The AI with Maribel Lopez (AI with ML)

Guest ProfileLiz Centoni brings over 25 years of experience at Cisco where she currently leads a team of 20,000+ people dedicated to helping customers maximize the value of their technology investments. She also serves on the boards of Mercedes-Benz and Workday.Episode HighlightsCisco's Unique Position in the AI LandscapeLiz outlines Cisco's three-pillar approach to AI:Investment in back-end AI networks with hyperscalersEnterprise deployment of secure AI use casesMeeting increased capacity requirements for both private and public front-end cloud networksRecent partnership with NVIDIA to accelerate AI adoption and simplify building AI-ready data centersTransforming Customer ExperienceVision for customer experience: personalized, proactive, and predictiveGoal: Make every customer "feel like they are our only customer"Leveraging data across tech stacks to break down silos and deliver proactive experiencesUsing AI to reduce cognitive load and workplace friction for employeesAI Renewals Agent: A Case Study in Predictive AIJointly developed with Mistral AI and announced in February 2025Consolidates data from 50+ signals and sources (both structured and unstructured)Provides real-time sentiment analysis by incorporating customer support dataExpected to reduce time spent on renewal proposals from 40% to less than 5%The Future of Agentic AIMoving from AI as a tool to AI as a teammateCurrent focus on assisting and augmenting tasks, not replacing rolesHuman oversight remains critical for complex customer networksEvolution from reactive to proactive customer careImpact on Jobs and WorkExpectation that everyone needs baseline AI skillsHistorical pattern of rebalancing versus complete replacementFocus on using AI to eliminate busy work and reduce cognitive loadImportance of emotional intelligence and empathy in areas where AI still falls shortClosing ThoughtsLiz's definition of success: "Customers walk up and say, 'You really know me better than I know myself'... and they feel they can't live without three things: Cisco's security, Cisco's networking portfolio, and Cisco services."

SummaryIn this conversation, Maribel Lopez and Jeetu Patel discuss the transformative potential of AI in business, the challenges organizations face in adopting AI, and the importance of security in AI applications. They explore the need for visibility, validation, and guardrails in securing AI, the rise of specialized AI models, and the future of AI agents in automating workflows. Patel emphasizes Cisco's commitment to innovation and the urgency for companies to embrace AI to remain relevant in a rapidly evolving landscape.TakeawaysAI is transforming business strategies across industries.CEOs are optimistic about AI but feel unprepared.Security practitioners face significant staffing shortages.AI can both complicate and simplify security challenges.Organizations must secure AI models and use AI for defense.Visibility, validation, and guardrails are essential for AI security.Specialized AI models can be more effective and cost-efficient.AI agents will enhance productivity and workflow automation.Cisco is innovating rapidly and operating like a startup.Companies must embrace AI to thrive in the future.Chapters00:00The Exciting Intersection of AI and Business02:47Challenges in AI Adoption and Security06:34Securing AI: Visibility, Validation, and Guardrails12:47The Rise of Specialized AI Models18:00The Future of AI Agents and Automation25:31Cisco's Transformation and Innovation31:10Embracing AI: A Call to ActionFollow us at: Jeetu Patel  https://www.linkedin.com/in/jeetupatel/Maribel Lopez https://www.linkedin.com/in/maribellopez/

In this episode, Maribel speaks with  Shub Bhowmick, the CEO and Co-founder of Tredence on how its using AI internally and externally. Bhowmick also provides advice on what's important for enterprise buyers looking to leverage AI. TakeawaysThe shift from proof of concept to proof of value is crucial for businesses.AI is enabling organizations to achieve more with fewer resources.Agentic solutions are becoming increasingly relevant in various industries.Internal innovations at Treatance are focused on developing interconnected AI agents.Organizations must prepare for a future where they need to do more with less.Crawl, walk, and run is a practical approach to AI implementation.Creating a robust monitoring and operations foundation is essential.Small language models can be more effective and cost-efficient than larger models.AI can significantly enhance productivity and creativity in the workplace.Health and personal well-being are important considerations in a fast-paced professional environment.Sound Bites"Proof of value is the new proof of concept.""AI is enabling you to do more with less.""Agents are like smart interns, very analytical.""The speed of AI is moving much faster.""AI can 10x your productivity.""Crawl, walk, and run with AI implementation.""Small language models are the new thing."Chapters00:00Introduction to Treatance and AI Trends07:28Emerging Use Cases in AI11:46Real-World Applications of AI in Business18:33Internal Innovations at Treatance30:33Advice for Organizations on AI Implementation

SummaryIn this conversation, Maribel Lopez speaks with Markus Nispel about the integration of AI in networking solutions, particularly at Extreme Networks. They discuss the evolution of AI capabilities, the importance of data governance, and the role of AI in enhancing operational efficiency and security. Markus emphasizes the need for trust in AI systems and the potential of agentic AI to transform networking operations. The discussion also touches on the challenges of skill development and the future of AI in the industry. Extreme Networks, trusted by tens of thousands of customers globally, delivers AI-native cloud networking solutions that seamlessly connect people, applications, data, and devices.Info on Extreme Networks Platform One: https://www.extremenetworks.com/platform-one and an explainer video https://vimeo.com/1036922077/58472f1411?ts=0&share=copy. Takeaways AI has been integrated into networking solutions for measurable business value. Data quality is crucial for effective AI implementation. Generative AI can significantly reduce the time for knowledge acquisition. Agentic AI combines various capabilities for enhanced networking solutions. Trust and transparency are essential for AI adoption in enterprises. AI can optimize security policy configurations and reduce attack surfaces.The orchestration of agents is vital for achieving automation in networking.AI's role in skill development is critical for new employees.The future of AI in networking will involve more autonomous systems. Continuous feedback loops enhance trust in AI systems. Sound Bites"AI allows for a consistent support experience.""Data governance is critical for AI systems.""The orchestration of agents is key to automation.""Trust is essential for AI adoption in enterprises.""The future is dynamic with AI advancements." Chapters 00:00 Introduction to AI in Networking03:40 Evolution of AI Integration in Networking Solutions06:54 Understanding AI's Unique Positioning in Networking10:18 AI's Role in Skill Development and Knowledge Acquisition13:02 Defining Agentic AI and Its Current Capabilities16:54 The Importance of Orchestration in AI Systems19:45 Addressing Trust and Resistance in AI Adoption23:19 Demonstrating ROI from AI Implementations25:29 Future of AI: The Rise of Agentic Systems 

In the category of better late than never, we found the missing recording file with Vijay. Enjoy!Show Notes:In this episode of "AI with Maribel Lopez," host Maribel Lopez sits down with Vijay Sundaram, Chief Strategy Officer at Zoho, at Zoho Day 25 in Austin, Texas. They discuss Zoho's strategic evolution and approach to AI.Key Highlights:Zoho's Market Evolution: Vijay explains how Zoho has expanded from primarily serving small and medium businesses to increasingly being adopted by larger enterprise customers worldwide. This evolution has happened naturally as their products became more sophisticated and larger customers discovered them.Enterprise Adaptation Challenges: To serve enterprise customers, Zoho had to make changes in three areas:Technology (their strength as a product-driven company)Operations (building expertise in account management, solutions consulting, etc.)Transitioning from an inbound to outbound business modelAI Implementation Strategy: Vijay clarifies that while generative AI has recently captured public attention, Zoho has been implementing various AI technologies (machine learning, NLP, video recognition) for over a decade. Much of this AI has been "headless" - working behind the scenes in applications rather than through conversational interfaces.Three Levels of AI: Zoho approaches AI implementation through:Contextual AI within business applicationsInteractive AI for specific purposesExpert-level insights that enable non-experts to gain valuable business intelligencePlatform Approach: By integrating applications and creating a comprehensive platform, Zoho can leverage data across domains (finance, sales, HR, operations) to provide more valuable AI-driven insights.AI Market Shift: Vijay predicts that AI differentiation will increasingly move from foundational models to the application layer, where companies like Zoho can add value through their access to business data across domains.Privacy and Security: Zoho maintains a strong stance on privacy (no trackers on their websites) and has built a "trust layer" into their platform to ensure proper data access controls for AI interactions.

SummaryIn this conversation, Maribel Lopez speaks with Ivana Bartoletti, the Global Privacy Chief Officer at Wipro, about the intersection of AI, privacy, and governance. They discuss the transformative impact of generative AI, the importance of embedding ethics in AI development, and the role of synthetic data in mitigating bias. Ivana also shares insights on the Audrey initiative aimed at promoting human rights in the digital age and highlights common mistakes in AI regulation. The conversation concludes with a positive outlook on the collaborative efforts to build fair and responsible AI.TakeawaysPublic trust is essential to harness AI's benefits.Generative AI is transforming how we live and work.Privacy is a crucial collective good that must be respected.Ethics in AI goes beyond compliance with laws.AI should retain human agency and decision-making.Bias in algorithms can perpetuate social inequalities.Synthetic data can help mitigate bias but has limitations.Transparency in data usage is vital for equity.AI regulation should not be seen as opposing innovation.Collaboration across sectors is key to responsible AI governance.You can follow Ivana here: https://www.linkedin.com/in/ivana-bartoletti-77b2b29/You can follow me here: https://www.linkedin.com/in/maribellopez/https://www.youtube.com/@AIwithMaribelLopezhttps://x.com/MaribelLopez

Episode Overview:Maribel Lopez speaks with Tim Marklein, CEO of Big Valley Marketing, about how AI is changing marketing and communications. The conversation explores the practical applications, limitations, and future of AI in the marketing landscape.Guest:Tim Marklein - CEO of Big Valley Marketing, an award-winning consulting firm that helps technology companies grow and win in various markets including software infrastructure, AI, cybersecurity, digital health, and supply chain.Key Topics Discussed:Current state of AI adoption in marketing: Despite surveys showing varied adoption rates, most professionals are still "dabbling" with AI rather than fully integrating it into workflowsThree key areas where AI is proving valuable:As a search alternative for market insightsFor pattern analysis and audience researchFor writing and editing assistanceThe continued importance of original thinking: AI can't replace a company's unique point of view, especially in B2B contexts where buyers want to understand a company's beliefs and perspectivesBrand differentiation concerns: Discussion about whether widespread AI adoption might lead to homogenized marketing content and brand positioningAI for audience targeting: How AI can help with audience research but cannot replace strategic decisions about which audiences to prioritizeWorkflow integration challenges: The disconnect between the ideal AI tools and those integrated into existing workflowsAI and marketing metrics: How AI primarily makes it easier to capture existing metrics rather than creating new onesAuthenticity and ethics: The research showing that simply disclosing AI use doesn't build trust when 80% of people don't trust AI to begin withAppropriate vs. responsible use: The importance of communicating who is using AI and why, not just how it's being usedSkills development for the AI era: The value of experimentation and curiosity over becoming a dedicated "prompt engineer"You can follow Tim Marklein, the Founder and CEO, Big Valley Marketing ( bigvalley.co) at LinkedIn: https://www.linkedin.com/in/tmarklein/ X: @tmarkleinYou can follow me at:https://www.linkedin.com/in/maribellopez/https://www.youtube.com/@AIwithMaribelLopezhttps://x.com/MaribelLopez

Episode SummaryIn this episode, Maribel Lopez interviews Kate Soule, Director of Technical Product Management for IBM's Granite products. They discuss IBM's third-generation AI models, their focus on efficiency and enterprise readiness, and the latest advancements including vision capabilities and reasoning features.GuestKate Soule - Director of Technical Product Management for IBM's Granite productsKey Topics & Timestamps00:04 - IntroductionMaribel introduces the show and Kate SouleBrief overview of IBM Granite as fit-for-purpose, open-source enterprise AI models00:48 - What is IBM Granite?Designed as core building blocks for enterprises building with generative AIFocus on efficiency with smaller model sizesMonthly innovation updates to keep pace with rapidly evolving field02:19 - Understanding AI ReasoningExplanation of reasoning capabilities in AI modelsHow allowing models to generate more text at inference time can improve performanceCost/benefit tradeoffs of reasoning features03:13 - Enterprise AI Model Selection CriteriaMoving beyond "one model to rule them all" thinkingImportance of fit-for-purpose modelsWhy smaller models can be customized more easilyTrust and transparency considerations05:38 - AI Governance and SafetyHow to evaluate models for governance requirementsSafety evaluations and benchmarks as table stakesSystems-based approach to safety with guardrailsIBM's Granite Guardian and protection mechanisms08:55 - Benefits of Smaller ModelsWhy size matters: cost, latency, and customization advantagesSmaller models are easier to customize and require less computing powerIBM's transparent approach to training data10:13 - Future of AI EvaluationPerformance per cost becoming the key evaluation metricThe growing importance of flexibility in model selectionHow the "efficient frontier" between cost and performance will differentiate providers12:41 - IBM's Vision ModelsIBM's pragmatic enterprise focus for multimodal capabilitiesVision understanding (image in, text out) for practical business use casesSpecialization for documents, charts, and dashboardsDelivering powerful capabilities in only 2 billion parameters15:25 - Understanding Model Size ContextEvolution from millions to billions of parametersPractical considerations of deploying different-sized modelsFinding the right cost-benefit trade-off for specific use cases

This conversation explores the transformative impact of AI on business, particularly focusing on Zoho's evolution as it aims to enhance its enterprise offerings. The speakers discuss the importance of understanding customer data, the global dynamics of AI adoption, and Zoho's unique culture that fosters innovation. They also touch on the future of enterprise software and the integration of AI, emphasizing the need for a holistic view of customer engagement.Takeaways:Massive interest in AI is changing markets and valuations.Tools are only as effective as their application in serving customers.Zoho is aggressively moving into the enterprise space with a focus on AI.Integration of data is crucial for a comprehensive customer view.The concept of customer 360 is often misunderstood.Global market dynamics affect how AI is adopted in different regions.Zoho's culture promotes innovation and responsiveness to customer needs.AI will soon be an integral part of enterprise operations.Not every enterprise is a fit for Zoho's offerings.The future of enterprise software will be driven by AI and data integration.Chapters00:00The Rise of AI and Its Impact on Business01:59Zoho's Evolution and Enterprise Focus06:10Understanding Customer Data and Integration10:08Global Perspectives on AI and Market Dynamics13:54Zoho's Unique Culture and Approach to Innovation21:56Future of Enterprise Software and AI Integration 

In this episode, Maribel Lopez of Lopez Research interviews Kevin McInturff Chief Technology Officer of Logility. We explore the transformative impact of artificial intelligence on supply chain management and the key considerations for successful implementation. Our discussion covers critical insights for business leaders and practitioners navigating the AI landscape.Key Discussion PointsThroughout our conversation, we delve into how artificial intelligence is fundamentally reshaping supply chain operations. The democratization of information through generative AI has opened new possibilities, though organizations continue to grapple with data integration challenges. We examine the critical balance between innovation and responsibility, particularly regarding ethics and data security in AI deployment.The discussion reveals how real-world applications of AI are enhancing decision-making processes across supply chain operations. We explore emerging AI technologies that are revolutionizing forecasting methods, while acknowledging the ongoing evolution of ROI measurement for AI investments. Building trust in AI systems emerges as a fundamental requirement for successful adoption.Our conversation emphasizes the importance of practical experimentation with AI solutions. Organizations must understand the interplay of different roles and technical languages in AI implementation. This approach allows companies to develop effective, tailored solutions while maintaining ethical considerations and data security.## Episode ResourcesIf you'd like to learn more about the topics discussed in this episode, follow me on social media at Youtube for the video version of this podcast and LinkedIN and X (Twitter) for AI research updates and insights.Kevin McInturff Expert Bio:Kevin McInturff, Chief Technology Officer of Logility, has 20+ years of experience in product and engineering roles. He spent his early career as an engineer on a plant floor working in industrial automation and plant information systems before moving into enterprise SaaS software. Under his leadership Logility has accelerated the pace of innovation and focused on delivering high quality product, a superior user experience and solutions that enable supply chain organizations to anticipate disruptions as opportunities to reap competitive advantages. He is passionate about understanding and meeting client needs with innovative solutions while building great engineering and product culture within his team.  Outside of his work with Logility he actively volunteers with the 501st Legion a non-profit who partners with other organizations to brighten the lives of the less fortunate and to bring awareness to positive causes on both a local and global scale. Kevin is a lifelong learner, an artist, and avid practitioner of the art of tsundoku.  He has earned a BS in Computer Science from the Georgia Institute of Technology, and a Masters of Science, Management of Technology from Georgia Tech Scheller College of Business. Kevin lives in Smyrna, Georgia with his wife and three daughters. 

Maribel Lopez of Lopez Research hosted a podcast at AWS Reinvent, discussing QuickSight with ATracy Daugherty GM, QuickSight at Amazon Web Service and Travis Muhlestein, Chief Data and Analytics Officer at GoDaddy. QuickSight, a cloud-based BI tool, enables real-time data sharing and decision-making through dashboards, pixel-perfect reports, and Q for asking data questions. In the podcast, Muhlstein shares how QuickSight has transformed GoDaddy's approach from static dashboards to real-time, interactive data exploration and analysis, enabling more agile, data-driven decision-making across the organization.Follow the guests at:Maribel Lopez https://www.linkedin.com/in/maribellopez/Travis Muhlestein, Chief Data and Analytics Officer at GoDaddy https://www.linkedin.com/in/travis-muhlestein/Tracy Daugherty GM, QuickSight at Amazon Web Services https://www.linkedin.com/in/tracy-daugherty-28a1014/

Every industry, including the quick service restaurant (QSR) market, plans to transform its business with artificial intelligence (AI). Several years ago, Wendy's embarked on its AI journey, leveraging cloud services and generative AI to enhance employee and customer experiences. The drive-thru experience presents numerous challenges for QSR restaurants due to the complexities of menu options, limited-time offers, special requests, and ambient noise. Wendy's chose to tackle the drive-thru experience with AI because 75 to 80 percent of Wendy's customers choose the drive-thru as their preferred ordering channel. The company saw a tremendous opportunity to improve the customer experience by creating a seamless ordering experience using AI automation in the drive-thru. In an interview with Lopez Research, Wendy's CIO Matt Spessard shared how its AI program had advanced over the past year and shared advice for other leaders looking to tackle AI within their business.

At Amazon Re:Invent, Maribel Lopez met with several industry analysts to discuss their perspectives on what happened at one of the industry's premier cloud computing and AI trade shows. https://reinvent.awsevents.com/  

Episode Summary: In this episode, Maribel Lopez speaks with Dell's Chief Technology Officer and Chief AI Officer John Roese about Dell's enterprise AI technologies from their development to their future. Roese explains how the initial magical thinking around artificial intelligence has shifted into a more practical approach that aims to maximize the benefits of each implementation. He also discusses the emerging trends and ideas that he is seeing in the AI space.Key Themes: Maribel and John start by delving into enterprise AI and AI markets in general. John explains the types of AI markets and how enterprise AI differs from other applications. The conversation then moves into the challenges of AI and the steps that Dell is taking to address them. Next, John and Maribel reflect on the near-universal reactive approach that companies took to AI two years ago and how parts of that approach backfired or fizzled out. While this technology could have been approached better, its widespread use has provided companies with a real world understanding of LLMs and their applications. Now, companies take a more practical approach to AI while continuing to innovate. The key innovation that Roese highlights is agentic architecture. This technology differs from previous generative AI applications because it can operate autonomously and is highly specialized. Individual “agents” can have job descriptions that they are trained for much like a human being, and they can interact with each other as a human team would. For detailed show notes, navigate the episode using the time stamps below:[1:26] Maribel introduces the guest of the episode, John Roese. Roese is the CTO and Chief AI Officer at Dell Technologies. [1:59] The AI market is not a singular market – there is a traditional market, a training market, and an enterprise market. The enterprise market is very pragmatic in its applications. [4:10] Maribel asks about the challenges businesses see in enterprise adoption. Early discussions of new AI technology treated it like magic. Now that we have real world use cases and a better understanding of the technology, Dell is able to have grounded conversations about AI applications with real impacts. [7:48] Roesch explains the challenges that Dell is facing with AI. One of the challenges was determining where to prioritize as a company. Another is the process by which you develop application ideas. Dell had this issue when bringing ideas that were not fully formed to their legal team. [11:44] No one got AI perfectly right. Almost universally, companies reacted at the technical level before looking at business priorities. Roese encourages companies to move toward a more thoughtful approach to AI technology.[13:36] Dell learned that its goal was to add in the minimum sufficient AI structure to address the maximum use cases. In Dell's case, half of their use cases were related to converting proprietary data into generative outcomes. Creating one model to handle all of these cases is the most efficient approach. [15:05] Maribel asks Roese about the trends Dell is seeing in AI. Roese points to the emergence of agentic architecture. The idea behind agentic architecture is that they are autonomously performing agents with very specialized purposes. They can be combined much like a team of human beings. Follow John Roese: https://www.linkedin.com/in/johnroese/ Learn more about Dell's AI solutions: https://www.dell.com/en-us/shop/scc/sc/artificial-intelligence Follow Maribel Lopez on X/Twitter: https://x.com/maribellopez Subscribe to Maribel Lopez on YouTube: https://www.youtube.com/c/MaribelLopezResearch Follow Maribel Lopez on LinkedIn: https://linkedin.com/in/maribellopez/ 

Episode Summary:In this episode, Maribel Lopez speaks with Google Cloud Product Manager Bobby Allen about the current benefits and future possibilities of artificial intelligence in the context of Google's AI services. They explore the flexibility of Googles services that sets them apart, the environmental impacts of LLMs in comparison with their predecessor NLMs, and how companies can take a human approach to AI to make peoples lives better. Key Themes:Maribel and Bobby begin by discussing Google's AI services. Allen explains the wide variety of AI services offered by Google, which fall into three main categories: building AI, building with AI, and using AI. Most organizations are currently interested in using AI, and they have seen tangible benefits from doing so.Bobby refers to these benefits as the “four I's”: insight, increase, improvement, and innovation. Companies that adopt AI can see increases in productivity, gain insights into large documents through AI summarization, and more. Ai also has growing applications in compliance and query creation to analyze large datasets.Last, Maribel and Bobby discuss the future of AI. Bobby points to a human-first future with a focus on the impacts of AI applications, including sustainability and marginalization. He believes that AI should solve real problems and male peoples lives better.Follow Bobby Allen: https://www.linkedin.com/in/ballen-clt/Learn more about AWS: http://aws.amazon.com/Visit Maribel Lopez's Website: https://www.lopezresearch.com/Follow Maribel Lopez on X/Twitter: https://x.com/maribellopezSubscribe to Maribel Lopez on YouTube: https://www.youtube.com/c/MaribelLopezResearchFollow Maribel Lopez on LinkedIn: https://linkedin.com/in/maribellopez/ 

Episode Summary: In this episode, Maribel Lopez speaks with Qventus co-founder and CEO Mudit Garg. Mudit explains how automation can help patients receive efficient care and hospitals maximize their performance. Learn how Qventus is helping hospital systems cut down their “excess days,” why efficiency is essential to care, and Mudit's predictions for the future of AI in healthcare. Key Themes: Maribel begins the episode by speaking with Mudit about how Qventus is changing the hospital system for the better. Mudit explains that AI can be extremely helpful for hospital coordination. There are many cases in healthcare where the patient and the hospital system are aligned in their goals, like booking a surgery for a patient, but administrative complexities make those goals difficult to accomplish. Qventus bases its system on two crucial components – behavioral science and machine learning. Machine learning is a great tool for determining patterns for coordination and scheduling, but factoring human behavior is crucial to create a model that actually works. Mudit credits the success of Qventus to the combination of these factors. Maribel and Mudit also discuss the future of artificial intelligence in hospitals. Many industries are adopting AI in a wide range of applications, but Mudit suggests that healthcare systems should focus in on perfecting technology that benefits both patients and hospitals. He also notes his interest in Ai's potential for data siloing, which would cut down administrative work.  Follow Mudit Garg on LinkedIn: https://www.linkedin.com/in/gargmudit/ Learn more about Qventus: https://qventus.com/ Visit the 3Blue1Brown YouTube Channel: https://www.youtube.com/@3blue1brown Visit Maribel Lopez's Website: https://www.lopezresearch.com/ Follow Maribel Lopez on X/Twitter: https://x.com/maribellopez Subscribe to Maribel Lopez on YouTube: https://www.youtube.com/c/MaribelLopezResearch Follow Maribel Lopez on LinkedIn: https://linkedin.com/in/maribellopez/ 

Episode Summary:In this episode, Maribel Lopez speaks with Roni Jamesmeyer about the changing role of AI in healthcare. Roni Jamesmeyer, the the Senior Healthcare Marketing Manager for Five9, has over twenty years of experience in IT sales, giving her an understanding of the complexity of healthcare delivery. She focuses on Five9's healthcare strategy to help health systems, payers, and life sciences move their contact centers to the cloud and close the gaps in patient communications. Maribel and Roni discuss technological advancements in AI, different uses of AI in healthcare, and Roni's research findings.Key Themes:Maribel and Roni open the episode by discussing the healthcare industry's past attempts to improve the patient experience and how its goals have shifted. Currently, Roni is seeing healthcare companies working toward an omnichannel experience for their customers – meaning that they can interact over many communication channels. AI is helping the industry move forward. Intelligent Virtual Agents (IVAs) improve operations in four major ways: security, patient experience, revenue generation, and reduced administrative backend work. Different companies may focus more on some of these categories than others, but all four functions are extremely important to the healthcare industry. Roni also discusses her AI research findings. She found that AI tuning is crucial to improvement, allowing models to pick up and retain information. As these models are used, they become more personalized and more intelligent and can take on more work as a result. She also found that AI agents open up phone lines, allowing previously missed calls to be answered. Visit Maribel Lopez's Website: https://www.lopezresearch.com/ Follow Maribel Lopez on X/Twitter: https://x.com/maribellopez Subscribe to Maribel Lopez on YouTube: https://www.youtube.com/c/MaribelLopezResearch Follow Maribel Lopez on LinkedIn: https://www.linkedin.com/in/maribellopez/ Learn More About Five9: https://www.five9.com/ Download AI in Healthcare: How AI Drives Value for Five9 Customers: https://www.five9.com/resources/ebook/how-ai-drives-value-healthcare-customers#:~:text=Partners-,AI%20in%20Healthcare%3A%20How%20AI%20Drives%20Value%20For%20Five9%20Healthcare,customer%20surveys%2C%20and%20analyst%20insight. Attend Roni's Webinar with Exact Sciences: https://www.five9.com/registration/2024/exact-sciences-webinar Follow Roni Jamesmeyer on LinkedIn: https://www.linkedin.com/in/roni-jamesmeyer-5733461/ 

Episode Summary:In this episode, Maribel Lopez discusses generative AI with Dr. Sherry Marcus, the Director of Generative AI Sciences at Amazon Web Services. Her insights into the artificial intelligence needs of businesses gives her a unique perspective on the future of generative AI. Learn about the concept of agents in AI, why customers are moving toward the use of multiple models, and the ways AI might evolve in the future.Key Themes:Maribel and Sherry begin their conversation by discussing Amazon Bedrock, which is Amazon's AI building service. The technology allows AWS customers to create their own AI models by offering choices of foundational models that can be customized.Next, Sherry and Maribel discuss AI agents. In AI, Agents can retrieve real-time data to assist LLMs in providing information they cannot access in their training data. They also discuss how customers are currently using artificial intelligence, and why there is a shift away from specific modes and toward using multiple models for different use cases.Dr. Sherry Marcus also explains how customers have historically used RAG (Retrieval Augmented Generation) to answer questions, and how that technology is evolving. Last, she explains why companies are using synthetic data to train their models, her predictions for the future of AI, and her favorite primer on AI.Read What Is Chat GPT Doing… and Why Does It Work? by Stephen Wolfham: https://www.amazon.com/What-ChatGPT-Doing-Does-Work/dp/1579550819 Follow Dr. Sherry Marcus: https://www.linkedin.com/in/sherry-marcus-ph-d-4a4110/ Learn more about AWS: http://aws.amazon.com/ Visit Maribel Lopez's Website: https://www.lopezresearch.com/ Follow Maribel Lopez on X/Twitter: https://x.com/maribellopez Subscribe to Maribel Lopez on YouTube: https://www.youtube.com/c/MaribelLopezResearch Follow Maribel Lopez on LinkedIn: https://linkedin.com/in/maribellopez/ 

In this episode, I interview Kevin McCartan, Senior IT Delivery Engineer at Musgrave, about how he leverages AI (Open AI's ChatGPT and Juniper Mist AI) to streamline network operations.You can find a copy of the video here. https://www.youtube.com/watch?v=g1ZoMXn6c6MCase studies hereMusgrave Stores Undergoes Transformation with AI-Native Network Enhancementshttps://www.juniper.net/us/en/the-fee...Three Steps on the AI Path to Retail Operational Zenhttps://blogs.juniper.net/en-us/ai-na...

Episode Summary: In this episode, Maribel Lopez discusses responsible AI governance with Credo AI's Head of Product Susannah Shattuck. Susannah builds AI governance tools that help organizations design, develop, and deploy ethical AI at scale. She has been working in Machine Learning Operations and AI governance for the last five years; her passion for AI governance can be traced back to her days on the IBM Watson implementations team, where she saw firsthand all of the things that can go wrong during the ML development lifecycle. Maribel and Susannah discuss the difference between responsible AI strategy and AI governance, the EU AI Act, and how she helps teams build governance plans that work for them.Key Themes: Maribel and Susannah begin their conversation by discussing the risks of generative AI. Large language models have overlapping risks with older models such as algorithmic biases, but they also come with new risks such as hallucinations, privacy risks, and security risks. Many companies want to implement AI, but those same companies recognize that they are not prepared for its risks. Susannah helps teams create AI governance plans that protect against risks without holding them back. She notes that it is not possible or practical to eliminate all risks, and that part of building a good strategy is allowing for low-risk use cases. Later in the conversation, Maribel and Susannah dive into how Credo AI works with organizations to implement responsible governance. They also discuss the EU AI Act, which will shape AI governance in the years to come. Last, Susannah shares her predictions for the future of AI implementation and AI governance. Visit Maribel Lopez's Website: https://www.lopezresearch.com/ Follow Maribel Lopez on X/Twitter: https://x.com/maribellopez Subscribe to Maribel Lopez on YouTube: https://www.youtube.com/c/MaribelLopezResearch Follow Maribel Lopez on LinkedIn: https://linkedin.com/in/maribellopez/ Follow Susannah's LinkedIn: https://www.linkedin.com/in/susannah-shattuck/ Follow Susannah's Twitter: https://x.com/shshattuck?lang=enCredo AI LinkedIn: https://www.linkedin.com/company/credo-ai/Credo AI Twitter: https://x.com/credoai?lang=en

Episode Summary:In this episode, Maribel Lopez speaks with Five9's CTO and Head of AI Jonathan Rosenberg on AI's potential in the Customer Experience (CX) and Contact Center as a Service (CcaaS) space. Currently, customers are often unsatisfied with chatbot communication services at contact centers. However, AI's increasing generative capabilities show potential for exciting future applications.  Key Themes:Maribel and Jonathan begin by discussing the current state of AI in CcaaS, and how many customers are unsatisfied with their experiences with automated calls. Contact centers have long attempted to automate aspects of the CX experience, first with DTMF and later with directed dialogue.Unlike these technologies, generative AI has seen widespread adoption. Consumer familiarity with artificial intelligence will lead to them understanding how to interact with generative AI over the phone. Jonathan and Maribel also discuss their predictions for how AI will impact jobs in at contact centers. Jonathan believes that jobs will change, but they will not disappear. Last, Jonathan defines open platforms and explains how their unique features allow for useful CX capabilities. The future of AI in CX depends on how quickly companies eliminate AI hallucinations. Once models overcome this obstacle, Jonathan predicts that AI will see wide adoption in the CX space. For detailed show notes, navigate using the time stamps below:Follow Jonathan Rosenberg on LinkedIn: https://www.linkedin.com/in/jonathanrosenberg1/Follow Jonathan Rosenberg on X/Twitter: https://x.com/jjrosenberg?lang=en Read Jonathan Rosenberg's articles in the Forbes Technology Council: https://www.forbes.com/councils/forbestechcouncil/people/jonathanrosenberg/ Read the Broken Earth series: https://www.amazon.com/Broken-Earth-Trilogy-Season-Obelisk/dp/031652719X

Episode Summary: In this episode, recorded live at the IBM Think event in Boston, Maribel Lopez moderates a panel on AI governance with key figures from IBM and AWS. The discussion revolves around the current state and future of AI governance, the challenges and opportunities it presents, and the role of innovation and regulation in shaping responsible AI adoption.Speakers: Maribel Lopez, Lopez Research Karthik Krishnan from Amazon SageMaker Heather Gentile from IBM Watsonx.GovernanceKush Varshney from IBM Research. Key themes:This  panel discussed the  necessity for organizations to manage data across hybrid multi-cloud environments while ensuring robust governance is discussed. Gentile highlighted the strategic importance of AI governance for organizations aiming to align AI adoption with their ethics, culture, and valuesThe panel discussed how companies are shifting from siloed AI projects to enterprise-wide governance frameworks driven by generative AI innovations as well as the need to closely follow changes in the regulatory landscape. Krishnan discusses the collaboration between AWS and IBM Watson to integrate governance tools with AI and ML workflows. This integration aims to simplify risk management and regulatory compliance for customers using generative AI. Collaboration between AWS and IBM is seen  Varshney shared insights on ongoing research in AI governance, particularly in addressing issues like hallucination in generative AI and developing algorithms for regulatory compliance.

This podcast was recorded as a LInkedIn Live on managing AI risk, governance, and explainability. We also talk about the EU AI Act's impact on the overarching global regulatory environment. Bio: Heather Gentile, Director of watsonx.governance Product Management, IBM Data and AI Software. (Learn more about Watson X here. https://www.ibm.com/watsonx)  Heather Gentile is Director of Product in IBM's Data and AI software division. Heather focuses on opportunities to apply AI technologies to develop innovative solutions for IBM's watsonx.governance and governance, risk and compliance portfolio. She works with organizations to enable responsible, transparent and explainable AI.   Heather has a passion for innovation and works with IBM's technology and design teams to lead user experience workshops to solve for AI governance, risk and compliance challenges. Her experience expands across financial services, regulatory agencies, and other highly regulated industries.  Prior to joining IBM, Heather was responsible for overseeing the compliance analytics division of regulatory solutions at Wolters Kluwer. She received her undergraduate degree from Bryant University in Business Administration and her MBA from the University of Massachusetts. Social LinksYou can follow Heather at: https://www.linkedin.com/in/heathergentile/You can follow Maribel  at: X/Twitter: https://twitter.com/maribellopezLinkedIn: https://www.linkedin.com/in/maribellopezYouTube: https://www.youtube.com/c/MaribelLopezResearch

In today's episode, we delve into the transformative role of artificial intelligence in modern contact centers. We had the pleasure of speaking with Carmit DiAndrea, Director of AI and Data Management at NICE, who shared her invaluable insights on integrating AI to enhance customer and agent experiences. Episode Highlights:The Evolution of AI in Contact Centers: Understand how AI has transitioned from automating basic tasks to powering sophisticated, conversational interactions.Special purpose AI vs.  General AI: A discussion on how organizations need AI that's   purpose-built  for CXGenerative AI vs. Traditional AI: Discover the differences between these two AI types and their unique roles in improving customer experiences and operational efficiency.AI's Impact on the Workforce: Carmit DiAndrea debunks common misconceptions about AI, highlighting new career opportunities emerging within the industry.Social LinksYou can follow Carmit at: https://www.linkedin.com/in/carmitd/You can follow Maribel  at: X/Twitter: https://twitter.com/maribellopezLinkedIn: https://www.linkedin.com/in/maribellopezYouTube: https://www.youtube.com/c/MaribelLopezResearch

In this episode, we dive deep into the world of Edge AI with a focus on the embedded edge market, featuring insights from Krishna Rangasayee, the founder and CEO of SiMa.ai. In this podcast we discuss the need to scale AI and ML technologies in the physical industrial realm, understanding what purpose-built AI looks like for the embedded edge market. We also talk about the potential of large multimodal models (LMM) in shaping the future of AI on the edge. Learn how these models promise enhanced accuracy and efficiency, along with reduced costs and power consumption. The episode wraps up with recommendations for further learning, including the book "Good to Great," which offers valuable insights into scaling and navigating the technology industry.BioKrishna Rangasayee is Founder and CEO of SiMa.ai. Previously, Krishna was COO of Groq and at Xilinx for 18 years, where he held multiple senior leadership roles including Senior Vice President and GM of the overall business, and Executive Vice President of global sales. While at Xilinx, Krishna grew the business to $2.5B in revenue at 70% gross margin while creating the foundation for 10+ quarters of sustained sequential growth and market share expansion. Prior to Xilinx, he held various engineering and business roles at Altera Corporation and Cypress Semiconductor. He holds 25+ international patents and has served on the board of directors of public and private companies.Social LinksYou can follow Krishna  at: https://www.linkedin.com/in/krishnarangasayee/You can follow Maribel  at: X/Twitter: https://twitter.com/maribellopezLinkedIn: https://www.linkedin.com/in/maribellopezYouTube: https://www.youtube.com/c/MaribelLopezResearch

AI has the potential to revolutionize healthcare in areas that range from drug discover to the patient experience. In this podcast, Heather Lane from athenahealth shares the challenges and opportunities of using AI to improve the patient and clinician experience.Heather's Bio:Heather has a  PhD  from Purdue, where she focused on developing machine learning methods for the computer security problem of anomaly detection. She's worked at the   MIT AI Lab (now CSAIL) working with Leslie Kaelbling on reinforcement learning and decision-theoretic planning, Markov decision processes, and the tradeoff between stochastic and deterministic planning.In 2002, she moved to the University of New Mexico as an assistant professor in the Department of Computer Science. There she worked on a number of application areas of ML, including the bioinformatics of RNA interference, genomics, and computational neuroscience (inference of brain activity networks from neuroimaging data). Much of that work involved Bayesian networks and dynamic belief networks.In 2008, she was promoted to associate professor at UNM and was granted tenure. In 2012, she moved from academia to industry, joining Google in Cambridge, MA. working  on Knowledge Graph, Google Books, Project Sunroof, and Ads Latency.In 2017, she joined athenahealth to  lead a Data Science team working to use athena's immense store of healthcare data to improve healthcare experiences for clinicians and patients.Social LinksYou can follow Heather at: https://www.linkedin.com/in/terranlane/You can follow Maribel  at: X/Twitter: https://twitter.com/maribellopezLinkedIn: https://www.linkedin.com/in/maribellopezYouTube: https://www.youtube.com/c/MaribelLopezResearchHashtags: #AI, #Healthcare #PatientExperience

In this podcast we discuss how leading business create an AI mindset and how to overcome technical AI challenges. About Arun Kumar:Arun Kumar, EVP, Data & Insights at Hero Digital With over a decade of experience delivering analytical customer experience solutions, Arun believes organizations need to combine technology at scale with the power of human insight and empathy to develop meaningful, relevant, and experience-based relationships with constituents. He has led teams for some of the top agencies in the world including Wunderman Thompson, and Publicis Sapient. Arun has helped build multi-channel touchpoints and direct-to-consumer strategies for brands like The American Red Cross, Bose, Carnival, Newell Brands, and TD Bank.Social Links:LinkedIn: https://www.linkedin.com/in/kumararun/Hero Digital author page: https://herodigital.com/insights/author/arunkumar/You can follow Maribel  at: X/Twitter: https://twitter.com/maribellopezLinkedIn: https://www.linkedin.com/in/maribellopezYouTube: https://www.youtube.com/c/MaribelLopezResearchHashtags: #AI, #BusinessStrategy #AIEthics #AIGovernanceHere is a link to the Hero Digital AI Readiness report: https://herodigital.com/insights/ai-readiness-report/

In this bonus podcast episode, I interviewed Juniper Networks' Chief AI Officer, Bob Friday,  to discuss changes in AI and how AI impacts the networking industry.   Mr. Friday also defines AIOps and what it means to deliver what Juniper Networks calls an AI-native platform.   Bob Friday's Bio: Bob Friday, Chief AI Officer and CTO, Juniper NetworksBob is the co-founder of Mist Systems and currently serves as the Chief AI Officer at Juniper Networks and CTO of Juniper's enterprise business following Juniper's acquisition of Mist. Bob started his career in wireless at Metricom (Ricochet wireless network) developing and deploying wireless mesh networks across the country to connect the first generation of Internet browsers. After Metricom, Bob co-founded Airespace, a start-up focused on helping enterprises manage the flood of employees bringing unlicensed Wi-Fi technology into their businesses. After Cisco's acquisition of Airespace in 2005, Bob became the VP/CTO of Cisco enterprise mobility and drove mobility strategy / investments in the wireless business (e.g. Navini, Cognio, ThinkSmart, Phunware, Wilocity, Meraki) and product / industry innovation (e.g. CMX, Cleanair, HS2.0 / Passpoint, indoor location). He holds more than 15 patents.Social LinksYou can follow Bob at: https://www.linkedin.com/in/bobfriday/You can follow Maribel  at: X/Twitter: https://twitter.com/maribellopezLinkedIn: https://www.linkedin.com/in/maribellopezYouTube: https://www.youtube.com/c/MaribelLopezResearchJuniper Social Links:X/Twitter: https://twitter.com/JuniperNetworksLinkedIn: https://www.linkedin.com/company/juniper-networks/Facebook: https://www.facebook.com/JuniperNetworksHashtags: #JuniperNetworks #AI, #AIOps, #datacenter

Amazon Web Services held its annual cloud computing conference in Las Vegas at the end of November. In this podcast, Maribel Lopez recaps some of the key artificial intelligence announcements from her attendance at the event. There were key product launches that span AI chips, models and services. There is also a video recording of the podcast from the show floor that can be found on her YouTube channel at www.youtube.com/@MaribelLopezResearchYou can follow Maribel on LinkedIn at https://www.linkedin.com/in/maribellopez/And on X at https://twitter.com/MaribelLopez@awscloud #reinvent #GenAI #cloudcomputing

It's the year of generative AI and every technology category changed as a result of access to new foundation models. In this podcast, I speak with Elastics's CPO Ken Exner about how enterprise search analytics and other categories, such as how security and observability are evolving.About Ken ExnerChief Product Officer, Elastic"Helping customers gain actionable insights from data is increasingly important in a world of ever-increasing volumes of data. At Elastic, I have the privilege of leading our cross-functional product teams. Nothing is more exciting than seeing engineering, product, and design teams working in rhythm to deliver great experiences for our customers. I am passionate about building customer-oriented solutions that balance flexibility and ease of use, and I don't believe customers should have to compromise for either."Exner  joined Elastic after three decades in various technology companies leading product and engineering teams. Most recently, he spent 16 years at Amazon Web Services (AWS), where he built and managed dozens of products used by millions of customers worldwide.He holds a bachelor of science degree from the Haas School of Business at the University of California, Berkeley. He and his family live on the outskirts of Seattle, where they spend time with their pets, which include dogs, cats, chickens, goats, and alpacas. Follow Ken at https://www.linkedin.com/in/ken-exner-b914542/ Follow Maribel at https://www.linkedin.com/in/maribellopez/About Elastic Elastic is a leading platform for search-powered solutions. Elastic understands it's the answers, not just the data. The Elasticsearch platform enables anyone to find the answers they need in real-time using all their data, at scale. Elastic delivers complete, cloud-based, AI-powered solutions for enterprise security, observability and search built on the Elasticsearch platform, the development platform used by thousands of companies, such as well-known brands Uber, Slack, Microsoft, and more than 50% of the Fortune 500.Elastic is a platform for search-powered solutions that helps everyone — organizations, their employees, and their customers — find what they need faster, while keeping applications running smoothly, and protecting against cyber threats.The company offers three main product categories that include Elastic Enterprise Search, Observability, and Security solutions. Some of its customers include well known brands such as Uber, Slack, Microsoft, and thousands of others who rely on us to accelerate results that matter.Follow Elastic at https://www.elastic.co/

In this episode, we take on questions such as how do hallucinations in AI impact the CX space? Are developers still necessary in the age of AI and what advice Verint would offer to companies investigating AI for their customer experience projects.Jaime Meritt serves as Verint's Chief Product Officer. Jaime joined Verint in 2015 and is a key player in defining the company's product and technology strategy, and a driving force for cloud and AI initiatives.You can follow Jaime's on LinkedIn at: https://www.linkedin.com/in/jaime-meritt-90aa19/You can follow Maribel  at: http://twitter.com/MaribelLopez and https://www.linkedin.com/in/maribellopez/

Everyone talks about AI in the cloud. However to achieve the full business benefits of Artificial Intelligence,  companies need to create a foundational software and hardware infrastructure that can support AI at the device level, edge and cloud. In this podcast, I speak with Intel's Sachin Katti about changes in the market to support AI anywhere and everywhere. Bio: Sachin Katti is senior vice president and general manager of the Network and Edge Group (NEX) at Intel Corporation. He is responsible for driving technology and product leadership throughout the network to the intelligent edge.Katti previously served as vice president and chief technology officer for NEX, a role responsible for technical strategy and vision across the group.Prior to joining Intel in 2021, he served as the vice president of Telco & Edge Strategy at VMware, where he defined both the product and technology vision to capitalize on the cloudification of the network and edge.Katti is a professor of electrical engineering and computer science at Stanford University. He is also the co-chair of the Technical Steering Committee for the O-RAN Alliance and was founding director of the xRAN Foundation before its merger with the O-RAN Alliance. Katti is co-founder and former CEO of Uhana (now part of VMware), which built a network AI platform to monitor and optimize mobile networks and applications. He previously co-founded Kumu Networks, which commercializes breakthrough research from his lab on full duplex radios.Katti received his doctorate in electrical engineering/computer science from MIT in 2009.

In this podcast, I interview Kavitha Prasad. She is Intel's VP  for Artificial Intelligence Strategy.  We started the conversation by defining the various  types of AI accelerators to deliver clarity. We move on to discuss the barriers to unlocking value from AI and  advice on how to improve AI implementations. We close the podcast with what's new and exciting in the space.Her bio.As an experienced Business and Technology leader across a wide range of system applications, system architecture, business development, and go-to-market strategies, she has delivered competitive solutions to Cloud, Enterprise and Embedded markets.Kavitha has a masterful track record of building high performance teams that consistently deliver high quality products at an aggressive cadence. As an established leader in the semiconductor industry, Kavitha's broad hardware and software proficiency enables her to deliver multiple successful products in ASICs, SOCs, FPGAs and servers across multiple process nodes.Best known for leveraging her passion for building authentic customer relationships and coupling it with her technical engineering expertise, Kavitha brings best-in-class AI and Machine Learning solutions in training and inference across edge to cloud.You can follow Kavitha here:https://www.linkedin.com/in/kavitha-prasad-2b38737/

Wendy's CIO shares his thoughts on building a next generation customer experience, and designing with cross-functional teams. Vaconi shares how  cloud computing, mobility and  AI provide the technical  foundation for delivering  on new business opportunity. Relevant Blog: Wendy's Unveils New Global Restaurant Design StandardBIO:Kevin VasconiChief Information OfficerKevin joined Wendy's as our Chief Information Officer in 2020. In this role, he is responsible for all aspects of Wendy's global technology efforts, including Consumer-facing Digital, Restaurant Technology, Enterprise Architecture and Technology, and Information Security.Prior to joining the Company, Kevin served as Executive Vice President, Chief Information Officer at Domino's Pizza, Inc. At Domino's, he served on the executive leadership team and was responsible for developing and leading all domestic and international technology capabilities. Emphasis on technology innovation helped Domino's achieve more than half of all global retail sales in 2019 from digital channels, primarily online ordering and mobile applications. He has been recognized in the Top 10 of Nation's Restaurant News' Power List for his technology and innovation leadership, overseeing the team that spearheaded digital innovations that changed the pizza landscape and have served as inspiration for the broader QSR category.Kevin has more than 30 years of technology experience across multiple industries including automotive, hardware, software and retail. His tenure prior to Domino's includes service as CIO and VP of Engineering for the Stanley Security Solutions division of Stanley Black & Decker; SVP & CIO, R.L.Polk & Co.; and Chief Technology Officer for a number of business units and platforms within the Ford Motor Company. You'll find the Son of Baconator in his favorites on the Wendy's mobile app.Kevin received his B.S. in Technology from Purdue University.

In this podcast with Accenture's Christie Smith, we discuss the organizational learnings from the company's recent book Radically Human and the  changes in required to successfully navigate the future of work.  Her bio:Christie Smith is the global lead of Talent & Organization/Human Potential at Accenture. Christie joined Accenture in 2020 to lead and expand the transformation offerings that address the complex change management challenges facing CEOs, C-suites and boards, and assumed leadership of global Talent & Organization/Human Potential in March 2021. In 2022, she became Accenture's Executive Pride Sponsor, representing and promoting LGBTIQ+ equality at the highest level of the organization. Previously, Christie was with Apple where she was the global vice president for Inclusion & Diversity (I&D), I&D business partners and I&D solutions. She managed the global expansion of the function and the team in all regions and countries where Apple had offices and retail stores. Her leadership at Apple was integral to iconic products such as Memoji, iPhone Camera and iOS software in multiple languages. In addition, at Apple, she was instrumental in the growth of female and underrepresented minorities, expansion of scalable solutions in recruiting, global pay equity and compensation, and development of leaders. Prior to her role at Apple, Christie served as interim CHRO at Grail, a start-up cancer detection company, and was a principal with Deloitte Consulting. As a national Human Capital leader at Deloitte, she was responsible for working with global clients on their talent management, organizational design, workforce planning, compensation strategies, I&D and HR technology solutions. In this role, Christie led large-scale technology implementations, change management, risk and communication strategies. She also has deep expertise in CEO consulting around global talent strategies, along with CEO succession and executive team structure, management and capability. As a strategist, she led new product offering strategies for Deloitte in the United States and global markets, including the development of customer strategy in BRIC (Brazil, Russia, India and China) and EMEA (Europe, Middle East and Africa) countries. As part of her strategic framework, she leveraged deep data analytics to drive predictive socioeconomic and political factors that would impact business and market strategies. Her leadership in business development and expansion includes being the west region managing principal of Deloitte Consulting, where she led growth in consulting, technology, human capital and strategy. She also led Deloitte's west region Life Sciences industry practice. Christie was part of the leadership team that drove expansion of Deloitte Consulting into China and greater APAC. Christie also was responsible for the founding and leadership of the Deloitte University Centers for Inclusion and Community Impact.  She is a frequently sought-after speaker on leadership, strategy, I&D, and people analytics. She has been covered by The New York Times, Wall Street Journal, Harvard Business Review, Fortune, Forbes and CNN. Christie has been recognized as a Most Influential Woman in San Francisco (2012-2015), Women to Watch from Diversity Magazine (2012), Top 50 Diversity Leader (2020) and a leader in Fast Company's Queer 50 list (2021). She is a member of the Committee of 200 (C200) and World 50 Women.Her recommendations:https://mastersofscale.com podcast Michael Gervais on Finding Mastery“Radically Human: How New Technology is Transforming Business and Shaping Our Future” by Paul R. Daugherty and H. James Wilson.” 

In this podcast we discuss the intersection of  digital identity, security and artificial intelligence.  Joe Burton, Chief Executive Officer, TelesignJoseph Burton is the CEO of Telesign. Before Telesign, he served as CEO of Plantronics (now Poly) from 2016 to 2020, after joining the company in 2011 as Chief Technical Officer and then serving as Chief Commercial Officer. He started his career in 1990 as a software engineer, was acquired into Cisco in 2001 and served as Cisco's CTO for Unified Communications until 2010. Burton specializes in digital transformation, growth acceleration, corporate and go-to-market strategies, and has extensive expertise in technology and product development. He was most recently a Senior Advisor to the management consulting company McKinsey & Company. He holds a Bachelor of Science in Computer Information Systems and completed the Stanford Executive program at Stanford University.You can follow Joe at https://www.linkedin.com/in/joe-burton/ and Maribel at https://www.linkedin.com/in/maribellopez/ and @MaribelLopez

In this podcast, I speak with Michelle Donnelly, the Chief Revenue Officer at Groq, about how advancements in AI accelerators are enabling companies to process workloads that were previously unimaginable. Michelle's bio.Michelle Donnelly, the Chief Revenue Officer at Groq,  a startup known for accelerating systems with real-time artificial intelligence and high performance computing solutions. Michelle is a results-oriented executive with 20+ years of experience leading and operating distribution and go-to-market functions in hyper-growth environments.Known to be customer-obsessed and a “growth hacker,” Michelle joined Groq from Salesforce where she led Retail and Consumer Goods sales organizations focused on cloud strategy, strategic partnerships, ecosystem development, and revenue growth. Under her leadership, her teams shaped customer demand, scaled for rapid growth, and exceeded revenue targets year-over-year.When Michelle is not working, she is hanging out in San Francisco with her husband, her teenage daughter, and her pandemic puppy. Michelle has traveled the world and is rumored to have hung out with gorillas in the Congo, trekked the Himalayan mountain ranges, and studied yoga in India. In this podcast, we talk about Groq's customer work, including the recent Army Validation Report conducted with Groq customer, Entanglement AI™, on their cybersecurity anomaly detection capability that runs on Groq hardware. Report: https://apps.dtic.mil/sti/citations/AD1180411Video: US Army Confirms 1000x Performant Cybersecurity Technology by Entanglement AI™ Run on Groq™ Hardware  https://www.youtube.com/watch?v=oQ8V8kMxGfsThe book recommendation can be found here:  Turn the Ship Around! L. David Marquet https://davidmarquet.com/turn-the-ship-around-book/You can follow Michelle at: https://www.linkedin.com/in/michelledonnelly/You can follow Maribel at :  https://www.linkedin.com/in/maribellopez/ & on Twitter @MaribelLopez

In this podcast, Sharon Mandell describes how AI helps her team at Juniper and Juniper Networks'  IT customers to deliver better experiences.  Links to information discussed in the podcast. 2022 Juniper Networks AI Report: https://juni.pr/3CyRdyuAssessing AI Security Risk: https://www.microsoft.com/security/blog/2021/12/09/best-practices-for-ai-security-risk-management/Cassie Kozyrkov's AI Lectures: https://www.youtube.com/playlist?list=PLRKtJ4IpxJpB_2ei8-5eWU31EZ6uSj9_sBill Schmarzo's Big Data MBA Series: https://www.youtube.com/playlist?list=PLaQqEd_Tx4Ep1bOIFEzDJNXI9r64rjhXLEthical Machines by Reid Blackman (Book): https://www.reidblackman.com/ethical-machines/A Beginner Guide on Synthetic Data: https://towardsdatascience.com/synthetic-data-key-benefits-types-generation-methods-and-challenges-11b0ad304b55The Real Promise of Synthetic Data: https://news.mit.edu/2020/real-promise-synthetic-data-1016Bio.Sharon Mandell is the Senior Vice President and Chief Information Officer leading Juniper's global information technology team. In this role, she leads the ongoing enhancement of the company's IT infrastructure and applications architectures to support the growth objectives of the company. She and her team are also responsible for showcasing Juniper's use of its technologies to the world. Prior to joining Juniper in 2020, Mandell was the Chief Information Officer for TIBCO Software and previously developed her leadership strategy at Harmonic, Black Arrow (now Cadent), Knight Ridder and the Tribune Company. Throughout her career, Mandell developed a level of expertise in cyber security and compliance, enterprise architecture and road mapping, data and analytics, digital transformation and customer service. She is passionate about supporting women in STEM careers and in her free time Mandell serves on various arts and education related boards. She also proudly serves on the computer science advisory board at Temple University. Mandell holds a bachelor's degree in computer science from Temple University and an MBA from the University of Chicago Booth School of Business.https://www.linkedin.com/in/sharon-mandell-juniper/ @sharonomink

Peter Scott (AI leader and author of Artificial Intelligence and You) is an expert on all things AI, Peter Scott is on a mission to help us to get along with artificial intelligence. He has given TEDx talks, spoken to audiences as diverse as transformational leaders, executives, and British parliamentarians, and created a program to train coaches in helping clients become resilient to exponential disruption. A Master's degree in computer science from Cambridge University led him to spend more than thirty years working for NASA's Jet Propulsion Laboratory, helping advance our exploration of space. A parallel pursuit of the human development field as a certified coach positioned him to recognize and address technological disruption. The births of his children brought him into a mission, to help people understand, use, and advance AI for the betterment of all.In 2020, Scott started the Artificial Intelligence and You Podcast, bringing together expert guests as diverse as politicians, CEOs, philosophers, developers, and artists to help audiences understand this incredibly complex thing called AI. He has recorded over 100 episodes and generated an audience of more than 1,000 listeners. Scott is also the founder of Next Wave Institute, an international educational organization teaching how to understand and leverage AI to thrive through technological disruption.

Tracy Pizzo Frey is the Founding Partner, Uncommon Impact Ventures. Founder, Restorative AI. She was a one time dancer, teacher, forest explorer, Googler and is currently a mom. Uncommon Impact Ventures invests in technology solutions led by founders who share our values to create products, equity, and profits with integrity. To support them, it created a proprietary model of startup development that combines the best of VCs, incubators, and accelerators. Its  holistic playbook de-risks a new venture to create a higher win ratio by providing companies with capital, infrastructure, and connectivity.You can learn more about and follow Tracy at https://www.linkedin.com/in/tracy-frey/ and https://tracypfrey.medium.com

Alex Hagerup, the CEO of Vic.ai, shares the difference between using AI for  automation versus autonomy in accounting. About Alex:Alexander is a serial tech entrepreneur with a strong passion for artificial intelligence. Prior to launching Vic.ai, he founded two other technology companies; his last one was funded by Northzone Ventures and later acquired by NASDAQ-listed J2 Global Inc., in 2014. He has a finance and accounting background and is a former board member of 24SevenOffice.com, the largest cloud accounting & ERP system in the Nordic region.Where you can find him:  https://www.linkedin.com/in/alexanderhagerup/https://www.linkedin.com/company/vic.ai/https://twitter.com/VicDotAiYou can follow me at:  http://twitter.com/MaribelLopez https://www.linkedin.com/in/maribellopez/  and http://www.lopezresearch.comYou can  subscribe to the podcast on your favorite channel and the newsletter by visiting https://aiwithml.com

There are numerous challenges to working with distributed data. How do we secure, analyze and govern data in a hybrid cloud world? In this podcast, Michael Factor from IBM Research describes what a hybrid data fabric is and how it helps companies gain value from data in distributed locations. Michael Factor's bio. Dr Factor is an IBM Fellow with a focus on cloud data, storage and systems.   He has a B.Sc., Valedictorian (1984) in Computer Science from Union College, Schenectady, NY. M.Sc. (1988), M.Phil. (1989) and Ph.D. (1990) in Computer Science from Yale University. Since graduating, Dr. Factor has worked at the IBM Research -- Haifa.His current main focus area is hybyrd cloud data.  Among his responsiblities is as a global lead for all work on Hybrid Data form IBM Research.  In this role, he and the global team are defining future directions to ensure 1) it is easy to get the right data for a task, 2) that data is always used in a secure and governed fashion and 3) that IBM has high-performance, secure, highly-functional and cost efficient data stores and processing engines.  In addition, he serves as the main focal point in moving IBM Research innovations from the Lab into the IBM public cloud where his team has contributed to services such as IBM Cloud Object Storage, IBM SQL Query Service, and various Spark related services.  Beyond his Research efforts, he also works closely with both the IBM Public Cloud and the IBM Data and AI team to provide guidance and expertise on directions such as serverless computation, data lakes and future enhancements to object storage.You can follow Michael's research here.   You can follow me on Twitter @MaribelLopez and on LinkedIn here. 

Machine Learning Operations (MLOps or ML Ops) is a set of practices that aims to deploy and maintain machine learning models in production reliably and efficiently, as defined in various publications.  In this podcast we take on the topic of  MLOPs. What is it and is it like DevOps for AI?  Turns out it's broader than you might think including everything monitoring to governance and explainability.  Adewumni shares why it's both necessary and exciting. For her 30 second recommendation, Ade shared the Cloudera Fast Forward Labs blog which can be found here. She also mentioned a report by the Algorithmic Justice League on bug bounties for algorithmic harms which can be found here. You can follow Ade on Twitter  @Adewunmi  and  @FastForwardLabs . You can also find her on Medium medium.com/@adeadewunmi and LinkedIn here. You can follow me on Twitter @MaribelLopez and on LinkedIn here. 

In this podcast, Merve Unuvar, the  Director of AI Platforms and Automation team in IBM Research AI, talks  about automation trends including AI-enabled low code automation, API management, and how to deal with unstructured data. About MerveMerve Unuvar is leading the global research strategy for Business and IT Automation, partnered with the IBM Hybrid Cloud Automation business with a focus on bringing AI infusion across IBM's Cloud Paks for automation, and integration. Her team consists of research and data scientists, engineers and designers building platforms, tools and programming models that enable data scientists and developers to create and operate AI models and applications faster and better. Merve's team is developing cutting edge technology in the intersection of core AI, distributed systems, cloud computing, human computer interaction and visualization. You can follow her at: https://www.linkedin.com/in/merveunuvar/ & https://researcher.watson.ibm.com/researcher/view.php?person=us-munuvarYou can follow me at:  http://twitter.com/MaribelLopez https://www.linkedin.com/in/maribellopez/  and http://www.lopezresearch.comYou can  subscribe to the podcast on your favorite channel and the newsletter by visiting https://aiwithml.com

Machine learning and cybersecurity are tied at the hip. In this podcast, Chris Pedigo, the Go-to-market CTO for Lacework, discusses key trends, common misconceptions and advice for navigating a rapidly evolving security market. You can follow Chris at https://www.linkedin.com/in/chrispedigo/ You can follow Maribel at http://twitter.com/MaribelLopez and https://www.linkedin.com/in/maribellopez/You can  subscribe to the podcast on your favorite channel and the newsletter by visiting https://aiwithml.comAbout LaceworkLacework is a  security company for the cloud. The Lacework Polygraph® Data Platform automates cloud security at scale. It  collects, analyzes, and correlates data across an organization's AWS, Microsoft Azure, Google Cloud, and Kubernetes environments, and narrow it down to the handful of security events that matter. It was founded in 2015 and is headquartered in San Jose, California. Learn more  at www.lacework.com.

Natural Language Processing in AI isn't a new field, but it's  advanced rapidly since 2019. Are we at the human-level of understanding  with NLP and what can be done today? Models trained on generic data sets often fail to retrieve the right information for businesses. Today, technology companies are developing solutions that allow enterprises to extract meaningful insights from textual data.  In this podcast Shila Ofek-Kiofman, the Director of Language Technologies for IBM Research AI, shares what's happening in NLP research and how it will help companies create better models using business-specific terms.  You can follow Shila at https://www.linkedin.com/in/shila-ofek-koifman-1660701/   

How can computer vision and machine learning change retail? In this podcast, I interview Richard Schwartz of Pensa Systems. The company offers an automated retail shelf intelligence solution that uses patented computer vision and artificial intelligence to scan all products and categories within a  store. In this podcast, we talked about how AI can help retailers with instantaneous access to actual shelf inventory conditions, enabling them to improve sales, optimize labor and deliver better shopping experiences.

In this podcast, I speak with Afsana Akhter about how Amelia Virtual care uses newer technology such as augmented reality, virtual reality and artificial intelligence  to help individuals overcome fears from their homes and at professional facilities. Her bio Afsana Akhter, CEO of Amelia Virtual CareWith 20+ years of experience across Tech and Digital Health, Afsana Akhter is driving the expansion and adoption of Amelia Virtual Care's VR platform for mental healthcare. Afsana has held commercial leadership roles at Livongo, Prealize Health, and Medullan. Afsana holds BS and MEng degrees in E.E.C.S. from MIT. You can follow her at:  https://www.linkedin.com/in/afsana-akhter/ & @AfsanaNow You can follow me on Twitter @MaribelLopez & LinkedIN https://www.linkedin.com/in/maribellopez/

AI Automation is a hot topic in enterprise IT circles but getting it right requires more than a set of Robotic Process Automation tools. In this podcast, I speak with Anisha Biggers from NTT DATA Services on the how and why of automation.  We discuss topics such as return on value versus return on investment. Where to find us:You can follow me on Twitter at http://twitter.com/MaribelLopez and LinkedIN at https://www.linkedin.com/in/maribellopez/You can follow Anisha at  https://www.linkedin.com/in/anishapbiggers/