briefing process, design system, brand guidelines, marketing campaigns, and data to automate high-volume creative tasks. In this episode, we focus on how and where AI is applied within organizations and workflows. It details how organizations can prepare themselves for implementing AI and how to address the core barriers and risks of the technology.Listen on Spotify | Listen on Apple PodcastsWhat was most interesting about this conversation was his prediction that the adoption of AI will explode in enterprise orgs starting in 2026 and that it could continue into the 2030s. He believes that the value of AI in enterprise has already been proven and that more use cases exist than anyone can believe. That adoption thus far has only been limited because of legal and procurement policies.If this is true, organizations that aren't already at least planning for this workflow-automated future will soon be at a huge competitive disadvantage. Finding 10x augmentations of creative output is routinely achieved, and more will be possible for organizations with highly-structured and easily-repeatable workflows. The gains will be largest in orgs that leverage the uniquely-LLM capability of contextualizing outputs based on data. Examples include localizing campaigns to micro-niche segments or regions of the world. Thanks for reading Design of AI: Strategies & insights for product teams! This post is public so feel free to share it.Headwinds will reduce the number of creatives earning a living wageAs we barrel towards the increasingly inevitable reliance on LLMs, it puts creatives in the uncomfortable position of fighting for their survival and protesting for what's ethically correct. The music industry is the canary in the coal mine in this battle. Many artists earn the majority of their income from their back catalogues and LLMS are effectively using those albums as mulch to improve generative capabilities. On one side, you have an entire way of life being threatened; on the other, you have artists that will quickly need to learn how to master generative capabilities to become an indispensable musician regardless of the headwinds that will reduce the amount of music earning a living wage. As platforms get better, we'll just generate the music and images we need instead of hiring professionals.Overcoming the uncanny valley: Not being able to determine what was generated by AIWhat has made all of us feel more comfortable has been that AI still sucks at a lot of creative tasks. Blooper reels and countless articles of AI creative generative fails give us hope that the technology isn't ready to replace anyone yet. But we've learned from our latest episode and many previous ones that the technology is much more ready for primetime than we might believe. Many of the failures we see today result from the false sense of confidence the platforms offer novices. While the simplicity of these tools has exploded the amount of experimentation happening, we're flooded with more fails than fantastic examples.Another factor is that the simplicity of the GenAI interfaces obscures the complexity happening in the background. We believe we can generate a campaign-ready 20-second video by typing in a prompt. But the complexity comes from knowing what models, protocols, data sets, and projects to connect for the best outcomes. This is an era dominated by creative technologists who can see these possibilities and stay up-to-date with the latest capabilities.In the hands of someone who understands how to overcome the rawness of the technology, the possibilities are limitless. And for every project we see published, there are at least another dozen working to push those capabilities further in the near future. Sesame is another example of technology overcoming the uncanny valley by delivering conversational voice capabilities indistinguishable from humans. These developments are happening at such a pace that it's impossible to keep up. For example, researchers have created an agentic, autonomous framework that iteratively structures and refines knowledge in situ.The point is that whether you agree with the hype of an AI-powered future or not, businesses everywhere will implement it because the impact is increasingly undeniable. Action items: What can we do to prepare ourselves and our workI hate that the ethics of AI seem like an afterthought to the beating drum of business automation. It's deeply uncomfortable that many professions and industries must adapt or face extinction. The only way to stare into this abyss and feel hopeful is to believe that the rising tide of resentment against big tech will fuel a renaissance of altruistic misfits building the models and layers that do less harm. But that won't calm the nerves of the musicians and artists who see an end to their way of life today.We can mourn the tidal wave of change while also preparing for the new world order that comes next.If you're a creative:* Stop undervaluing yourself and your work. Listen back to yourself explain the work you do. Recognize all the steps, decisions, and life lessons you neglect to mention. You need to document who you are to such a granular level that you spot where your genius is most pronounced and where you're on autopilot. Then consider how to leverage AI to amplify/automate each of those.* Tap into your most significant creative strengths. You are more than your outputs. You fell into this career for a reason and persist because of at least one exceptional creative strength. Document it and the conditions under which it enhances your work more than others. Now find AI tools that can make that happen more often and for longer periods. * Lead the change you want to see. Don't wait for inspiration and innovative products to land in your inbox. Go find them, test them, implement them, and prove if they can or can't help you achieve your goals.If you're a business leader: * Accept that change is coming fast. You can feel unsure about the technology, worried about the risks, and apprehensive about the costs. But you cannot wait to start imagining what the future of your business and industry might look like. Go through future casting exercises and monitor the countless startups slowly eating away at your competitive moat.* Empower your team to succeed. Even if people tell you they aren't worried about the coming change, they probably are. You need to lead them through this and create a shared vision of what the future version of your business and workforce can look like. Include teams in co-creation processes to determine the best ways to empower them to succeed by eliminating barriers and inefficiencies.* Structure your data and production workflows. AI is most effective in highly repetitive situations where success can be easily evaluated. Businesses will succeed that have standardized their key workflows and have structured data that adds critical context about situations and success. Do the work now before an expensive consultant charges you millions once there's a veritable gun to your head due to competitive concerns. Contact me if you need helpThank you for following the Design of AI podcast and this newsletter. This year, we'll spend more time discussing this seemingly insurmountable challenge of implementing AI effectively. Please comment if there are specific questions or topics you need us to discuss. And feel free to vent about topics that you're most frustrated or concerned about so we know what our community needs.We're also hoping to launch some events in major markets this year to bring together early adopters and experimenters with those eager to leverage this technology effectively.And if you need help with any consulting related work related to envisioning your AI-powered future, email me at arpy@ph1.ca Product of the month: RaycastRaycast is a perfect example of the disruptive potential of AI. While everyone else is running to add bullshitty AI features to make using their products easier, others are rewriting the way we interact with digital experiences. Raycast basically looked at MacOS and said, “Let's rebuild the entire finder and launcher experience.”It's ironic for me because one year ago, I worked on a project where the outcome was the real potential value of AI in a mobile phone experience would be as an assistive launcher experience that eliminates all the inefficiencies of Android. Well, here it is! Thanks for reading Design of AI: Strategies & insights for product teams! This post is public so feel free to share it. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit designofai.substack.com
During this episode, hosts Tom and Simon engage in a lively discussion about various historic and contemporary crime cases. They begin with personal banter and discuss Simon's return to Glasgow. The conversation shifts to historical crimes, including the St. Valentine's Day Massacre, detailing Al Capone's gang war, the genesis of forensic ballistics, and the societal aftermath such as the advent of RICO laws.They touch on the 1999 murder case of Jill Dando, delving into the initial conviction and subsequent acquittal of Barry George. This leads to discussing pressures faced by detectives in high-profile cases. The hosts further explore the notorious Salem Witch Trials, comparing the use of 'spectral evidence' then to present-day concerns about evidence integrity.Modern crime analysis through artificial intelligence is evaluated, highlighting its potential but also the ethical dilemmas it presents. The episode revisits the notorious Great Train Robbery of 1963, emphasizing the botched post-crime execution by the robbers and the relentless pursuit by police detective Jack Slipper.Attention is given to the tragic case of police officers Nicola Hughes and Fiona Bone, murdered by Dale Cregan. The subsequent discussion transitions from historical cases to future policing advancements and concludes with reflections on the variable nature of policing work and the dangers faced by officers.Throughout, the hosts blend personal anecdotes with professional insights, discussing everything from historical crime impacts to modern policing technologies and reflections on justice and societal protection.00:00 Welcome and Banter01:02 Upcoming Gigs and Personal Stories02:42 Book Launch Preparations03:37 St. Valentine's Day Massacre14:58 Jill Dando Murder Case21:58 Salem Witch Trials30:35 Unyielding Courage in History30:57 Spectral Evidence and Its Implications31:19 Artificial Intelligence in Crime Prediction31:46 Challenges in Implementing AI in Law Enforcement32:27 The Importance of Accurate Data Input36:10 Bias in Judicial Sentencing39:55 The Great Train Robbery: A Detailed Analysis52:20 Dale Cregan: A Case of Tragic Violence56:46 Concluding Thoughts and Reflections Hosted on Acast. See acast.com/privacy for more information.
Welcome to "Advancement Amplified: AI for IA," a 5-part Pulse Check hosted by Dan Giroux, a higher education marketing and communications leader focused on elevating the strategic impact of Advancement. Advancement is at a pivotal moment. As institutions navigate shifting donor expectations, alumni engagement challenges, financial pressures, and the demand for greater efficiency, AI is emerging as a transformative force.In today's Part 1, Dan Giroux sits down with Matthew Lambert, Senior Vice President for University Advancement at William & Mary, and Dan Frezza, Chief Advancement Officer at the College of Charleston. Together, they explore how artificial intelligence is reshaping the future of institutional advancement, from donor engagement to marketing and career services. With rapid technological shifts, both institutions are leveraging AI-powered tools, including autonomous virtual engagement officers (VEOs), to enhance outreach and optimize fundraising efforts.Related Links:Inside Higher Ed interview with Wren and Wren's websiteAGB magazine article around AIKey TakeawaysAI is not a replacement, but an enhancement. AI tools in advancement free up professionals to focus on high-value tasks while automating routine processes like contact reports and donor outreach.Virtual Engagement Officers (VEOs) are changing the game. AI-driven fundraisers at William & Mary and the College of Charleston are already fostering one-on-one donor relationships, leading to increased engagement and donations.AI adoption requires a culture of innovation. Institutions that embrace risk-taking and long-term thinking are better positioned to leverage AI effectively.Personalization is key. AI tools can customize communication, ensuring alumni and donors receive relevant, engaging content that strengthens their connection to their alma mater.Transparency builds trust. Clearly identifying AI-powered agents in donor interactions helps maintain credibility and donor confidence.Advancement leaders should experiment and iterate. Small-scale testing of AI tools allows teams to refine their approach while minimizing risks.Episode SummaryHow is AI Being Used in Institutional Advancement?AI is playing an increasingly critical role in institutional advancement, helping teams engage donors, streamline operations, and personalize communications. Both William & Mary and the College of Charleston are leveraging AI-driven solutions like virtual engagement officers (VEOs) to handle donor outreach, allowing human fundraisers to focus on high-value relationships. AI is also being integrated into marketing, career services, and student engagement to drive deeper connections across the university ecosystem.What Are Virtual Engagement Officers (VEOs) and How Do They Work?VEOs are AI-powered autonomous fundraisers that manage donor portfolios, initiate personalized conversations, and guide alumni through the giving process. At William & Mary, the VEO named "Wren" is engaging alumni by sharing curated content, answering inquiries, and even suggesting philanthropic opportunities based on donor interests. Similarly, the College of Charleston's VEO, “Alex,” is successfully fostering engagement by tailoring interactions, including crafting poetry for an alum who tested its capabilities.How Do Institutions Ensure AI Enhances, Rather Than Replaces, Human Connection?A key priority for both institutions is maintaining authenticity and transparency in AI-driven interactions. AI fundraisers introduce themselves as virtual engagement officers, rather than impersonating human staff members. Additionally, AI serves as a bridge to real fundraisers, helping schedule meetings or flagging high-potential donors for personal outreach. By handling lower-priority tasks, AI allows advancement professionals to deepen relationships with major donors and alumni in meaningful ways.What Challenges Exist in AI Adoption for Advancement?Implementing AI in institutional advancement comes with hurdles, including skepticism from staff, concerns over data security, and the need for institutional buy-in. Some advancement professionals worry about AI's impact on job security, while others fear losing the human touch in donor relationships. However, leaders like Lambert and Frezza emphasize that AI is not replacing human fundraisers, but rather empowering them to be more efficient and effective.What's Next for AI in Advancement?Both William & Mary and the College of Charleston plan to expand their use of AI beyond fundraising. Future applications may include using AI for student engagement, career advising, and even enrollment marketing. As AI technology continues to evolve, its role in advancement will likely grow, offering new ways to personalize outreach, improve donor experiences, and drive institutional success.AI is no longer a futuristic concept—it's happening now, and institutions that embrace it strategically will have a competitive edge in advancement and fundraising.Guest Names: Matthew Lambert, Senior Vice President of University Advancement, William & Mary; CEO, William & Mary FoundationDan Frezza, Chief Advancement Officer of Institutional Advancement, College of Charleston; CEO, College of Charleston FoundationGuest Socials: Matthew - https://www.linkedin.com/in/matthewtlambert/Dan - https://www.linkedin.com/in/dan-frezza-56203262/Guest Bios: Matthew T. Lambert - Matthew Lambert leads University Advancement at William & Mary, overseeing all alumni engagement, private fundraising and philanthropic outreach, university marketing and communications, and career development & professional engagement efforts. Under his leadership, William & Mary successfully completed its record-breaking $1 billion For the Bold campaign, strengthening the university's culture and philanthropy. As CEO of the William & Mary Foundation, he stewards more than $1 billion in endowments, ensuring long-term financial support for the university. A William & Mary alumnus, Matthew holds degrees from The Ohio State University (M.A.) and the University of Pennsylvania (Ed.D.). Before returning to W&M in 2013, he held leadership roles in Advancement at Georgetown University. In addition to his work in philanthropy, he is an active scholar in public policy and higher education, authoring Privatization and the Public Good (Harvard Education Press) and co-editing Advancing Higher Education (Rowman & Littlefield). Follow Matthew Lambert on LinkedIn. Dan Frezza - Dan Frezza serves as the Chief Advancement Officer at the College of Charleston, leading the university's development, alumni relations, stewardship, and advancement services. In this role, he is responsible for fostering a strong culture of engagement and philanthropy across the institution. As CEO of the College of Charleston Foundation, he oversees institutional fund management and works to grow the university's endowment. Before joining the College of Charleston in 2023, Dan spent over a decade at William & Mary, where he played a key leadership role in the university's $1 billion For the Bold campaign alongside Matthew Lambert—driving alumni engagement and participation efforts. Prior to that, he led advancement programs at Appalachian State University and East Carolina University. Dan holds a Master's in Higher Education Administration from North Carolina State University and a Bachelor's in Communication with a minor in Business from Western Carolina University. Follow Dan on LinkedIn. - - - -Connect With Our Co-Hosts:Mallory Willsea https://www.linkedin.com/in/mallorywillsea/https://twitter.com/mallorywillseaSeth Odell https://www.linkedin.com/in/sethodell/https://twitter.com/sethodellAbout The Enrollify Podcast Network:The Higher Ed Pulse is a part of the Enrollify Podcast Network. If you like this podcast, chances are you'll like other Enrollify shows too!Enrollify is made possible by Element451 — the next-generation AI student engagement platform helping institutions create meaningful and personalized interactions with students. Learn more at element451.com.Attend the 2025 Engage Summit! The Engage Summit is the premier conference for forward-thinking leaders and practitioners dedicated to exploring the transformative power of AI in education. Explore the strategies and tools to step into the next generation of student engagement, supercharged by AI. You'll leave ready to deliver the most personalized digital engagement experience every step of the way.Register now to secure your spot in Charlotte, NC, on June 24-25, 2025! Early bird registration ends February 1st -- https://engage.element451.com/register
Rescue Spot founder Nicole Patrick returns to Petworking to share exciting updates about her pet adoption platform. In this in-depth conversation, Nicole reveals how Rescue Spot is transforming the animal welfare landscape by: Launching a major platform upgrade that will integrate data from thousands of shelters Creating the first dedicated fostering website in the industry Implementing AI to provide personalized pet care recommendations Maintaining a free service for shelters while monetizing through strategic partnershipsWe explore how Rescue Spot's universal application system is solving the "clogged pipeline" between pets and adopters, why there's no actual shortage of adoptable pets despite common misconceptions, and how the platform's marketplace model benefits all parties. If you're interested in pet adoption, animal welfare technology, or innovative business models in the pet industry, this episode offers valuable insights into how Rescue Spot is becoming the "eBay of pet adoption."
Higher ed is exhausted—literally. A new report from The Chronicle of Higher Education confirms what many faculty and staff already feel: heavier workloads, fewer resources, and increasing pressure are pushing employees to the brink. But is there a way out? In this episode, Mallory and Seth explore how AI can be a powerful tool in reducing burnout, streamlining workloads, and helping institutions retain their best talent. Plus, they share real-world AI solutions, from automating admin tasks to freeing up time for strategic, high-impact work.Chronicle Articles:Higher Ed Is ExhaustedWhat It's Like to Work in Higher EdKey Takeaways: Burnout is at crisis levels. The Chronicle report shows that 65% of faculty and staff are working more than they were five years ago, often due to layoffs and staffing shortages.It's not just about workload—it's about control. Many higher ed professionals feel overworked, undervalued, and left out of key decision-making processes, leading to higher turnover.AI isn't a magic fix, but it helps. Implementing AI tools can automate repetitive tasks, improve efficiency, and allow employees to focus on more meaningful work.Small AI wins add up. Simple tools like voice-to-text software, AI-powered research assistants, and automated meeting recaps can significantly reduce stress and save time.Leadership must embrace AI for change to happen. Many higher ed leaders aren't using AI themselves, which makes it harder for institutions to adopt these tools at scale.The future of higher ed depends on retaining great talent. If burnout continues unchecked, institutions risk losing experienced professionals, which could impact student outcomes and institutional success.Calls to ActionRegister for the AI Engage Summit to learn practical ways AI can transform your institution. Enrollify.org/engageExperiment with AI tools. Try NotebookLM, ChatGPT, Whisper, or Loom to streamline your daily tasks.Advocate for AI at your institution. Share AI success stories with leadership and push for tools that can lighten workloads.Read the full Chronicle report on burnout in higher ed (linked in the show notes).Subscribe to Enrollify for more episodes on the future of higher ed marketing and enrollment. - - - -Connect With Our Co-Hosts:Mallory Willsea https://www.linkedin.com/in/mallorywillsea/https://twitter.com/mallorywillseaSeth Odell https://www.linkedin.com/in/sethodell/https://twitter.com/sethodellAbout The Enrollify Podcast Network:The Higher Ed Pulse is a part of the Enrollify Podcast Network. If you like this podcast, chances are you'll like other Enrollify shows too!Enrollify is made possible by Element451 — the next-generation AI student engagement platform helping institutions create meaningful and personalized interactions with students. Learn more at element451.com.Attend the 2025 Engage Summit! The Engage Summit is the premier conference for forward-thinking leaders and practitioners dedicated to exploring the transformative power of AI in education. Explore the strategies and tools to step into the next generation of student engagement, supercharged by AI. You'll leave ready to deliver the most personalized digital engagement experience every step of the way.Register now to secure your spot in Charlotte, NC, on June 24-25, 2025! Early bird registration ends February 1st -- https://engage.element451.com/register
Unveiling the Complexities: The Dark Side of AI and Its Real-World Implications In this episode, explore the intricate discussions surrounding AI with experts Marcel Gagné, John Pinard, and Jim Love. Dive into contemporary understandings of AI, its potential threats, and its application in both personal and professional realms. The panel discusses the 'dark side' of AI not to instill fear, but to devise strategies for managing its risks. Topics include AI misconceptions, the potential for AI to misbehave, operational security in AI implementation, and philosophical debates on AI consciousness. The episode emphasizes the importance of critical thinking, debate, and responsible use as AI technologies become increasingly integrated into society. Join the conversation and share your thoughts on AI's evolving landscape. 00:00 Introduction to Project Synapse 00:46 Exploring the Dark Side of AI 01:05 Invitation to Join the Discussion 02:01 Three Key Areas of AI Concerns 02:38 Speculative Risks and Science Fiction Scenarios 03:29 Implementing AI in Corporate Settings 04:37 AI Misbehavior and Security Concerns 07:09 Consciousness and AI 20:04 AI as Hyper-Intelligent Children 29:18 Security and Data Privacy in AI 31:36 Human Weakness in Security 31:50 Social Engineering Tactics 32:37 Security Misconceptions in Engineering 33:11 AI Data Storage and Security 34:45 AI Data Retrieval Concerns 39:05 Testing Security in Development 40:35 Regulatory Challenges with AI 43:26 Bias and Decision Making in AI 46:47 The Importance of Critical Thinking 50:09 The Role of Social Interaction in Business 54:35 AI as a Consultant 01:01:50 The Future of AI and Responsibility 01:04:24 Conclusion and Contact Information
Unveiling the Complexities: The Dark Side of AI and Its Real-World Implications In this episode, explore the intricate discussions surrounding AI with experts Marcel Gagné, John Pinard, and Jim Love. Dive into contemporary understandings of AI, its potential threats, and its application in both personal and professional realms. The panel discusses the 'dark side' of AI not to instill fear, but to devise strategies for managing its risks. Topics include AI misconceptions, the potential for AI to misbehave, operational security in AI implementation, and philosophical debates on AI consciousness. The episode emphasizes the importance of critical thinking, debate, and responsible use as AI technologies become increasingly integrated into society. Join the conversation and share your thoughts on AI's evolving landscape. 00:00 Introduction to Project Synapse 00:46 Exploring the Dark Side of AI 01:05 Invitation to Join the Discussion 02:01 Three Key Areas of AI Concerns 02:38 Speculative Risks and Science Fiction Scenarios 03:29 Implementing AI in Corporate Settings 04:37 AI Misbehavior and Security Concerns 07:09 Consciousness and AI 20:04 AI as Hyper-Intelligent Children 29:18 Security and Data Privacy in AI 31:36 Human Weakness in Security 31:50 Social Engineering Tactics 32:37 Security Misconceptions in Engineering 33:11 AI Data Storage and Security 34:45 AI Data Retrieval Concerns 39:05 Testing Security in Development 40:35 Regulatory Challenges with AI 43:26 Bias and Decision Making in AI 46:47 The Importance of Critical Thinking 50:09 The Role of Social Interaction in Business 54:35 AI as a Consultant 01:01:50 The Future of AI and Responsibility 01:04:24 Conclusion and Contact Information
Artificial intelligence is moving at breakneck speed, and mental health professionals are scrambling to keep up. In this episode of Psyched to Practice, Paul and Ray welcome Dr. Dan Florell—professor, psychologist, and AI expert—to break down how AI is reshaping clinical work, research, and education. Is AI a game-changing tool or a legal and ethical minefield? We cover the risks, rewards, and practical ways you can start integrating AI into your practice today. Don't get left behind—tune in now to stay ahead of the curve.To hear more and stay up to date with Paul Wagner, MS, LPC and Ray Christner, Psy.D., NCSP, ABPP visit our website at: http://www.psychedtopractice.com Please follow the link below to access all of our hosting sites. https://www.buzzsprout.com/2007098/share “Be well, and stay psyched” #mentalhealth #podcast #psychology #psychedtopractice #counseling #socialwork #MentalHealthAwareness #ClinicalPractice #mentalhealth #podcast
In this conversation, Ryan Worobel shares his extensive experience in the technology sector, discussing the evolution from traditional monitoring to observability. He highlights the cultural and technical challenges organizations face during this transition, emphasizing the importance of collaboration and data management. Ryan also explores the role of AI in enhancing IT operations, advocating for a balance between automation and human expertise. He provides insights on implementing AI in organizations, the risks and opportunities associated with it, and the necessity of understanding company culture for successful adoption.Key TakeawaysObservability requires a cultural shift towards collaboration.Data management is crucial to avoid overwhelming teams.AI is transforming IT from reactive to proactive approaches.Organizations must start small when implementing AI.Understanding company culture is key to AI adoption.Uptime is essential; downtime is no longer acceptable.AI should supplement human expertise, not replace it.Effective data sorting can reduce noise in decision-making.Innovation is necessary to maintain a competitive edge.Organizations need to establish governance around AI usage.Chapters00:00 Introduction to Ryan Worobel and His Journey07:37 Proactive vs Reactive Approaches in IT13:31 Implementing AI in Organizations19:31 Conclusion and How to Connect with Ryan
Hear Matt Yates explore the transformative role of AI in contact centers, discussing technologies like natural language processing and sentiment analysis. They delve into the balance between AI efficiency and the irreplaceable human touch in customer service, highlighting the importance of transparency, training, and continuous improvement in AI integration.Key TakeawaysAI is revolutionizing contact centers and customer interactions.Natural language processing is key to understanding customer sentiment.Human agents are essential for nuanced customer interactions.AI models are not 100% accurate and can introduce bias.Transparency in AI decision-making is crucial for customer trust.Organizations should balance AI efficiency with human emotional intelligence.Predictive analytics can enhance customer loyalty and service.Continuous training is necessary for both agents and AI systems.Implementing AI should be done gradually to avoid disruption.Data-driven decision-making is vital for successful AI integration.Chapters00:00 Introduction to AI in Contact Centers06:02 The Role of Human Agents in AI-Driven Environments11:49 Ensuring Transparency and Accountability in AI17:53 Using Predictive Analytics for Customer Loyalty
Bio Bala has rich experience in retail technology and process transformation. Most recently, he worked as a Principal Architect for Intelligent Automation, Innovation & Supply Chain in a global Fortune 100 retail corporation. Currently he works for a luxury brand as Principal Architect for Intelligent Automation providing technology advice for the responsible use of technology (Low Code, RPA, Chatbots, and AI). He is passionate about technology and spends his free time reading, writing technical blogs and co-chairing a special interest group with The OR Society. Interview Highlights 02:00 Mentors and peers 04:00 Community bus 07:10 Defining AI 08:20 Contextual awareness 11:45 GenAI 14:30 The human loop 17:30 Natural Language Processing 20:45 Sentiment analysis 24:00 Implementing AI solutions 26:30 Ethics and AI 27:30 Biased algorithms 32:00 EU AI Act 33:00 Responsible use of technology Connect Bala Madhusoodhanan on LinkedIn Books and references · https://nymag.com/intelligencer/article/ai-artificial-intelligence-chatbots-emily-m-bender.html - NLP · https://www.theregister.com/2021/05/27/clearview_europe/ - Facial Technology Issue · https://www.designnews.com/electronics-test/apple-card-most-high-profile-case-ai-bias-yet - Apple Card story · https://www.ft.com/content/2d6fc319-2165-42fb-8de1-0edf1d765be3 - Data Centre growth · https://www.technologyreview.com/2024/02/06/1087793/what-babies-can-teach-ai/ · Independent Audit of AI Systems - · Home | The Alan Turing Institute · Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World, Marco Iansiti & Karim R. Lakhani · AI Superpowers: China, Silicon Valley, and the New World, Kai-Fu Lee · The Algorithmic Leader: How to Be Smart When Machines Are Smarter Than You, Mike Walsh · Human+Machine: Reimagining Work in the Age of AI, Paul R Daugherty, H. James Wilson · Superintelligence: Paths, Dangers, Strategies, Nick Bostrom · The Alignment Problem: How Can Artificial Intelligence Learn Human Values, Brian Christian · Ethical Machines: Your Concise Guide to Totally Unbiased, Transparent, and Respectful AI, Reid Blackman · Wanted: Human-AI Translators: Artificial Intelligence Demystified, Geertrui Mieke De Ketelaere · The Future of Humanity: Terraforming Mars, Interstellar Travel, Immortality, and Our Destiny Beyond, Michio Kaku, Feodor Chin et al Episode Transcript Intro: Hello and welcome to the Agile Innovation Leaders podcast. I'm Ula Ojiaku. On this podcast I speak with world-class leaders and doers about themselves and a variety of topics spanning Agile, Lean Innovation, Business, Leadership and much more – with actionable takeaways for you the listener. Ula Ojiaku So I have with me here, Bala Madhusoodhanan, who is a principal architect with a global luxury brand, and he looks after their RPA and AI transformation. So it's a pleasure to have you on the Agile Innovation Leaders podcast, Bala, thank you for making the time. Bala Madhusoodhanan It's a pleasure to have a conversation with the podcast and the podcast audience, Ula. I follow the podcast and there have been fantastic speakers in the past. So I feel privileged to join you on this conversation. Ula Ojiaku Well, the privilege is mine. So could you start off with telling us about yourself Bala, what have been the key points or the highlights of your life that have led to you being the Bala we know now? Bala Madhusoodhanan It's putting self into uncharted territory. So my background is mechanical engineering, and when I got the job, it was either you go into the mechanical engineering manufacturing side or the software side, which was slightly booming at that point of time, and obviously it was paying more then decided to take the software route, but eventually somewhere the path kind of overlapped. So from a mainframe background, started working on supply chain, and then came back to optimisation, tied back to manufacturing industry. Somewhere there is an overlap, but yeah, that was the first decision that probably got me here. The second decision was to work in a UK geography, rather than a US geography, which is again very strange in a lot of my peers. They generally go to Silicon Valley or East Coast, but I just took a choice to stay here for personal reasons. And then the third was like the mindset. I mean, I had over the last 15, 20 years, I had really good mentors, really good peers, so I always had their help to soundboard my crazy ideas, and I always try to keep a relationship ongoing. Ula Ojiaku What I'm hearing is, based on what you said, lots of relationships have been key to getting you to where you are today, both from mentors, peers. Could you expand on that? In what way? Bala Madhusoodhanan The technology is changing quite a lot, at least in the last 10 years. So if you look into pre-2010, there was no machine learning or it was statistics. People were just saying everything is statistics and accessibility to information was not that much, but post 2010, 2011, people started getting accessibility. Then there was a data buzz, big data came in, so there were a lot of opportunities where I could have taken a different career path, but every time I was in a dilemma which route to take, I had someone with whom either I have worked or who was my team lead or manager to guide me to tell me, like, take emotion out of the decision making and think in a calm mind, because you might jump into something and you might like it, you might not like it, you should not regret it. So again, over the course of so many such decisions, my cognitive mind has also started thinking about it. So those conversations really help. And again, collective experience. If you look into the decision making, it's not just my decision, I'm going through conversations that I had with people where they have applied their experience, so it's not just me or just not one situation, and to understand the why behind that, and that actually helps. In short, it's like a collection of conversations that I had with peers. A few of them are visionary leaders, they are good readers. So they always had a good insight on where I should focus, where I shouldn't focus, and of late recently, there has been a community bus. So a lot of things are moving to open source, there is a lot of community exchange of conversation, the blogging has picked up a lot. So, connecting to those parts also gives you a different dimension to think about. Ula Ojiaku So you said community bus, some of the listeners or people who are watching the video might not understand what you mean by the community bus. Are you talking about like meetups or communities that come around to discuss shared interests? Bala Madhusoodhanan If you are very much specifically interested in AI, or you are specifically interested in, power platform or a low code platform, there are a lot of content creators on those topics. You can go to YouTube, LinkedIn, and you get a lot of information about what's happening. They do a lot of hackathons, again, you need to invest time in all these things. If you don't, then you are basically missing the boat, but there are various channels like hackathon or meetup groups, or, I mean, it could be us like a virtual conversation like you and me, we both have some passionate topics, that's why we resonate and we are talking about it. So it's all about you taking an initiative, you finding time for it, and then you have tons and tons of information available through community or through conferences or through meetup groups. Ula Ojiaku Thanks for clarifying. So, you said as well, you had a collection of conversations that helped you whenever you were at a crossroad, some new technology or something emerges or there's a decision you had to make and checking in with your mentors, your peers and your personal Board of Directors almost, that they give you guidance. Now, looking back, would you say there were some turns you took that knowing what you know now, you would have done differently? Bala Madhusoodhanan I would have liked to study more. That is the only thing, because sometimes the educational degree, even though without a practical knowledge has a bigger advantage in certain conversation, otherwise your experience and your content should speak for you and it takes a little bit of effort and time to get that trust among leaders or peers just to, even them to trust saying like, okay, this person knows what he's talking about. I should probably trust rather than, someone has done a PhD and it's just finding the right balance of when I should have invested time in continuing my education, if I had time, I would have gone back two years and did everything that I had done, like minus two years off-set it by two years earlier. It would have given me different pathways. That is what I would think, but again, it's all constraints. I did the best at that point in time with whatever constraints I had. So I don't have any regret per se, but yeah, if there is a magic wand, I would do that. Ula Ojiaku So you are a LinkedIn top voice from AI. How would you define AI, artificial intelligence? Bala Madhusoodhanan I am a bit reluctant to give a term Artificial Intelligence. It's in my mind, it is Artificial Narrow Intelligence, it's slightly different. So let me start with a building block, which is machine learning. So machine learning is like a data labeller. You go to a Tesco store, you read the label, you know it is a can of soup because you have read the label, your brain is not only processing that image, it understands the surrounding. It does a lot of things when you pick that can of soup. You can't expect that by just feeding one model to a robot. So that's why I'm saying like it's AI is a bit over glorified in my mind. It is artificial narrow intelligence. What you do to automate certain specific tasks using a data set which is legal, ethical, and drives business value is what I would call machine learning, but yeah, it's just overhyped and heavily utilised term AI. Ula Ojiaku You said, there's a hype around artificial intelligence. So what do you mean by that? And where do you see it going? Bala Madhusoodhanan Going back to the machine learning definition that I said, it's basically predicting an output based on some input. That's as simple as what we would say machine learning. The word algorithm is basically something like a pattern finder. What you're doing is you are giving a lot of data, which is properly labelled, which has proper diversity of information, and there are multiple algorithms that can find patterns. The cleverness or engineering mind that you bring in is to select which pattern or which algorithm you would like to do for your use case. Now you're channelling the whole machine learning into one use case. That's why I'm going with the term narrow intelligence. Computers can do brilliant jobs. So you ask computers to do like a Rubik's cubes solving. It will do it very quickly because the task is very simple and it is just doing a lot of calculation. You give a Rubik's cube to a kid. It has to apply it. The brain is not trained enough, so it has to cognitively learn. Maybe it will be faster. So anything which is just pure calculation, pure computing, if the data is labelled properly, you want to predict an outcome, yes, you can use computers. One of the interesting videos that I showed in one of my previous talks was a robot trying to walk across the street. This is in 2018 or 19. The first video was basically talking about a robot crossing a street and there were vehicles coming across and the robot just had a headbutt and it just fell off. Now a four year old kid was asked to walk and it knew that I have to press a red signal. So it went to the signal stop. It knew, or the baby knew that I can only walk when it is green. And then it looks around and then walks so you can see the difference – a four year old kid has a contextual awareness of what is happening, whereas the robot, which is supposed to be called as artificial intelligence couldn't see that. So again, if you look, our human brains have been evolved over millions of years. There are like 10 billion neurons or something, and it is highly optimised. So when I sleep, there are different set of neurons which are running. When I speak to you, my eyes and ears are running, my motion sensor neurons are running, but these are all highly optimised. So the mother control knows how much energy should be sent on which neuron, right, whereas all these large language models, there is only one task. You ask it, it's just going to do that. It doesn't have that intelligence to optimise. When I sleep, maybe 90 percent of my neurons are sleeping. It's getting recharged. Only the dream neurons are working. Whereas once you put a model live, it doesn't matter, all the hundred thousand neurons would run. So, yeah, it's in very infancy state, maybe with quantum computing, maybe with more power and better chips things might change, but I don't see that happening in the next five to 10 years. Ula Ojiaku Now, what do you say about Gen AI? Would you also classify generative AI as purely artificial neural intelligence? Bala Madhusoodhanan The thing with generative AI is you're trying to generalise a lot of use cases, say ChatGPT, you can throw in a PDF, you can ask something, or you can say, hey, can you create a content for my blog or things like that, right? Again, all it is trying to do is it has some historical content with which it is trying to come up with a response. So the thing that I would say is humans are really good with creativity. If a problem is thrown at a person, he will find creative ways to solve it. The tool with which we are going to solve might be a GenAI tool, I don't know, because I don't know the problem, but because GenAI is in a hype cycle, every problem doesn't need GenAI, that's my view. So there was an interesting research which was done by someone in Montreal University. It talks about 10 of the basic tasks like converting text to text or text to speech and with a generative AI model or multiple models, because you have a lot of vendors providing different GenAI models, and then they went with task specific models and the thing that they found was the task specific models were cheap to run, very, very scalable and robust and highly accurate, right. Whereas GenAI, if, when you try to use it and when it goes into a production ready or enterprise ready and if it is used by customers or third party, which are not part of your ecosystem, you are putting yourself in some kind of risk category. There could be a risk of copyright issues. There could be a risk of IP issues. There could be risk of not getting the right consent from someone. I can say, can you create an image of a podcaster named Ula? You never know because you don't remember that one of your photos on Google or Twitter or somewhere is not set as private. No one has come and asked you saying, I'm using this image. And yeah, it's finding the right balance. So even before taking the technology, I think people should think about what problem are they trying to solve? In my mind, AI or artificial intelligence, or narrow intelligence can have two buckets, right. The first bucket is to do with how can I optimise the existing process? Like there are a lot of things that I'm doing, is there a better way to do it? Is there an efficient way to do it? Can I save time? Can I save money? Stuff like that. So that is an optimisation or driving efficiency lever. Other one could be, I know what to do. I have a lot of data, but I don't have infrastructure or people to do it, like workforce augmentation. Say, I have 10 data entry persons who are graduate level. Their only job is to review the receipts or invoices. I work in FCA. I have to manually look at it, approve it, and file it, right? Now it is a very tedious job. So all you are doing is you are augmenting the whole process with an OCR engine. So OCR is Optical Character Recognition. So there are models, which again, it's a beautiful term for what our eyes do. When we travel somewhere, we get an invoice, we exactly know where to look, right? What is the total amount? What is the currency I have paid? Have they taken the correct credit card? Is my address right? All those things, unconsciously, your brain does it. Whereas our models given by different software vendors, which have trained to capture these specific entities which are universal language, to just pass, on data set, you just pass the image on it. It just picks and maps that information. Someone else will do that job. But as part of your process design, what you would do is I will do the heavy lifting of identifying the points. And I'll give it to someone because I want someone to validate it. It's human at the end. Someone is approving it. So they basically put a human in loop and, human centric design to a problem solving situation. That's your efficiency lever, right? Then you have something called innovation level - I need to do something radical, I have not done this product or service. Yeah, that's a space where you can use AI, again, to do small proof of concepts. One example could be, I'm opening a new store, it's in a new country, I don't know how the store layout should look like. These are my products. This is the store square footage. Can you recommend me the best way so that I can sell through a lot? Now, a visual merchandising team will have some ideas on where the things should be, they might give that prompt. Those texts can be converted into image. Once you get the base image, then it's human. It's us. So it will be a starting point rather than someone implementing everything. It could be a starting point. But can you trust it? I don't know. Ula Ojiaku And that's why you said the importance of having a human in the loop. Bala Madhusoodhanan Yeah. So the human loop again, it's because we humans bring contextual awareness to the situation, which machine doesn't know. So I'll tie back this to the NLP. So Natural Language Processing, it has two components, so you have natural language understanding and then you have natural language generation. When you create a machine learning model, all it is doing is, it is understanding the structure of language. It's called form. I'm giving you 10,000 PDFs, or you're reading a Harry Potter book. There is a difference between you reading a Harry Potter book and the machine interpreting that Harry Potter book. You would have imagination. You will have context of, oh, in the last chapter, we were in the hilly region or in a valley, I think it will be like this, the words like mist, cold, wood. You started already forming images and visualising stuff. The machine doesn't do that. Machine works on this is the word, this is a pronoun, this is the noun, this is the structure of language, so the next one should be this, right? So, coming back to the natural language understanding, that is where the context and the form comes into play. Just think of some alphabets put in front of you. You have no idea, but these are the alphabet. You recognise A, you recognise B, you recognise the word, but you don't understand the context. One example is I'm swimming against the current. Now, current here is the motion of water, right? My current code base is version 01. I'm using the same current, right? The context is different. So interpreting the structure of language is one thing. So, in natural language understanding, what we try to do is we try to understand the context. NLG, Natural Language Generation, is basically how can I respond in a way where I'm giving you an answer to your query. And this combined is NLP. It's a big field, there was a research done, the professor is Emily Bender, and she one of the leading professors in the NLP space. So the experiment was very funny. It was about a parrot in an island talking to someone, and there was a shark in between, or some sea creature, which basically broke the connection and was listening to what this person was saying and mimicking. Again, this is the problem with NLP, right? You don't have understanding of the context. You don't put empathy to it. You don't understand the voice modulation. Like when I'm talking to you, you can judge what my emotion cues are, you can put empathy, you can tailor the conversation. If I'm feeling sad, you can put a different spin, whereas if I'm chatting to a robot, it's just going to give a standard response. So again, you have to be very careful in which situation you're going to use it, whether it is for a small team, whether it is going to be in public, stuff like that. Ula Ojiaku So that's interesting because sometimes I join the Masters of Scale strategy sessions and at the last one there was someone whose organisational startup was featured and apparently what their startup is doing is to build AI solutions that are able to do sentiment analysis. And I think some of these, again, in their early stages, but some of these things are already available to try to understand the tone of voice, the words they say, and match it with maybe the expression and actually can transcribe virtual meetings and say, okay, this person said this, they looked perplexed or they looked slightly happy. So what do you think about that? I understand you're saying that machines can't do that, but it seems like there are already organisations trying to push the envelope towards that direction. Bala Madhusoodhanan So the example that you gave, sentiment of the conversation, again, it is going by the structure or the words that I'm using. I am feeling good. So good, here is positive sentiment. Again, for me the capability is slightly overhyped, the reason being is it might do 20 percent or 30 percent of what a human might do, but the human is any day better than that particular use case, right? So the sentiment analysis typically works on the sentiment data set, which would say, these are the certain proverbs, these are the certain types of words, this generally referred to positive sentiment or a good sentiment or feel good factor, but the model is only good as good as the data is, right? So no one is going and constantly updating that dictionary. No one is thinking about it, like Gen Z have a different lingo, millennials had a different lingo. So, again, you have to treat it use case by use case, Ula. Ula Ojiaku At the end of the day, the way things currently are is that machines aren't at the place where they are as good as humans. Humans are still good at doing what humans do, and that's the key thing. Bala Madhusoodhanan Interesting use case that I recently read probably after COVID was immersive reading. So people with dyslexia. So again, AI is used for good as well, I'm not saying it is completely bad. So AI is used for good, like, teaching kids who are dyslexic, right? Speech to text can talk, or can translate a paragraph, the kid can hear it, and on the screen, I think one note has an immersive reader, it actually highlights which word it is, uttering into the ears and research study showed that kids who were part of the study group with this immersive reading audio textbook, they had a better grasp of the context and they performed well and they were able to manage dyslexia better. Now, again, we are using the technology, but again, kudos to the research team, they identified a real problem, they formulated how the problem could be solved, they were successful. So, again, technology is being used again. Cancer research, they invest heavily, in image clustering, brain tumours, I mean, there are a lot of use cases where it's used for good, but then again, when you're using it, you just need to think about biases. You need to understand the risk, I mean, everything is risk and reward. If your reward is out-paying the minimum risk that you're taking, then it's acceptable. Ula Ojiaku What would you advise leaders of organisations who are considering implementing AI solutions? What are the things we need to consider? Bala Madhusoodhanan Okay. So going back to the business strategy and growth. So that is something that the enterprises or big organisations would have in mind. Always have your AI goals aligned to what they want. So as I said, there are two buckets. One is your efficiency driver, operational efficiency bucket. The other one is your innovation bucket. Just have a sense check of where the business wants to invest in. Just because AI is there doesn't mean you have to use it right. Look into opportunities where you can drive more values. So that would be my first line of thought. The second would be more to do with educating leaders about AI literacy, like what each models are, what do they do? What are the pitfalls, the ethical awareness about use of AI, data privacy is big. So again, that education is just like high level, with some examples on the same business domain where it has been successful, where it has been not so successful, what are the challenges that they face? That's something that I would urge everyone to invest time in. I think I did mention about security again, over the years, the practice has been security is always kept as last. So again, I was fortunate enough to work in organisations where security first mindset was put in place, because once you have a proof of value, once you show that to people, people get excited, and it's about messaging it and making sure it is very secured, protecting the end users. So the third one would be talking about having secure first design policies or principles. Machine learning or AI is of no good if your data quality is not there. So have a data strategy is something that I would definitely recommend. Start small. I mean, just like agile, you take a value, you start small, you realise whether your hypothesis was correct or not, you monitor how you performed and then you think about scale just by hello world doesn't mean that you have mastered that. So have that mindset, start small, monitor, have constant feedback, and then you think about scaling. Ula Ojiaku What are the key things about ethics and AI, do you think leaders should be aware of at this point in time? Bala Madhusoodhanan So again, ethical is very subjective. So it's about having different stakeholders to give their honest opinion of whether your solution is the right thing to do against the value of the enterprise. And it's not your view or my view, it's a consent view and certain things where people are involved, you might need to get HR, you might need to get legal, you might need to get brand reputation team to come and assist you because you don't understand the why behind certain policies were put in place. So one is, is the solution or is the AI ethical to the core value of the enterprise? So that's the first sense check that you need to do. If you pass that sense check, then comes about a lot of other threats, I would say like, is the model that I'm using, did it have a fair representation of all data set? There's a classic case study on one of a big cloud computing giant using an AI algorithm to filter resumes and they had to stop it immediately because the data set was all Ivy League, male, white, dominant, it didn't have the right representation. Over the 10 years, if I'm just hiring certain type of people, my data is inherently biased, no matter how good my algorithm is, if I don't have that data set. The other example is clarify AI. They got into trouble on using very biased data to give an outcome on some decision making to immigration, which has a bigger ramification. Then you talk about fairness, whether the AI system is fair to give you an output. So there was a funny story about a man and a woman in California living together, and I think the woman wasn't provided a credit card, even though everything, the postcode is the same, both of them work in the same company, and it was, I think it has to do with Apple Pay. Apple Pay wanted to bring in a silver credit card, Apple card or whatever it is, but then it is so unfair that the women who was equally qualified was not given the right credit limit, and the bank clearly said the algorithm said so. Then you have privacy concern, right? So all these generic models that you have that is available, even ChatGPT for that matter. Now you can chat with ChatGPT multiple times. You can talk about someone like Trevor Noah and you can say hey, can you create a joke? Now it has been trained with the jokes that he has done, it might be available publicly. But has the creator of model got a consent saying, hey Trevor, I'm going to use your content so that I can give better, and how many such consent, even Wikipedia, if you look into Wikipedia, about 80 percent of the information is public, but it is not diversified. What I mean by that is you can search for a lot of information. If the person is from America or from UK or from Europe, maybe from India to some extent, but what is the quality of data, if you think about countries in Africa, what do you think about South America? I mean, it is not representing the total diversity of data, and we have this large language model, which has been just trained on that data, right? So there is a bias and because of that bias, your outcome might not be fair. So these two are the main things, and of course the privacy concern. So if someone goes and says, hey, you have used my data, you didn't even ask me, then you're into lawsuit. Without getting a proper consent, again, it's a bad world, it's very fast moving and people don't even, including me, I don't even read every terms and condition, I just scroll down, tick, confirm, but those things are the things where I think education should come into play. Think about it, because people don't understand what could go wrong, not to them, but someone like them. Then there is a big fear of job displacement, like if I put this AI system, what will I do with my workforce? Say I had ten people, you need to think about, you need to reimagine your workplace. These are the ten jobs my ten people are doing. If I augment six of those jobs, how can I use my ten resources effectively to do something different or that piece of puzzle is always, again, it goes back to the core values of the company, what they think about their people, how everything is back, but it's just that needs a lot of inputs from multiple stakeholders. Ula Ojiaku It ties back to the enterprise strategy, there is the values, but with technology as it has evolved over the years, things will be made obsolete, but there are new opportunities that are created, so moving from when people travelled with horses and buggies and then the automotive came up. Yes, there wasn't as much demand for horseshoes and horses and buggies, but there was a new industry, the people who would mechanics or garages and things like that. So I think it's really about that. Like, going back to what you're saying, how can you redeploy people? And that might involve, again, training, reskilling, and investing in education of the workforce so that they're able to harness AI and to do those creative things that you've emphasised over this conversation about human beings, that creative aspect, that ability to understand context and nuance and apply it to the situation. Bala Madhusoodhanan So I was fortunate to work with ForHumanity, an NGO which basically is trying to certify people to look into auditing AI systems. So EU AI Act is now in place, it will be enforced soon. So you need people to have controls on all these AI systems to protect - it's done to protect people, it's done to protect the enterprise. So I was fortunate enough to be part of that community. I'm still working closely with the Operation Research Society. Again, you should be passionate enough, you should find time to do it, and if you do it, then the universe will find a way to give you something interesting to work with. And our society, The Alan Turing Institute, the ForHumanity Society, I had a few ICO workshops, which was quite interesting because when you hear perspectives from people from different facets of life, like lawyers and solicitors, you would think, ah, this statement, I wouldn't interpret in this way. It was a good learning experience and I'm sure if I have time, I would still continue to do that and invest time in ethical AI. As technology, it's not only AI, it's ethical use of technology, so sustainability is also part of ethical bucket if you look into it. So there was an interesting paper it talks about how many data centres have been opened between 2018 to 2024, which is like six years and the power consumption has gone from X to three times X or two times X, so we have opened a lot. We have already caused damage to the environment with all these technology, and just because the technology is there, it doesn't mean you have to use it, but again, it's that educational bit, what is the right thing to do? And even the ESG awareness, people are not aware. Like now, if you go to the current TikTok trenders, they know I need to look into certified B Corp when I am buying something. The reason is because they know, and they're more passionate about saving the world. Maybe we are not, I don't know, but again, once you start educating and, telling those stories, humans are really good, so you will have a change of heart. Ula Ojiaku What I'm hearing you say is that education is key to help us to make informed choices. There is a time and place where you would need to use AI, but not everything requires it, and if we're more thoughtful in how we approach, these, because these are tools at the end of the day, then we can at least try to be more balanced in the risks and taking advantage of opportunities versus the risks around it and the impact these decisions and the tools that we choose to use make on the environment. Now, what books have you found yourself recommending most to people, and why? Bala Madhusoodhanan Because we have been talking on AI, AI Superpower is one book which was written by Kai-Fu Lee. There is this book by Brian Christian, The Alignment Problem: Machine Learning and Human Values alignment of human values and machine it was basically talking about what are the human values? Where do you want to use machine learning? How do you basically come up with a decision making, that's a really interesting read. Then there is a book called Ethical Machines by Reid Blackman. So it talks about all the ethical facets of AI, like biases, fairnesses, like data privacy, transparency, explainability, and he gives quite a detail, example and walkthrough of what that means. Another interesting book was Wanted: Human-AI Translators: Artificial Intelligence Demystified by a Dutch professor, again, really, really lovely narration of what algorithms are, what AI is, where, and all you should think about, what controls and stuff like that. So that is an interesting book. Harvard Professor Kahrim Lakhani, he wrote something called, Competing in the Age of AI, that's a good book. The Algorithmic Leader: How to Be Smart When Machines Are Smarter Than You by Mike Walsh is another good book, which I finished a couple of months back. Ula Ojiaku And if the audience wants to find you, how can they reach out to you? Bala Madhusoodhanan They can always reach out to me at LinkedIn, I would be happy to touch base through LinkedIn. Ula Ojiaku Awesome. And do you have any final words and or ask of the audience? Bala Madhusoodhanan The final word is, again, responsible use of technology. Think about not just the use case, think about the environmental impact, think about the future generation, because I think the damage is already done. So, at least not in this lifetime, maybe three or four lifetimes down the line, it might not be the beautiful earth that we have. Ula Ojiaku It's been a pleasure, as always, speaking with you, Bala, and thank you so much for sharing your insights and wisdom, and thank you for being a guest on the Agile Innovation Leaders Podcast. Bala Madhusoodhanan Thank you, lovely conversation, and yeah, looking forward to connecting with more like minded LinkedIn colleagues. Ula Ojiaku That's all we have for now. Thanks for listening. If you liked this show, do subscribe at www.agileinnovationleaders.com or your favourite podcast provider. Also share with friends and do leave a review on iTunes. This would help others find this show. I'd also love to hear from you, so please drop me an email at ula@agileinnovationleaders.com Take care and God bless!
In this insightful episode, Albert Thompson, Managing Director, Digital Innovation at Walton Isaacson (https://www.waltonisaacson.com/), shares his forward-thinking take on where programmatic advertising is headed. He challenges the industry to rethink outdated processes, improve partnerships, and embrace smarter ways of working. Looking ahead to 2025, Albert highlights AI's potential to eliminate inefficiencies, spark creativity, and redefine how brands tell their stories and connect with audiences. Beyond technology, Albert dives into the importance of training—not just for newcomers, but for everyone. He emphasizes that staying curious and continuously learning is the key to staying relevant in a fast-changing, AI-driven world. He shares personal experiences and strategic insights on why companies should prioritize education at all levels to stay ahead of the curve. One of the most exciting parts of the discussion? Albert's take on "agentic AI"—a game-changing concept where AI-powered agents go beyond human capabilities to transform industries. He explores how this shift will impact everything from creative strategy to how brands measure and capture consumer attention. From the evolving role of AI in programmatic advertising to the future of consumer engagement, Albert offers a fresh and engaging perspective on what's next in the digital space. About Us: Our mission is to teach historically excluded people how to get started in programmatic media buying and find a dream job. We do so by providing on-demand lessons via the Reach and Frequency® program (https://reachandfrequencycourse.thinkific.com ), a dope community with like-minded programmatic experts, and live free and paid group coaching. We can help 2 ways: Customized a training roadmap for teams of programmatic traders (https://www.heleneparker.com/workshop/ ), adops, customer success, AMs, etc focusing on campaigns performance increase, cross-departmental communication, and revenue growth overall
In this episode of In The Trenches, Dave and Jake from VenueNow share their evaluation of www.relevanceai.com with Don and Duncan from Tribe Global Ventures. The Ben AI YouTube channel referenced: https://www.youtube.com/@BenAI92 hello@tribeglobal.vc
In this episode of Casual Cattle Conversations, Shaye Koester-Wanner discusses the significance of crossbreeding in the beef industry with Dr. Bob Weaber. They explore how crossbreeding can enhance the efficiency and profitability of ranch operations, the importance of discipline in managing crossbreeding systems, and the value added by crossbred cows and calves. The conversation also delves into the economic implications of crossbreeding, the challenges faced by ranchers, and the various systems that can be implemented based on the size of the operation. The episode emphasizes the need for strategic planning and management in crossbreeding practices to maximize benefits. Chapters 00:00 Introduction to Crossbreeding in Beef Production 05:12 The Impact of Crossbreeding on the Beef Supply Chain 10:23 Economic Considerations and Profitability of Crossbreeding 19:22 Challenges and Mismanagement in Crossbreeding Systems 22:11 Value of Crossbred Cows and Calves 30:13 Popular Crossbreeding Systems for Different Ranch Sizes 42:02 Implementing AI and Technologies in Crossbreeding 44:53 Focus Areas for Successful Crossbreeding Management Additional Resources: Find Your Next Herd Sire: https://bit.ly/bullpen-ccc Connect with Bob: bweaber@ksu.edu https://ebeef.ucdavis.edu/ Bob's Slides: https://bit.ly/CCC-resources Goal-setting System for Ranchers: https://www.casualcattleconversations.com/ranchermind-events/p/move-the-ranch-forward-2025
“Limitless.” That's how Kishan Chetan, the Executive VP and GM of Salesforce Service Cloud, describes the future of AI in customer service. Kishan Chetan explains why customer experience has evolved from deflecting customer interaction and how state-of-the-art tools like Agentforce are the key to providing proactive customer engagement, meaningful connection for employees and customers alike, and equitable accessibility for every type of customer. Whether you're searching for that hidden, game-changing data that's currently free-floating in an untitled spreadsheet, or you need to centralize your customer's feedback so every department offers impeccable service, or you simply want to know how to choose, pilot, and customize the right AI tool for your business… this episode is for you.Key Moments:00:00 Introduction to Customer Efficiency00:41 Transforming Customer Service with AI02:06 The Limitless Future of AI03:48 Proactive and Reactive AI Service05:47 Introducing Agentforce07:49 AI Agents vs. Chatbots09:43 Human and AI Collaboration17:15 Real-World Examples of AI in Action22:58 Leveraging Unstructured Data for Better Operations23:20 Unified Knowledge: Powering AI with Comprehensive Data24:03 Challenges in Centralizing Data for AI25:55 Importance of Quality Data and Human Curation26:47 Practical Tips for Implementing AI in Customer Service28:16 Choosing the Right Channels for Customer Interaction29:21 Balancing AI and Human Interaction31:37 Piloting AI Solutions for Maximum Impact32:23 Creating Exceptional Customer Experiences with AI36:04 Future Trends in AI and Customer Service38:25 Potential Pitfalls and Considerations41:34 Optimizing Customer Experience: Real-World Examples44:04 Advice for Customer Experience Leaders –Are your teams facing growing demands? Join CX leaders transforming their strategies with Agentforce. Start achieving your ambitious goals. Visit salesforce.com/agentforce Mission.org is a media studio producing content alongside world-class clients. Learn more at mission.org
Is your construction business running like a well-oiled machine? Learn about business function charts and how to streamline operations and maximize efficiency with the use of Ai!Time Stamps01:54 - Martin's 50th Reunion Story06:32 - Experimenting with AI Tools18:43 - AI's Impact on Jobs25:15 - Getting Started with AI25:59 - Automating Business Processes with AI31:18 - Creating Knowledge Bases with ChatGPT31:41 - Automating Email Responses35:53 - Leveraging AI for Task Delegation37:54 - Hiring & SOPs42:47 - Building Effective Function Charts50:30 - Maximizing Business Efficiency with Function Charts54:58 - Evaluating Employee Performance58:11 - Making Tough Decisions on Staffing01:00:04 - Eliminating Redundancies01:01:37 - Episode OutroSnippets from the Episode"AI is not going to eliminate jobs. It's not taking anybody's job, especially in construction for that matter. But, the person who's gonna take your job is the person who uses Ai." -Khalil"If you had a function chart, and you had bullet points for each function, you would be in the top 3 percent of all businesses in the world for organization." - Martin24 Things Construction Business Owners Need to Successfully Hire & Train an Executive AssistantResourcesCheck out OpenPhoneBuild a Business that Runs without you. Explore our GrowthKits Need Marketing Help? We Recommend BenaliNeed Help with podcast production? We recommend DemandcastMore from Martin Hollandtheprofitproblem.comannealbc.com Email MartinMeet With MartinLinkedInFacebookInstagramMore from Khalilbenali.com Email KhalilMeet With KhalilLinkedInFacebookInstagramMore from The Cashflow ContractorSubscribe to our YouTube channelFollow On Social: LinkedIn, Facebook, Instagram, X(formerly Twitter)Visit our websiteEmail The Cashflow Contractor
Enhancing Pediatric Practices with Technology: Security, Efficiency, and AI IntegrationThis episode is sponsored by our friends at Freed.ai. Without their generous contribution, the show would not be possible. Dr. Rougu uses this product daily, and as he says, "It has changed my life. I don't work anymore." Please visit their website and support our sponsors. In this episode, we meet with Dr. Igor Trogan, a physician executive leader, to discuss technology that enhances medical practice quality, maximizes profits, and prevents physician burnout. Dr. Trogan shares insights into using security systems like Ring to monitor office activities, integrating electronic door locks, and employing virtual medical assistants (VMAs) from the Philippines for cost-effective staffing. The conversation also covers the usage of AI medical scribes like Freed AI to reduce documentation burdens, improve workflow efficiency, and various technology solutions like voice-over IP for better communication and patient care.00:00 Introduction and Guest Welcome00:23 Importance of Technology in Medical Practices01:56 Security Systems in Medical Offices05:45 Managing Multiple Office Locations13:52 Vaccine Storage and Monitoring21:05 Text-Enabled Communication Systems29:37 AI Medical Scribes: A Game Changer30:36 The Benefits of Voice Over IP in Medical Practices34:16 Efficient Call Center Operations38:38 Leveraging Virtual Medical Assistants49:54 Implementing AI for Documentation01:02:51 Conclusion and Final ThoughtsSupport the show
Management Development Unlocked - Management & Leadership Training
On this episode of Management Development Unlocked, Eric welcomes Jen Recla to the show. Jen works in the coaching and team development space, helping leaders build engaged, collaborative, and resilient teams. She uses coaching, team development work, leading retreats, and leadership workshops. Jen is a believer in the use of fun and levity to improve team dynamics and project outcomes. She has 12 years of experience in this space, leading teams and learning functions at various organizations before opening her business. In this episode, you'll hear:Jen Recla's work with leaders and what she offers them.How fun can help develop a high-performing team by reducing stress and burnout, creating connections, building trust, and improving communication.Incorporating fun to improve team dynamics and project outcomes and one of Jen's favorite activities to do this.Implementing AI into your team-building activities.Balancing productivity with a fun and engaging environment and asking for feedback.The practicalities of introducing fun into your team environment.Using small gestures to ingrain levity into your day-to-day environment.Jen's advice for leaders uncomfortable introducing fun into a traditional or serious workplace culture.The risks of adding in fun and creating toxic positivity.The services Jen offers to her clients and organizations.Connect with Jen Recla:LinkedInWebsite---Head over to girardtrainingsolutions.com to take a look at the 20+ courses I offer for new and experienced managers! Get your copy of the Amazon #1 Bestseller and #1 New Release Lead Like a Pro - The Essential Guide for New Managers while you're there!Connect with me on LinkedIn.Please subscribe and comment!
This week Morgan DeBaun discusses the ever-evolving world of AI with artificial intelligence leader, advisor, and investor, Allie K. Miller. Morgan is on a mission to help listeners harness the power of AI in their everyday lives, and Allie is here to share her wealth of knowledge on working smarter, not harder, with cutting-edge tools. In this episode: 00:00 Introduction and Guest Welcome 00:21 The Evolution of AI Tools 00:53 Implementing AI in Daily Workflows 02:00 Allie K. Miller's AI Journey 06:32 Customizing AI for Personal Use 10:36 Advanced AI Usage and Tips 14:42 Stages of AI Adoption 19:52 The Power of Google Gemini 21:12 AI in Personal and Professional Life 22:57 Transitioning to an AI-First Culture 27:43 Challenges in AI Integration 28:45 Advice for AI Adoption 33:39 Exploring Unconventional AI Tools 38:40 Final Thoughts and Resources In the episode, Morgan and Allie share personal examples of how they each integrate AI into daily routines and business operations, discussing how tools like ChatGPT, Otter AI, and Google Gemini can increase productivity. Allie offers actionable insights on integrating AI into daily workflows to boost productivity and spark creativity. Morgan and Allie also discuss the evolution of AI adoption and how individuals and companies can transition to an AI-first culture. They consider the challenges of introducing AI tools within larger organizations and share strategies for leveraging AI as a competitive advantage. Allie highlights the value of experimenting with AI, forming communities for shared learning, and exploring multimodal AI tools that combine text, voice, and visuals. The conversation also touches on the future of AI in entrepreneurship, predicting a wave of AI-driven startups and the potential for one-person unicorn companies. Whether you're new to AI or interested in taking your AI use to the next level, this episode offers insights to help you work smarter and adapt to the ever-evolving AI landscape. Tune in to discover how you can leverage AI to transform your productivity and creativity in life and business! More from Allie: https://www.alliekmiller.com/ https://www.linkedin.com/in/alliekmiller/ https://www.instagram.com/alliekmiller/Join the Newsletter for More Exclusive Content: https://worksmartprogram.ac-page.com/thejourneypodcast Make sure you are following Morgan's journey on TikTok: https://www.tiktok.com/@morgandebaun?_ Visit Mormatcha.com to make a purchase. Follow us on Instagram: https://instagram.com/thejourneybymdb Produced by MicMoguls.
Implementing AI is about more than just adopting technology—it's about bringing people along for the journey. Why is change management a critical competency for successful AI initiatives? How can organizations go beyond early adopters to drive full-scale adoption? And what are the tools and innovations in AI that we're most grateful for this year? Special guest Andrew DeBerry, Knownwell AI Advisory Board member, shares lessons from his work with Google X's Bellwether team, which Time Magazine recently named one of 2024's best inventions. Learn how AI is helping governments manage disaster response and why listening to end users is crucial for impactful innovation. Also, it's Thanksgiving week, and the AI Knowhow team is climbing aboard the “thankfulness train” to share the AI tools that have transformed the way we work and think this year. Which tools did Courntey, David, and Mohan say were their favorites?You'll have to listen to find out! All that PLUS Courtney talks with Pete in a new segment, Searching for Competition. Pete discusses OpenAI's live search engine in ChatGPT and what it means for businesses leveraging real-time information. Watch this episode on YouTube: https://youtu.be/0mDFVprFbyU Explore Knownwell's AI innovations at www.knownwell.com/demo
Are you skeptical about integrating AI into your toy business?In this episode of Making It In The Toy Industry, host Azhelle Wade, also known as The Toy Coach, shares her AI expertise from this year's People of Play Innovation Conference and ChiTAG - Toy and Game Fair in Chicago, where she presented her talk on 'How AI is Making Toy Innovation and Pitching Easier Than Ever Before.' You'll see firsthand how AI can significantly 10x your toy development process with a custom GPT solution. Azhelle talked about identifying bottlenecks, researching AI tools, and planning, testing, and training your team to implement AI effectively. Take advantage of learning the five-step process to integrate AI seamlessly while preventing the pitfalls. Watch the full episode to understand how to employ AI from idea generation to creating compelling visuals and pitches that can streamline and potentially level up your toy business. Listen For These Important MomentsOverview of AI-Enhanced Workflows – [00:03:13]Integrating AI Without Overload – [00:06:53]Using AI to Refine Business Bottlenecks – [00:08:57]Custom GPT for Idea Refinement – [00:12:37]MakeItToyetic Custom GPT Demo – [00:13:52]Testing AI's Effectiveness – [00:16:20]Enhanced Workflow with Cast Magic – [00:21:21]Addressing AI Concerns and Limitations – [00:25:41]Generating Toy Ideas Using ChatGPT – [00:29:34]Implementing AI in Teams and Processes – [00:33:29]Send The Toy Coach Fan Mail!Support the showPopular Masterclass! How To Make & Sell Your Toy IdeasYour Low-Stress, Start-To-Finish Playful Product Launch In 5 Steps >> https://learn.thetoycoach.com/masterclass
In this sponsored episode of the Identity at the Center podcast brought to you by Strivacity, Jeff and Jim welcome Stephen Cox, co-founder and CTO of Strivacity, to discuss the evolving landscape of identity management. The conversation covers Strivacity's unique approach to customer identity and access management (CIAM), the importance of isolation by design for security, and the integration of generative AI into their platform. Stephen shares insights on how Strivacity differentiates itself in the market, the recognition from Gartner, and the challenges of implementing AI in identity management systems. They discuss the evolving landscape of AI, particularly in relation to data access, security, and identity management. Also explored is the balance between leveraging AI for business insights and the potential threats it poses to data security. The discussion also touches on the future of AI technology, the challenges of governance in a rapidly changing environment, and an unexpected segue into astrophotography, highlighting the intersection of AI technology and personal interests. Chapters 00:00 Introduction to the Identity at the Center Podcast 01:37 Meet Steven Cox from Strivacity 02:34 Strivacity's Unique Approach to CIAM 09:27 Differentiating Consumer and Customer IAM 11:49 Strivacity's Recognition and Achievements 14:05 The Importance of Isolation by Design 15:38 Generative AI in IAM Products 21:45 Implementing AI in Strivacity's Platform 29:25 Addressing AI Hallucinations and Security Concerns 30:56 Cost Implications of AI Systems 31:50 Leveraging AI for Business Insights 34:03 Implementing AI with Security in Mind 38:53 Future of AI in Identity Space 44:48 Astrophotography Adventures 53:52 Conclusion and Final Thoughts Connect with Stephen: https://www.linkedin.com/in/stephencox/ Learn more about Strivacity: https://strivacity.ai Connect with us on LinkedIn: Jim McDonald: https://www.linkedin.com/in/jimmcdonaldpmp/ Jeff Steadman: https://www.linkedin.com/in/jeffsteadman/ Visit the show on the web at idacpodcast.com and watch at https://www.youtube.com/@idacpodcast Keywords Identity Management, Customer IAM, Strivacity, AI Integration, Cybersecurity, Digital Identity, Gartner Recognition, Isolation by Design, Generative AI, User Experience, AI, data security, identity management, astrophotography, technology governance
Darren Saul is a Serial Podcaster, Strategist, Trainer, Coach, Keynote Speaker and Student of Human Attention. ---Help Support the show through my Business Partners : Upgrade Your Brain Unleash & Use Your Uniqueness https://braingym.fitness/ --------------------------Awakening Podcast Social Media / Coaching My Other Podcasts https://roycoughlan.com/ Health & Wellness Products https://partnerco.world/ My Website https://partner.co/?custid=N6543249 ------------------About my Guest Darren Saul: Darren Saul is a Serial Podcaster, Strategist, Trainer, Coach, Keynote Speaker and Student of Human Attention. He started heavily utilising the Power of Podcasting to build his photography business and was so amazed with the results he never looked back! He is now a Podcast Junkie who consults with organisations to help them get serious business results integrating Podcasting into their marketing strategy. A PODCAST IS NOT JUST A “NICE TO HAVE” ANYMORE - IT IS A "MUST HAVE"! Darren loves people and loves to share the insights, stories and knowledge he has gained over the years. He is very passionate about helping others develop, get results and feel fulfilled as marketers and entrepreneurs! What we Discussed: - Why we prefer the older Movies - Who is Darren Saul and why Podcasting (2 mins) - How does he manage his time (4 mins) - Should you do a pre call for your podcast guest interviews ( 6 mins) - Unexpected costs when podcasting (9:30 mins) - Implementing Ai in your Podcsat (11:30 mins) - Where we host our Podcasts (15:30 mins) - Having your Podcast translated into different languages (21:30 mins) - Video Channels to promote (23 mins) - Don't get too upset with the Metrics (25 mins) - Can a Blog help you get Clients (26 mins) - Does a low entry point course lead to further sales (28:30 mins) - Why you Should do your own Show (32 mins) - The Social media Mindfield (34:45 mins) - Using Social Media Platforms (36 mins) - Repurposing the content (38 mins) - Puting a section at the start of the show ( 39 mins) How to Contact Darren Saul: https://suspendedanimation.com.au/ https://www.instagram.com/suspendedanimationnn/ https://www.facebook.com/SuspendedAnimationPodcasting https://www.youtube.com/channel/UCvqogVAOcxF-7_-BfSybedw?view_as=subscriber https://www.linkedin.com/in/suspendedanimation/------------------------------More about the Awakening Podcast:All Episodes can be found at www.awakeningpodcast.org Help Support the show through my Business Partners : Upgrade Your Brain Unleash & Use Your Uniqueness https://braingym.fitness/ --------------------------Speaking Podcast Social Media / Coaching My Other Podcasts https://roycoughlan.com/ Health & Wellness Products https://partnerco.world/ My Website https://partner.co/?custid=N6543249 Our Facebook Group can be found at https://www.facebook.com/speakingpodcast
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