Podcasts about ai strategy

 The push for hyperscale AI data centers in every county isn't about innovation — it's about centralized control, land grabs, and the surveillance state. China just beat the U.S. tech giants for a fraction of the cost. I'm joined by computer scientist and AI expert Jim Calhoun to expose the massive grift behind America's generative AI strategy. While U.S. tech giants like OpenAI, Microsoft, and Amazon take on trillions in debt to build massive, power-draining data centers, China just released a decentralized, open-weight AI model (Kimi-3) essentially for free. Calhoun breaks down why decentralized "edge computing" is the real future of AI and why Big Tech's current path is a dangerous misallocation of capital disguised as a "Sputnik moment." Learn more about your ad choices. Visit megaphone.fm/adchoices

Adrienne Gordon is the CEO of PriceSpace and founder of Pricing Empowered. With more than 25 years of pricing experience, she helps organizations combine pricing strategy, organizational change, and AI adoption to improve commercial performance.  In this episode, Adrienne and Mark explore what happens when pricing teams become half human and half AI. They debate whether AI can ever make pricing decisions on its own, why "humanless negotiation" may be closer than most companies realize, and how pricing leaders can use AI to strengthen—not replace—human judgment.   Why you have to check out today's podcast: Learn how to build a pricing team where humans and AI each do what they do best. See how pricing analysts, managers, and executives can use AI to make smarter decisions—not just write better prompts. Discover why AI buyers and humanless negotiations are closer than you think—and what pricing leaders should do now.   "Always offer versions. Put three things on the table so your customer chooses between you and you; not you and your competitor." – Adrienne Gordon   Topics Covered: 01:45 – AI Won't Replace Pricing Teams. It'll Redesign Them. Discover which pricing responsibilities AI can handle today—and where human judgment still matters most. 03:25 – Stop Using ChatGPT Like Google. Learn Adrienne's simple framework for turning AI into an experienced pricing partner instead of a search engine. 05:15 – The Pricing Work AI Should Already Be Doing. See how AI can clean data, uncover pricing insights, build value calculators, and automate repetitive analysis. 07:00 – How Pricing Leaders Should Use AI. Explore how managers and executives can use AI to test pricing strategies, positioning, and competitive scenarios. 09:15 – Don't Trust One AI. Make Them Debate. Why Adrienne uses multiple AI models to challenge each other's thinking and produce better recommendations. 12:05 – Building a Pricing Team That's Half Human, Half AI. Learn how to redesign pricing roles so people and AI each focus on what they do best. 15:20 – The One Decision AI Still Can't Make. Mark and Adrienne debate why accountability—not intelligence—is AI's biggest limitation. 17:00 – Humanless Negotiation Is Coming. What happens when AI buyers negotiate with AI sellers—and how it could reshape commercial pricing. 21:10 – Buying AI Isn't an AI Strategy. Why companies need a clear adoption plan before investing in more AI tools. 24:10 – The Pricing Advice That Never Gets Old. Why offering three options helps buyers compare your solutions instead of your competitors'.   Key Takeaways: "Stop using AI like Google. Give it a role, give it context, then give it a task." – Adrienne Gordon "Stay in the same thread. Keep giving it feedback. It gets smarter." – Adrienne Gordon "When in doubt, put multiple AI agents against one another and let them check each other's work." – Adrienne Gordon   People / Resources Mentioned: PriceSpace – Adrienne Gordon's pricing consultancy focused on AI adoption and commercial excellence. ChatGPT – Used throughout the discussion as an example of AI for pricing analysis and strategy. Claude – Discussed as one of Adrienne's preferred AI tools for analytics and executive presentations. Manus – AI platform Adrienne frequently uses for research and strategic intelligence. DeepSeek – Mentioned as a strong AI platform for pricing analytics. Perplexity – Mark references using it alongside ChatGPT and Claude for research. McKinsey – Referenced in discussing research predicting the growth of AI-driven negotiations.   Connect with Adrienne Gordon: Website: https://pricespace.com LinkedIn: https://www.linkedin.com/in/adrienne-gordon-0a93129/    Connect with Mark Stiving: LinkedIn: https://www.linkedin.com/in/stiving/ Email: mark@impactpricing.com  

Send us Fan MailAI strategy for nonprofit leaders is no longer a future-planning exercise. AI is already influencing fundraising decisions, staff workflows, donor research, website visibility, and how prospective supporters evaluate nonprofit organizations.Darren Richards, Founder and Director of Charity AI Partners, explains why the central AI issue is not choosing the newest tool. It is exercising sound leadership judgment.“The tools aren't the problem,” Darren tells us. “The issue is where you do and don't use it. Where are the red lines?”Darren introduces three ways nonprofits can apply AI: predict, iterate, and automate. Predictive AI can analyze donor data, identify supporters at risk of lapsing, and improve campaign segmentation. Generative AI can adapt a case for support for different funders and audiences. AI agents can assist with research, analysis, writing, and routine administrative work. But capability does not equal permission!Nonprofit leaders must establish clear guardrails around donor data, communications, staff responsibilities, approvals, and the activities that must remain human. Darren's operating principle is direct: “Governance before gadgets.”This lively conversation also examines a major change in nonprofit visibility. Donors are increasingly asking AI systems which organizations are credible, efficient, local, or trustworthy. Those systems may answer without sending the donor to the nonprofit's website!!That makes traditional SEO only part of the equation. Darren explains the growing importance of generative engine optimization and answer engine optimization, including clear question-and-answer content that helps AI systems interpret an organization accurately.The fundraising opportunity is significant. . . . . Darren shares an example of a children's hospital that used AI to increase an appeal's return from 2-to-1 to 6-to-1, raise the average gift by nearly one-third, and mail half as many people.The goal is not fundraising without people. It is removing repetitive work so fundraisers can invest more time in judgment, empathy, creativity, gratitude, and donor relationships.Key Takeaways:Establish an organization-wide AI strategy before expanding tool usage.Use predictive AI to strengthen donor segmentation, retention, and campaign efficiency.Protect donor relationships, trust-building, and sensitive conversations as human responsibilities.Review what major AI platforms currently say about your organization.Structure website content around the questions prospective donors actually ask.Treat clean data, consistent messaging, and governance as prerequisites for successful AI adoption.00:00:00 AI Is a Leadership Issue00:02:04 Darren Richards' Fundraising and AI Journey00:03:41 Why Nonprofits Need AI Guardrails00:05:51 Predict, Iterate, and Automate00:08:18 What AI Should Never Do00:09:51 Protecting Authenticity and Human Connection00:11:39 How AI Is Changing Donor Search00:13:21 SEO, GEO, and Answer Engine Optimization00:17:26 Donor Trust in an AI-Directed World00:19:19 Why Governance Must Come Before Gadgets00:20:35 Will AI Eliminate Nonprofit Jobs?00:23:57 Using AI as a Thinking and Writing Partner00:26:01 Raising More Money With Better Data00:28:19 Free AI Fundraising Resources#TheNonprofitShow #NonprofitLeadership #NonprofitAIFind us Live daily on YouTube!Find us  Live daily on LinkedIn!Find us Live daily on X: @Nonprofit_ShowOur national co-hosts and amazing guests discuss management, money and missions of nonprofits!  12:30pm ET   11:30am CT  10:30am MT  9:30am PTSend us your ideas for Show Guests or Topics: HelpDesk@AmericanNonprofitAcademy.comVisit us on the web:The Nonprofit Show

In this episode, Laura Dyrda, Vice President, Editor-in-Chief, Becker's Healthcare, discusses the resurgence of hospital mergers and acquisitions, how health systems are refining AI and technology investments, and why revenue cycle is becoming a strategic priority across healthcare organizations.

Notes:     What separates organizations that simply adopt AI from those that truly transform their business? Rob Cato, Vice President of Worldwide Business Transformation for Lenovo's Infrastructure Solutions Group (ISG) joins us for an insightful conversation on why successful AI initiatives begin with business strategy—not technology. Rob shares how business transformation is "a disciplined shift in the way that we create value," emphasizing that every AI investment should start with one critical question: What measurable business outcome are we trying to achieve? From defining ROI to moving AI from pilot projects into production, Rob explains why infrastructure, data, security, networking, cooling, and services all play essential roles in delivering lasting business impact. Highlights Include:  Why every AI strategy should begin with the desired business outcome. Why customer intimacy is the greatest competitive advantage for MSPs. Moving AI from pilot projects to production with the right infrastructure. How curiosity, empowerment, and disciplined leadership fuel business transformation. Lenovo's channel-first approach and vision for continued global growth. Bringing innovative technology into the world of sports and sports franchises.   Ready to turn managed services into your biggest growth engine? Learn how Lenovo is helping MSPs accelerate growth, deliver greater customer value, and expand their services with Lenovo 360 for MSP: https://tinyurl.com/360forMSP                 Timestamps: 6:41 Successful AI Strategy 11:20 Providing True Value 17:30 Leadership Traits 22:24 Exciting Expectations

See omnystudio.com/listener for privacy information.

In today’s episode, Ben O’Shea unpacks Albanese’s vague AI strategy. Plus, EV sales hit a level not seen since Commodore in the 1990s & a pack of dogs saves two Melbourne women from a sexual assault.See omnystudio.com/listener for privacy information.

Prime Minister Anthony Albanese has delivered a major speech outlining the government's response to artificial intelligence.So, what's their plan? 

What happens when AI makes employees more productive today but gradually weakens the expertise companies will depend on tomorrow? In this episode of Tech Talks Daily, I speak with Dr. Margaret Cunningham, VP of Security and AI Strategy and Field CISO at Darktrace, about cognitive tech debt, the growing risk that companies are gaining short-term efficiency from AI while unintentionally weakening critical thinking, technical expertise, problem-solving ability, and human judgment. Margaret brings a rare combination of experience to this conversation. With a PhD in Applied Experimental Psychology and a career spanning behavioral science, cybersecurity, privacy, human-centered security, and AI strategy, she examines technology adoption through the lens of how people actually think, learn, develop expertise, and make decisions. She explains cognitive tech debt by comparing it with the technical debt familiar to software teams. Companies can introduce technology quickly and enjoy immediate improvements in speed and output, only to discover weaknesses underneath those gains later. With AI, the debt may accumulate in people. Employees can appear highly productive while outsourcing the difficult cognitive work required to build judgment, recognize patterns, understand failures, and develop genuine expertise. We discuss emerging evidence that over-reliance on AI is already affecting professional skills. Software engineers may become less capable of diagnosing problems in code they did not create themselves. Medical professionals can lose decision-making capabilities when they become dependent on automated systems. Across knowledge work, deep reading and sustained concentration are increasingly being replaced by summarization, generation, and superficial review. Margaret describes the current period as the "bridge years," when AI systems are becoming increasingly capable but people still need to maintain the expertise required to recognize mistakes, question recommendations, recover from failures, and understand when automation should not be trusted. Companies cannot safely abandon human skills before technology can reliably perform those responsibilities without supervision. The conversation also challenges one of the most repeated promises surrounding enterprise AI adoption: that automation will remove routine work and allow employees to concentrate on higher-value activities. Margaret argues that companies have done a poor job of defining which tasks people genuinely want to give up and which skills they need to preserve. Some of the repetitive, slow, and difficult work being automated may be exactly where people develop pattern recognition, creativity, and professional judgment. This creates a serious challenge for cybersecurity teams and other high-stakes professions. If employees become reviewers of AI-generated outputs rather than practitioners developing expertise through experience, where will the next generation of senior engineers, security analysts, doctors, researchers, and technical specialists come from? Margaret explains why leaders need to understand which AI techniques are being used for different business problems rather than treating every form of artificial intelligence as interchangeable. Large language models, machine learning systems, behavioral analytics, and other technologies have different strengths and limitations. Knowing what questions to ask requires domain expertise, creating a difficult paradox for companies that may be automating away the very experience needed to govern these systems responsibly. We also examine the human consequences of AI adoption. Technical specialists who enjoy solving difficult problems can lose motivation when meaningful work is replaced by reviewing machine-generated outputs. Companies may struggle to understand who owns decisions made through collaboration between humans and AI, while younger employees could lose access to the experiences that previously helped people progress from beginners to experts. Margaret offers practical advice for business and technology leaders deciding how quickly to introduce AI across their workforce. Companies can identify the skills they need to preserve, create opportunities for employees to practice difficult cognitive work, use simulations and training to maintain expertise, ask teams which aspects of their jobs give them purpose, and resist pressure to automate every task simply because the technology exists. The message is not anti-AI. Margaret sees enormous potential for artificial intelligence in scientific research, cybersecurity, productivity, and solving difficult problems. But realizing those benefits requires a more intentional relationship between people and machines. For business leaders, CISOs, technology teams, AI practitioners, and anyone concerned about the future of human expertise, this conversation provides a practical framework for recognizing cognitive tech debt, deciding what should and should not be automated, preserving critical thinking skills, and building healthier forms of human-AI collaboration. AI can make people faster. The bigger question is whether companies can capture those productivity gains without losing the human capabilities they will need when the technology gets something wrong.

In this episode of the Crazy Wisdom Podcast, host Stewart Alsop sits down with Violeta Bulc, former European Commissioner for Transport and coordinator of the book Leadership Challenged, featuring 24 authors from around the world. They explore the dangers of transhumanism, the misuse of artificial intelligence, and how Silicon Valley has lost its authority to lead on technology ethics. Drawing from her background as a computer engineer who worked in Silicon Valley, Bulc argues for creating global AI infrastructure with democratically agreed-upon standards—similar to how the early Internet was built. The conversation covers the manipulation of public consciousness, the importance of middle-class agency in social change, and why humanity needs to reclaim ownership of its collective knowledge before private enterprises consolidate total control. Bulc's book is available for free download at ecocivilization.earth.Timestamps00:00 Stewart introduces Violeta Bulc and her book Leadership Challenged, coordinated with 24 global authors discussing humanity's chance through better leadership approaches.05:00 Violeta explains her technology background and critiques artificial intelligence naming, arguing these are powerful data-processing tools without true intelligence, emphasizing unknown ethical standards embedded in AI systems.10:00 Discussion of transhumanism as investment buzzword serving elite agendas, comparing to previous Silicon Valley bubble while emphasizing humanity's unexplored relational, spiritual and energetic dimensions beyond industrial development.15:00 Stewart discusses mainstream culture's fragmentation since 2008, Silicon Valley's dystopian vision, and personal strategies for reducing dependency on AI tools through diversification and stepping back from reliance.20:00 Violeta explains historical civilization patterns and middle class destruction, expressing hope that emerging thoughts worldwide will eventually converge to shift current power dynamics and technological obsessions.25:00 Technology as tool versus misuse, emphasizing builders' responsibility and ethical frameworks needed, comparing AI regulation needs to automotive safety standards that weren't implemented early enough.30:00 Edward Bernays discussion revealing manipulation through public relations and psychological operations, leading to modern sock puppet armies used by nation states for narrative control online.35:00 Internet described as most democratic technological tool ever built, maintained by responsible groups preserving equality and inclusion principles through decentralized infrastructure and IP address accessibility.40:00 Proposal for global AI infrastructure with agreed rules treating applications as interfaces, questioning private enterprise ownership of humanity-generated data and advocating collective management with usage fees.45:00 Technology evolution patterns from mainframes to personal computing back to centralized cloud computing, emphasizing need to prevent domination while preserving entrepreneurship and collective decision rights.50:00 Quantum physics principles applied to human connection and responsibility, discussing EU ethical committees reviewing AI projects post-approval, emphasizing caring hearts over short-term quarterly corporate thinking.55:00 Violeta shares company transformation experiences moving away from competition models toward serving genuine market needs, concluding with book availability at ecocivilization.earth for free download.Key Insights1. Violeta Bulc argues that artificial intelligence is fundamentally misnamed because there is no actual intelligence within these systems. They are powerful computational tools capable of processing massive amounts of data and identifying patterns, but they lack genuine intelligence. What concerns her most is that this technology has owners with embedded interests and unknown ethical standards, yet society increasingly wants to build everything on these applications and even allow them to make decisions for us. She emphasizes that as someone with decades of experience in high-tech engineering, including work in Silicon Valley, she understands the architecture behind these systems and believes we must recognize them as tools rather than intelligent entities.2. During her time as European Commissioner, Bulc helped write the first European strategy on artificial intelligence, which included three critical elements she was proud of. First, there must always be a red button to switch off any application or technology when it causes harm. Second, there must be a responsible person behind every app who can be held accountable for its consequences. Third, there should be an ethical committee evaluating powerful applications to understand their potential consequences. Though these principles have been somewhat diluted over time, they represent an important framework for responsible technology development that prioritizes human oversight and accountability.3. Bulc observes that throughout human history, great civilizations have risen across all continents, not just in Europe or the Americas, and most brought themselves down through decadence, self-centeredness, and arrogance before being finished off by external forces. She believes Western civilization is currently at this point, having become accustomed to obtaining resources through force and authority while constantly readjusting moral standards to serve elite interests. The industrial revolution initially improved conditions for people because industry needed workers, which led to the emergence of a powerful middle class. However, the elite recognized that the middle class was the only segment of society truly interested in change, so they systematically worked to destroy it over the past twenty to thirty years.4. The Internet represents the most progressive democratic tool ever built in human society, according to Bulc. Its fundamental architecture, based on TCP IP protocol and packet switching, was designed to be non-hierarchical, allowing any computer with an IP address to be seen on the same level as powerful global corporations. The maintenance of Internet tables remains in the hands of people with high levels of awareness and responsibility who are faithful to its initial democratic mission. She had hoped this technology would bring the world together as the closest tool humanity has invented to support equality and inclusion, and despite the problems with applications built on top of it, the underlying infrastructure still maintains these democratic principles.5. Bulc proposes creating a global AI infrastructure with globally agreed rules and standards, similar to how the Internet functions. She argues that many AI tools currently claim ownership of humanity's knowledge, wisdom, and heritage without permission, manipulating data that rightfully belongs to all of humanity. Instead of allowing private enterprises to capture this data first and then charge people to access it, she envisions putting all of humanity's data into a commonly managed infrastructure with clear rules about who can use it, under what conditions, and with fees paid back to humanity. This approach would challenge the current fragmented network of privately owned data centers and restore collective ownership of human knowledge.6. The transhumanism movement represents an obsession rather than a thoughtful application of technology, in Bulc's view. She distinguishes between using transhumanism as a tool for exploring the universe under extreme conditions where humans cannot survive versus implementing it on Earth as a replacement for humanity. The fundamental problem is that the human characters building these machines and applications have questionable ethical models, and they will not allow the rest of humanity to coexist peacefully on the planet. She advocates for transhumanism to be used for space exploration while preserving Earth for humans who want to live as relational, spiritual, and social beings connected to the natural ecosystem.7. Bulc emphasizes that we must move beyond the competition model and think carefully about the consequences of our actions because humanity is too connected and interdependent to simply do things because we can. She applies three basic laws of quantum physics to everyday life: we are all connected and influence each other, the same ideas can emerge simultaneously around the world through entanglement, and the observer always makes a difference in any situation. The current rush to develop technology without pausing to assess consequences is a deliberate tool to prevent thinking, driven by fear of competition. However, her fourteen years of experience helping companies recover from financial trouble demonstrated that moving away from competition models and focusing on genuinely serving market needs creates sustainable, prominent players who work together with customers and local communities.

How do we make ourselves indispensable in a workforce where we're constantly being replaced? Welcome to today's ICYMI, where we kick off the week with a quick game-changing tip from one of our guests that you might have missed.  In this uncertain job market, the things that make you uniquely you — like your ideas, communication skills and emotional intelligence — are becoming increasingly important for career success. So we're throwing it back to this helpful advice from Emily The Recruiter on how to incorporate AI into your job to stand out, and the soft skills that will make you irreplaceable in the current market. Plus, Emily myth-busts how much of our authentic self we should actually bring to work.  Emily Durham—aka Emily the Recruiter—is a career coach, content creator, and host of the Clock In Podcast. With millions of views across TikTok, Instagram, and YouTube, Emily is known for her no-BS advice on how to land your dream job and deal with workplace dynamics like a boss.xn Listen to the full episode with Emily The Recruiter here. Tune in every Monday for an expert dose of life advice in under 10 minutes. Check out our first episode with Emily here. Follow Emily on Instagram, TikTok, and YouTube.  Subscribe to my Substack:teachmehowtoadult.substack.comFollow us on the ‘gram:@teachmehowtoadultmedia@gillian.bernerFollow on TikTok: @teachmehowtoadultSubscribe on YouTube

Legacy enterprises are facing a decisive shift from stalled pilots and fragmented data toward agentic systems that reshape customer experience, operations, and net‑new revenue.   Matt Renner, President and Chief Revenue Officer at Google Cloud, examines how leaders can move beyond early AI failures to build modern data foundations, orchestrate heterogeneous agents, and accelerate transformation in conversation with Daniel Faggella, Emerj CEO and Head of Research.   The discussion highlights capability‑driven ROI, structured AI governance, data modernization, agentic orchestration, and the emerging security imperatives shaping enterprise adoption.   To listen to the conversations other infrastructure and AI leaders in the Fortune 500 are tuned into, subscribe to the AI infrastructure podcast at emerj.com/inf1

In this episode, we discuss Microsoft's recent commitment of $2.5 billion to establish an AI implementation unit and the implications it may have on corporate transformation. We explore why simply reallocating funds may not address the deeper issue of driving real change in organizational behavior and AI adoption.Chapters00:00 Introduction00:22 Microsoft's AI Investment00:56 Challenges with Implementation03:00 The Behavioral Shift Needed07:00 Role of Leadership in AI Adoption14:35 Conclusion and Recommendations Show LinksGet the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleGet the AI Chat Daily Newsletter: https://www.aichatdaily.com/newsletter

Key Takeaways Solgari's leading innovations: Grant explains that Solgari provides a customer engagement platform built on Azure that extends Microsoft Teams and Dynamics 365 (as well as other CRMs) to capture customer conversations and centralize that data for better engagement. Customers are adopting it to quickly solve specific engagement challenges, gain fast ROI, and apply it to AI strategies to drive more intelligent business outcomes. AI's role in customer engagement: Companies that centralize customer conversations into a single data platform gain an advantage because AI is only as effective as the data it can access. Grant says customer engagement is "ground zero for AI" as it enables capabilities like automation, sentiment analysis, and sales or service intelligence that improve customer satisfaction, reduce costs, and deliver measurable ROI. Use case: Grant shares details on Solgari's involvement with AMB Sports & Entertainment, who own the Atlanta Falcons. Solgari helped them unify fan engagement across voice, SMS, email, and WhatsApp within Microsoft Teams and Dynamics 365, creating a repository of fan conversations in Dataverse. By consolidating this data, AMB Sports & Entertainment is now well positioned to "create momentum around their AI strategy." Final thoughts: In closing, Grant shares why Solgari has shifted its customer and partner conversations away from product demos and toward business outcomes, showing how customer engagement data can evolve into valuable AI use cases over time. Visit Cloud Wars for more.

Kevin Williams is the Founder and CEO of Ascend AI Labs, an AI enablement firm that helps organizations build AI literacy, governance, and implementation strategies. A serial entrepreneur with roots in DTC brand building and digital marketing, Kevin helps companies align leadership, improve workflows, and implement practical AI strategies. His expertise spans enterprise AI adoption, governance, agentic workflows, and transformation for brands. Kevin is also the President of KDF Aegis LLC, a consulting and private equity firm. In this episode… Many brands are racing to adopt AI, but the biggest barrier may not be the technology itself. Before teams can improve workflows or build automation, leaders need to define what AI means for the organization. So where should companies begin when the pressure to move fast collides with uncertainty and unclear direction? As an AI adoption and digital transformation expert, Kevin Williams argues that AI strategy has to start with leadership before data, tools, or technical infrastructure. His approach is to create alignment at the top through a clear AI manifesto, practical governance, and a shared roadmap that helps teams understand how AI will support the business. Rather than waiting for perfect data, Kevin recommends building literacy, giving employees the right connected tools, and identifying high-value workflows where AI can reduce friction. The strongest AI strategies come from the leaders who combine vision, communication, and practical execution. In this episode of The Digital Deep Dive, Aaron Conant talks with Kevin Williams, Founder and CEO of Ascend AI Labs, about why AI strategy starts in the C-suite, not in the cloud. Kevin shares how leadership maturity, AI manifestos, and connected workflows shape adoption. He also touches on agentic automation, implementation costs, cybersecurity risks, and why context makes AI tools more valuable.

Recorded live at SocialWest 2026 in Calgary, Sabaa Quao, venture studio advisor and AI strategist, joins host Lindsay Smith to explore how synthetic data is about to change the way every marketer builds customer models.Sabaa spends his days advising startups at the intersection of AI and fintech, and points to Arima as one of the clearest examples of where this is headed: a synthetic model of society built on 25,000 to 50,000 data points per person, layered on top of a brand's first-party data to fill in the gaps that surveys, forms, and imperfect customer records leave behind.Sabaa breaks down why ecosystems and compounding data models are the two biggest predictors of startup success, how synthetic data stays privacy-first while still getting richer over time, why marketing is behind industries like autonomous driving and fraud detection in adopting it, and what happens when predictive modeling becomes accessible to businesses of every size, not just the ones with a head of data and analytics.Guesswork was never a strategy. Now it doesn't have to be the default either.Edited and Produced by TAKT.

In this insightful episode of The Brand Called You, Ashutosh Garg speaks with Shanil Ebrahim, Partner and Head of AI Strategy at Deloitte Canada, about the evolving role of artificial intelligence in business. Shanil shares his expertise on what defines an effective AI strategy, why many organizations struggle to scale AI beyond pilot projects, and why leadership in the AI era requires a hands-on approach.Discover why successful AI adoption is about far more than technology—it requires transforming business operations, organizational culture, and decision-making processes. Shanil also discusses the importance of data governance, the impact of agentic AI on executive leadership, and how leaders can develop the skills needed to work effectively alongside intelligent systems. Learn what sets AI-native organizations apart and gain practical advice for leading in an AI-first world.Whether you're a business leader, technology professional, or simply curious about the future of AI in organizations, this episode is packed with actionable insights.

I'm thrilled to share some fascinating insights from my latest Capitalist Culture® podcast episode with Joe Toscano, CEO and co-founder of Service Stories, serial entrepreneur, author, and international keynote speaker on technology and humanity.This conversation explores AI, SEO, data privacy, entrepreneurship, and how businesses can leverage emerging technology without losing sight of the humans they serve.Here are the highlights you will not want to miss:Joe's Journey:• From Psychology to Technology: Joe's background in mathematics, psychology, and behavioral economics eventually led him to Silicon Valley and Google.• Inside Google: He worked on major initiatives involving Google AdWords and Google Business Profiles, gaining firsthand insight into how technology companies use research, experimentation, and data to influence product decisions.Leaving Silicon Valley• Challenging the Industry: Joe made the difficult decision to leave Google and publicly question how technology companies were developing and deploying powerful new technologies.• Technology and Humanity: His advocacy eventually led to his appearance in The Social Dilemma and the publication of his book, Automating Humanity.• Integrity Matters: Joe shared how his Nebraska upbringing shaped his belief that technology should serve people, not manipulate them.Building Service Stories• Turning Real Work Into Content: Joe created Service Stories to help service businesses transform everyday customer experiences into valuable digital content.• AI-Powered Growth: The platform uses AI to simplify content creation while preserving the authentic stories and expertise behind the business.• Real Results: Some customers have doubled their website traffic within months by consistently publishing content based on actual work experiences.AI, SEO, and the Future of Search• Search Is Changing: AI is fundamentally reshaping how customers discover companies, products, and services.• Authenticity Creates Advantage: Businesses with original expertise, real customer experiences, and valuable content will be better positioned to stand out in an increasingly automated world.• Global Thinking Matters: Joe shared lessons from designing technology for different languages, cultures, and markets around the world.AI Strategy for Business Leaders• Invest in AI Literacy: CEOs should ensure their teams understand how to use AI effectively rather than simply chasing the latest tools.• Start Small and Learn Fast: Companies can experiment with practical AI applications before making massive technology investments.• Small Language Models Matter: More focused AI systems can offer powerful, cost-effective solutions for specific business problems.Entrepreneurship and Opportunity• AI Is Creating a Window: Smaller companies now have access to technology that can help them compete with much larger organizations.• Execution Still Wins: Technology alone does not create great businesses. Understanding customers, solving real problems, and delivering measurable value remain essential.• Human Judgment Matters: The greatest opportunity is not replacing people with AI, but using technology to make people and organizations more capable.Final Thoughts• Technology Should Serve Humanity: Innovation is most valuable when it improves people's lives rather than simply increasing engagement or profits.• Authentic Expertise Wins: As AI generated content becomes more common, real experiences and trusted voices will become increasingly valuable.• This Is the Moment to Act: Business leaders who develop AI literacy, experiment intelligently, and move with purpose have an extraordinary opportunity to create competitive advantage.I hope these insights inspire you to listen to the full episode. There is so much more depth in this conversation about AI, entrepreneurship, technology ethics, and how businesses can thrive in a rapidly changing digital world.Turn Repair Orders Into New LeadsService Stories turns the work you do every day into content that helps customers find you without extra work for you or your team. Visit the Service Stories website to learn more: https://www.servicestories.com/Looking for your next A player executive?KIP Search® helps companies identify, attract, and hire exceptional leaders who create lasting impact. Visit the KIP Search website and connect with us on LinkedIn to learn how we can help with your executive search needs.P.S. Be sure to subscribe to Capitalist Culture® for more conversations with founders, investors, and leaders shaping the future of business, technology, and culture.Send us Fan MailConnect with Kip on LinkedInhttps://www.linkedin.com/in/kipknippel/Watch Bite-Sized Clips on YouTubehttps://www.youtube.com/@capitalistculture/shorts

What does legal AI value look like once speed stops serving as the headline metric? In this episode of The Geek in Review, Greg Lambert and Marlene Gebauer speak with Nikki Shaver, co-founder and CEO of Legal Technology Hub and a member of the inaugural Financial Times Law 50. Shaver argues that law firms need to move beyond time saved toward efficacy: stronger output, stronger client outcomes, and more effective legal advice.The conversation examines why the billable hour is far from finished yet no longer serves as the sole measure of legal value. Shaver compares hourly timekeeping to a taxi meter: useful for internal visibility, yet insufficient as the price signal for work transformed by AI. Workflow mapping, client discussions, and pricing discipline become central where an AI-enabled process compresses weeks of effort into hours.Corporate legal departments are adopting AI at a faster pace, bringing new pressure to outside counsel. Some in-house teams see AI as a route to keep more work inside, while others see room for firms to take on work that previously sat outside budget limits. Shaver frames the strategic question around delivering more for clients, especially in practice areas where a firm holds differentiated expertise.AI has not produced the promised empty calendar. Instead, lawyers report fuller schedules, longer documents, and a growing verification tax. Shaver flags the rise of 40-page forms, bloated redlines, and outputs that look polished yet lack sound reasoning. The episode makes a practical case for concise drafting, human review, and critical reasoning before any AI-generated material reaches a client or counterparty.Agentic AI raises the stakes. Legal Technology Hub's AI Agents in Law Map tracks hundreds of solutions, yet governance has not kept pace with new autonomy, connectors, and downstream system access. Shaver urges firms to establish traceability, unique identifiers, risk-based human oversight, enforceable policies, and a clear view of where data travels.For firms aiming past baseline adoption, Shaver draws a line between routine personal use and strategic transformation. Daily use builds fluency, but competitive advantage grows from proprietary workflows, data foundations, client-facing collaboration spaces, and focused investment in the practices where a firm already excels. Her crystal-ball view is blunt: trusted judgment will become a scarce premium asset, AI-native firms will rise, and traditional firms will launch AI-native subsidiaries of their own.Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠Substack⁠[Special Thanks to ⁠⁠Legal Technology Hub⁠⁠ for their sponsoring this episode.]⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.comMusic: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠Transcript:

While we take a break this 4th of July weekend, please enjoy this encore of AI Security Brief. Your enterprise AI strategy isn't as far along as you think. The reality for most organizations today is that AI is disrupting existing processes more than it's delivering outcomes… so far. And according to Dr. Grace Trinidad, Research Director at IDC, that's how it should be. In this episode, host Johnny Hand sits down with Dr. Grace to discuss how AI adoption follows the same pattern as almost every major digital transformation, and why this disruption phase we're in is messy, yet critically important.  What we cover: How history demonstrates that automation across industries created disruption well before delivering value Why your AI adoption strategy is much more than simple tool deployment What business and technology leaders need to consider as they integrate AI into operational workflows How token consumption and AI FinOps are the emerging security and cost risk How AI ontologies will be the next real business differentiator Why stick around:  If you've been wondering if your organization's AI adoption strategy is ahead of the curve, Dr. Grace will give you a much clearer picture of where you really stand. Episode resources: Dr. Grace Trinidad on LinkedIn Securing the AI Enterprise: 5 Key Steps for Business Leaders Closing the Governance Gap in Agentic AI ⁠Johnny Hand on LinkedIn TrendAI on LinkedIn About AI Security Brief AI Security Brief is where security and technology leaders come to get ahead. Join us for real conversations on the AI trends, threats, and decisions that can't wait. About TrendAI™ TrendAI™ empowers organizations to lead the future of AI with proactive security designed to inspire innovation and eliminate risk. TrendAI™. AI Fearlessly. Learn more about your ad choices. Visit megaphone.fm/adchoices

While we take a break this 4th of July weekend, please enjoy this encore of AI Security Brief. Your enterprise AI strategy isn't as far along as you think. The reality for most organizations today is that AI is disrupting existing processes more than it's delivering outcomes… so far. And according to Dr. Grace Trinidad, Research Director at IDC, that's how it should be. In this episode, host Johnny Hand sits down with Dr. Grace to discuss how AI adoption follows the same pattern as almost every major digital transformation, and why this disruption phase we're in is messy, yet critically important.  What we cover: How history demonstrates that automation across industries created disruption well before delivering value Why your AI adoption strategy is much more than simple tool deployment What business and technology leaders need to consider as they integrate AI into operational workflows How token consumption and AI FinOps are the emerging security and cost risk How AI ontologies will be the next real business differentiator Why stick around:  If you've been wondering if your organization's AI adoption strategy is ahead of the curve, Dr. Grace will give you a much clearer picture of where you really stand. Episode resources: Dr. Grace Trinidad on LinkedIn Securing the AI Enterprise: 5 Key Steps for Business Leaders Closing the Governance Gap in Agentic AI ⁠Johnny Hand on LinkedIn TrendAI on LinkedIn About AI Security Brief AI Security Brief is where security and technology leaders come to get ahead. Join us for real conversations on the AI trends, threats, and decisions that can't wait. About TrendAI™ TrendAI™ empowers organizations to lead the future of AI with proactive security designed to inspire innovation and eliminate risk. TrendAI™. AI Fearlessly. Learn more about your ad choices. Visit megaphone.fm/adchoices

In this episode of The Product Podcast by Product School, Carlos González de Villaumbrosia sits down with Arnab Bose, Chief Product Officer at Asana. Asana is the work management platform built for human and AI collaboration, trusted by over 170,000 customers including Accenture, Amazon, and Anthropic. The platform's Work Graph maps goals to portfolios to projects to tasks and serves as the foundation for Asana's AI Teammates: collaborative agents that operate inside the graph, learn from human decisions, and compound their intelligence with every cycle. What you'll learn:Why enterprise AI spend keeps returning zero productivity gains, and what is structurally breaking the loopWhy every employee approval, correction, or rejection of AI output is training data that makes the system smarter over timeHow Asana wires its own processes through the Work Graph so that AI decisions write back automatically and compound rather than resetHow PLG, forward-deployed engineers, and AI agents all report to the CPO, each under a GM who owns a revenue numberWhy the future of AI at work belongs to whoever has the richest shared context, not whoever has the best modelKey takeaways:Individual AI productivity gains compound into zero enterprise ROI when decisions never write back into a shared systemEvery human approval or correction is training data. The companies that capture it structurally will pull ahead of those that don'tPLG is an acquisition funnel, not a sales motion. Giving it a GM with a revenue number inside product changes the incentives entirelyCredits:Host: Carlos Gonzalez de VillaumbrosiaGuest: Arnab BoseSocial Links:Find out more about Product School hereFollow our Podcast on TikTok hereFollow Product School on LinkedIn here

Welcome to The Daily Wrap Up, an in-depth investigatory show dedicated to bringing you the most relevant independent news, as we see it, from the last 24 hours (6/24/26). As always, take the information discussed in the video below and research it for yourself, and come to your own conclusions. Anyone telling you what the truth is, or claiming they have the answer, is likely leading you astray, for one reason or another. Stay Vigilant. !function(r,u,m,b,l,e){r._Rumble=b,r[b]||(r[b]=function(){(r[b]._=r[b]._||[]).push(arguments);if(r[b]._.length==1){l=u.createElement(m),e=u.getElementsByTagName(m)[0],l.async=1,l.src="https://rumble.com/embedJS/u2q643"+(arguments[1].video?'.'+arguments[1].video:'')+"/?url="+encodeURIComponent(location.href)+"&args="+encodeURIComponent(JSON.stringify([].slice.apply(arguments))),e.parentNode.insertBefore(l,e)}})}(window, document, "script", "Rumble");   Rumble("play", {"video":"v79oxc2","div":"rumble_v79oxc2"}); Source Links (In Chronological Order): Trump says Iran hit ship in Strait of Hormuz, violating ceasefire (21) محمدباقر قالیباف | MB Ghalibaf on X: "America falsely claims our unfrozen assets will buy their agriculture. Interesting. The only crop we're harvesting is what you planted: decades of mistrust. It's organic, abundant, and homegrown. But apparently the US only exports GMO soybeans, broken promises and trash talks." / X (21) Eric Daugherty on X: "

The Transformation Ground Control podcast covers a number of topics important to digital and business transformation. This episode covers the following topics and interviews:   What Real OCM Actually Looks Like Change Management Isn't Fluffy (Afra Corona, Organizational Change Management Consultant at Third Stage Consulting) The Backfill Problem   We also cover a number of other relevant topics related to digital and business transformation throughout the show.  

In this episode of The Product Podcast by Product School, Carlos González de Villaumbrosia sits down with Jay Choi, Chief Executive Officer at Typeform. Typeform is the AI engagement platform trusted by more than 150,000 customers, including 95% of the Fortune 500. Before Typeform, Jay spent seven years as Chief Product Officer and General Manager at Qualtrics, where the company scaled from $100M to over $1B in ARR.What you'll learn:Breadth of surface area as a stronger AI moat than depth of use case, and why going broad is the right strategic bet right nowThe dual posture Typeform built: a defensive strategy to make their core product impossible to replicate, and an offensive strategy to expand into full customer workflowsResearch Flow, their new product that compresses 50 customer interviews from weeks into hours using AI-moderated researchBeing model-agnostic from day one, and what they learned when switching models without an observability platform in placeThe pricing experiment framework Jay uses: 30 simulations before a single market goes liveKey takeaways:When AI threatens to commoditize your core product, expanding surface area is a stronger defense than adding AI features to what you already havePositioning AI capabilities in plain language, not technical terminology, is the difference between adoption and abandonmentHappy churners are a product problem, not a marketing problem: the fix is finding structurally always-on use cases.Credits:Host: Carlos Gonzalez de VillaumbrosiaGuest: Jay ChoiSocial Links:Find out more about Product School hereFollow our Podcast on TikTok hereFollow Product School on LinkedIn here

Daniel moderated a live panel at Running Remote 2026 with Carmen Amara (Yelp), Brandon Sammut (Zapier), and Vinícius Coelho (Time Doctor) to discuss how AI is reshaping leadership, management, and career growth. ----  Sponsor Links:

What if the biggest AI challenge for CFOs is not the technology itself, but the culture and processes required to use it well? In this episode, host Heather Cole sits down with Jennifer Witts (Partner) and Kyle Vroegh (Director) of CohnReznick's Client Advisory Services Practice to unpack what separates financial leaders seeing real AI results from those spinning their wheels. They cover where CFOs should start with AI adoption, why layering automation on broken processes backfires, how to build a psychologically safe culture around experimentation, what governance and security questions to ask when evaluating outside firms, and how the role of the financial executive is shifting toward advisory and strategic work. Whether you are excited, overwhelmed, or somewhere in between, this episode offers a practical, no-hype path forward – one bite-sized use case at a time.Special Guests: Jennifer Witts and Kyle Vroegh.

Welcome to episode #1041 of Thinking With Mitch Joel (formerly Six Pixels of Separation). At a time when every leadership team is being told that artificial intelligence will change everything, Charlene Li has spent her career helping organizations separate signal from noise. A New York Times bestselling author and trusted advisor to CEOs and boards, Charlene first became widely known for helping leaders understand transformative shifts through books like Groundswell, Open Leadership and The Disruption Mindset. Her latest book, Winning With AI - The 90-Day Blueprint For Success, co-authored with Dr. Katia Walsh, tackles one of the most pressing questions facing business leaders today: not what AI is, but what to do about it. Drawing on research, executive interviews and practical experience, Charlene argues that organizations do not need an AI strategy… they need to rethink how AI serves their existing business strategy. In our conversation, she explores why most organizations are still struggling to move beyond experimentation, why leadership and transformation matter more than technology selection, and why the greatest opportunity may not be efficiency at all, but creating more human-centered organizations. Along the way, Charlene challenges conventional thinking about AI pilots, workforce transformation, organizational design and the future role of leadership in an era where intelligence itself is becoming abundant. Enjoy the conversation… Running time: 1:01:50. Hello from beautiful Montreal. Listen and subscribe over at Apple Podcasts. Listen and subscribe over at Spotify. Please visit and leave comments on the blog - Thinking With Mitch Joel. Feel free to connect to me directly on LinkedIn. Check out ThinkersOne. Here is my conversation with Charlene Li. Winning With AI - The 90-Day Blueprint For Success. Dr. Katia Walsh. Groundswell. Open Leadership. The Disruption Mindset. Charlene's other books. Follow Charlene on LinkedIn. Chapters: (00:00) - Introduction to AI and Leadership. (03:02) - Navigating the AI Landscape. (05:57) - Understanding AI's Impact on Organizations. (09:09) - The Human Element in AI. (12:10) - Rethinking Workflows and Decision-Making. (14:45) - Strategic AI Roadmaps. (17:54) - Investment and Governance in AI. (20:52) - Creating Value with AI. (23:53) - Emergent Thinking and AI Adoption. (31:00) - The Role of Leadership in AI Implementation. (34:50) - Ownership and Accountability in AI Strategy. (39:01) - Creating Value Beyond Efficiency with AI. (45:07) - Navigating Workforce Changes and Reskilling. (48:59) - Addressing Employee Concerns About AI. (54:54) - The Case Against AI Pilots. (55:54) - The Importance of Speed in AI Adoption.

...it needs an AI learning system. This episode argues that the Fable 5 disruption exposed a deeper enterprise problem: companies can't treat AI as a vendor strategy. The real advantage will come from building learning systems that capture institutional judgment, workflow traces, private evals, and model-portable IP. In the headlines: could Anthropic and the White House be headed for a resolution? Register for our new enterprise-grade AI training programs: http://training.besuper.ai/⁠Brought to you by:KPMG – Research from KPMG and the University of Texas at Austin shows the highest-impact AI users treat AI like a reasoning partner — and those skills can be taught at scale. Learn more at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠kpmg.com/us/Sophisticated⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Section - Section turns AI investment into workforce transformation and ROI - ⁠⁠⁠https://www.sectionai.com/⁠⁠⁠Outsystems - Stop wondering how AI will change your business and start building the agents that will lead it - ⁠⁠http://outsystems.com/⁠⁠Scrunch - The AI customer experience platform - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://scrunch.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Zenflow Work - Agents for knowledge work - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://zenflow.free/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Blitzy - Want to accelerate enterprise software development velocity by 5x? ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://blitzy.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠MissionCloud - Eliminate AWS complexity with end-to-end cloud and AI services ⁠⁠https://www.missioncloud.com/⁠⁠AssemblyAI - The best way to build Voice AI apps - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.assemblyai.com/brief⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Robots & Pencils - Cloud-native AI solutions that power results ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://robotsandpencils.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠The AI Daily Brief helps you understand the most important news and discussions in AI. Subscribe to the podcast version of The AI Daily Brief wherever you listen: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://pod.link/1680633614⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Our Newsletter is BACK: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://aidailybrief.beehiiv.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Interested in sponsoring the show? sponsors@aidailybrief.ai

What happens when one of the world's largest enterprise software companies declares that it is no longer a software company, but an AI company? At SAP Sapphire, I caught up with James Bates, Head of Customer Advisory at SAP UK & Ireland, to discuss the company's vision for what it calls the Autonomous Enterprise and why this year's event felt different from any SAP conference before it. From standing-room-only AI sessions to bold declarations from SAP leadership, there was a clear sense that the conversation around AI has moved beyond experimentation and into the world of measurable business outcomes. In our conversation, James explained why so many organizations remain stuck in what he described as the experimentation phase of AI, despite years of investment and countless pilot projects. We explored why successful AI initiatives begin with business outcomes rather than technology choices and why data, governance, and process context have become the foundations of enterprise AI success. We also examined some of the standout announcements from Sapphire, including SAP's AI Agent Hub, the growing role of Joule as a new interface for work, and the company's expanding ecosystem of partnerships with organizations including Anthropic, NVIDIA, Microsoft, Google Cloud, Palantir, and Mistral. James shared why SAP believes the future lies in combining large language models with business context, process knowledge, and trusted enterprise data. The discussion also touched on real-world examples that demonstrate how AI agents are beginning to transform customer experiences, automate complex workflows, and support employees across finance, supply chain, and customer-facing operations. Rather than replacing people, James sees AI assistants and agents working alongside employees, removing repetitive tasks and helping teams focus on higher-value activities. We also explored the challenge many business leaders continue to wrestle with: how to balance autonomy with governance. As AI agents become more capable, maintaining visibility, accountability, and control becomes increasingly important. James shared why governance, trusted data, and strong business processes must remain at the center of every AI strategy. If you've been wondering whether enterprise AI is finally moving beyond the hype cycle and into meaningful business transformation, this conversation offers a fascinating perspective from the heart of SAP's AI strategy and its vision for the future of work. What role do you think AI agents will play inside your organization over the next few years? Share your thoughts.

Gary Shapiro has spent decades at the center of the global consumer technology industry, leading the Consumer Technology Association (CTA) and building CES into one of the most important stages for innovation, policy, and deal-making on the planet.In this first episode of 2026, Gary joins Charlie, Rony, and Ted to preview CES, unpack the explosion of AI across every category, and deliver unusually blunt takes on tariffs, China, manufacturing, and U.S. innovation policy. He explains how CES has evolved from a TV-and-gadgets show into a global platform where boards meet, standards are set, and policymakers, chip designers, robotics firms, and health-tech startups all collide.In the News: Before Gary joins, the hosts break down Nvidia's $20 billion “not-a-deal” with Singapore's Groq, the stake in Intel, and what that combo might signal about the edge of the GPU bubble and the shift toward inference compute, x86, and U.S. industrial policy. They also dig into Netflix's acquisition of Ready Player Me and what it suggests about a Netflix metaverse and location-based entertainment strategy, plus Starlink's rapid growth and an onslaught of “AI everything” products ahead of CES.Gary walks through new features at this year's show: CES Foundry at the Fontainebleau for AI and quantum, expanded tracks on manufacturing, wearables, women's health, and accessibility, plus an AI-powered show app already fielding thousands of questions (top query: where to pick up badges).He also talks candidly about his biggest concern—that fragmented state-level AI regulation (1,200+ state bills in 2025) will crush startups while big players shrug—and why he believes federal standards via NIST are the only realistic path. The discussion ranges from AI-driven healthcare and precision agriculture to robotics, demographics, labor culture, global supply chains, and what CES might look like in 2056.5 Key Takeaways from Gary:AI is now the spine of CES. CES 2026 centers on AI as infrastructure: CES Foundry at the Fontainebleau for AI + quantum, AI training tracks for strategy, implementation, agentic AI, and AI-driven marketing, and an AI-powered app helping attendees navigate the show.Fragmented state AI laws are an existential risk for startups. Over 1,200 state AI bills in 2025—including proposals to criminalize agentic AI counseling—could create a compliance maze only large incumbents can survive, which is why Gary argues for federal standards via NIST.Wearables are becoming systems, not gadgets. Oura rings, wrist devices, body sensors, and subdermal glucose monitors are starting to be designed as interoperable families of devices, with partnerships emerging to combine data into unified health services.Robotics is breaking out of the industrial niche. CES will showcase the largest robotics presence yet, moving beyond factory arms and drones to humanoids, logistics, social companions, and applied AI systems across sectors.Tariffs, alliances, and AI will reshape manufacturing. Gary is skeptical of “Fortress USA” strategies that try to onshore everything, pointing instead to allied reshoring (Latin America, Europe, Japan, South Korea) and the long-term role of AI-powered robotics in changing labor economics and global supply chains.This episode is brought to you by Zappar, creators of Mattercraft—the leading visual development environment for building immersive 3D web experiences for mobile headsets and desktop. Mattercraft combines the power of a game engine with the flexibility of the web, and now features an AI assistant that helps you design, code, and debug in real time, right in your browser. Whether you're a developer, designer, or just getting started, start building smarter at mattercraft.io. Hosted on Acast. See acast.com/privacy for more information.

From Tesla's Model 3 era to Waymo to founding LightSource, Spencer Penn has built at the frontier of transformation. In this episode, Sal Silvester and Spencer unpack what leaders can learn from radically different cultures (Tesla's “flat org, vertical power” vs. Waymo's “layered org, grassroots power”), the values he's building inside LightSource, and the real leadership challenge of pushing aggressive timelines without burning people out. We close with a grounded take on AI adoption—why most organizations are still early, what “AI strategy” should actually start with, and where automation is likely to hit first.

The Transformation Ground Control podcast covers a number of topics important to digital and business transformation. This episode covers the following topics and interviews:   ERP Status Reporting Best Interview Moments (Kristin Valentyn, Karm Saliba, Greg Benton, Jeff Winter, & More) Follow the Money: Why ERP Projects Fail   We also cover a number of other relevant topics related to digital and business transformation throughout the show.  

For episode 300 of The Product Podcast, Carlos Gonzalez de Villaumbrosia sits down with Ajit Varma, Head of Firefox at Mozilla, the nonprofit behind the original challenger browser that pioneered browser tabs, pop-up blockers, and browser extensions. With 210 million active users and $826 million in annual revenue, Firefox is the only major independent, open-source browser still standing against Google Chrome's 68% share, Apple Safari's 17%, and a new wave of agentic browsers. Before Mozilla, Ajit spent six years at Meta leading monetization of WhatsApp and overseeing its business messaging platform. He has also held product roles at Google, Uber, and Square.What you'll learn:Why LLMs are making browsers more strategically important, and what that means for product teams building in an agentic worldWhy "trust us" is no longer enough, and how open source changes the standard for privacy in AI products- How to compete against trillion-dollar incumbents without abandoning your missionKey takeaways:Privacy claims without open-source inspectability are unverifiable, "trust us" is no longer a sufficient product strategy in the AI eraCompeting against trillion-dollar companies is possible when mission clarity defines what you refuse to optimize forThe agent-driven internet will either democratize access or concentrate it, product choices made today will determine whichSocial Links:Find out more about Product School hereFollow our Podcast on TikTok hereFollow Product School on LinkedIn here

What does strategy look like when the technology industry seems to change every few months? Recorded at Cisco Live, this episode features Ammar Maraqa, Cisco's Chief Strategy Officer, whose role spans corporate strategy, mergers and acquisitions, venture investments, technology incubation, strategic partnerships, and long-term planning. Few people have a broader view of where the technology industry is heading and how companies can position themselves for what comes next. During our conversation, Ammar shares why he believes many organizations are thinking about AI the wrong way. Rather than viewing it as a productivity tool or cost-saving exercise, he argues that AI represents a much deeper shift in how work gets done, how organizations operate, and how leaders should think about growth. We explore Cisco's approach to strategy in an era defined by constant disruption, including why the company focuses on testing assumptions rather than repeatedly changing direction. Ammar also explains how Cisco uses a combination of building, acquiring, partnering, investing, and incubating to accelerate innovation and stay close to emerging technologies. The discussion also examines what Cisco learns from engaging with startups, entrepreneurs, venture investors, customers, and partners around the world. From advances in AI infrastructure and silicon to agent orchestration, observability, security, and enterprise adoption, Ammar shares the themes he believes deserve the closest attention from business leaders today. We also discuss one of the biggest challenges facing organizations: the growing gap between what AI is capable of and what companies are actually prepared to adopt. Ammar explains why infrastructure, data, security, workflow redesign, and organizational change remain essential ingredients for success, regardless of how powerful the underlying models become. Along the way, he offers insights into business model disruption, the future of enterprise software, and why some companies successfully reinvent themselves while others struggle to adapt. If you're interested in strategy, innovation, AI adoption, or the forces shaping the next decade of enterprise technology, this conversation provides a thoughtful perspective from someone helping guide one of the industry's most influential companies through a period of extraordinary change. How often does your organization challenge the assumptions behind its strategy, and would those assumptions still hold true if you were making them today?

Keith Kirkpatrick breaks down the market's negative reaction to Adobe's (ADBE) strong quarter, pointing to concerns around its freemium model and leadership changes. He highlights the long-term value of Adobe's AI strategy for enterprise customers, while noting investor focus on execution, including converting free users to paid subscribers and navigating the CFO's departure to Marvell (MRVL).======== Schwab Network ========Empowering every investor and trader, every market day.Subscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – https://twitter.com/schwabnetworkFollow us on Facebook – https://www.facebook.com/schwabnetworkFollow us on LinkedIn - https://www.linkedin.com/company/schwab-network/About Schwab Network - https://schwabnetwork.com/about

Are you looking at AI through a rearview mirror and making the same mistakes every generation makes during technological change?   Everywhere you turn, people are predicting what AI will do to jobs, leadership, and business. The problem? Nobody really knows. In this episode, Bradley Hartmann explores Marshall McLuhan's groundbreaking book The Medium Is the Massage and reveals why today's AI debates sound remarkably similar to conversations that happened decades ago around television, integrated circuits, and the Internet. If you're a leader trying to make sense of rapid change without getting caught up in fear or hype, this episode offers a refreshing perspective.    In this episode you will Discover why every generation believes its technological disruption is different and why history suggests otherwise. Learn McLuhan's powerful concept that technology doesn't just help us; it changes how we think, communicate, and lead. Understand how curiosity, experimentation, and dialogue can help leaders navigate uncertainty more effectively than predictions and fear.   Listen now to gain a practical framework for leading confidently through AI uncertainty and technological change without losing focus on what matters most.   At Bradley Hartmann & Company, we help construction teams improve sales, leadership,  and communication by reducing miscommunication, strengthening teamwork, and bridging language gaps between English and Spanish speakers. To learn more about our product offerings, visit bradleyhartmannandco.com.   The Construction Leadership Podcast dives into essential leadership topics in construction, including strategy, emotional intelligence, communication skills, confidence, innovation, and effective decision-making. You'll also gain insights into delegation, cultural intelligence, goal setting, team building, employee engagement, and how to overcome common culture problems—whether you're leading a crew or managing an entire organization.   Have topic ideas or guest recommendations? Contact us at info@bradleyhartmannandco.com.   New podcasts are dropped every Tuesday and Thursday.     This episode is brought to you by The Construction Spanish Toolbox —the most practical way for construction teams to learn jobsite-ready Spanish in just minutes a day over 6 months.      

The Transformation Ground Control podcast covers a number of topics important to digital and business transformation. This episode covers the following topics and interviews:   When Output Becomes Unlimited, Judgment Becomes Priceless What Machines Can't Replace (Jim Koetting) You're Not the Hero — You're the Guide We also cover a number of other relevant topics related to digital and business transformation throughout the show.  

See what the team at The Successful Bookkeeper has on right now → AI is moving fast, and the bookkeeping profession is squarely in its path — but not in the way most people fear. In this episode, Michael Palmer sits down with AI strategist and educator Benjamin Tasker to talk about what the shift actually looks like on the ground, which skills will separate bookkeepers who thrive from those who stall, and how to start building your own AI system without a data science degree. Chapters [00:00] Welcome and Ben's Background [03:15] From Data Science to AI Education [08:00] AI's Real Impact on Bookkeeping [12:00] Human Judgment as the Key Check [15:30] Skills That Separate Thriving Bookkeepers [21:00] Data, Systems, and AI Strategy [25:00] Opportunities to Move Up the Value Chain [29:00] First Steps for Integrating AI [32:00] Client Expectations and Transparency [35:00] Fear, Mindset, and Where to Find Ben AI Will Elevate Bookkeeping, Not Replace It Ben is direct about the headline fear: bookkeepers are not going away. "AI will help elevate what a bookkeeper does," he says. The repetitive work — transaction coding, receipt capture, anomaly detection, drafting reports — gets absorbed by AI, which frees up the bookkeeper to move from data entry to data judgment. Think less time in the books and more time coaching clients on their financial pain points. AICPA and Intuit both point in the same direction: the future of the role looks a lot more like analytics and advisory than data input. The Two Skill Lanes Every Bookkeeper Should Know Ben references the World Economic Forum's skills taxonomy, which divides skills into two tracks. AI skills — analytical thinking, systems thinking, coding — pay a premium today, but AI will eventually encroach on those. Human skills — communication, empathy, leadership — are undervalued right now but will command a premium as AI can only mimic, never genuinely replace, them. "AI can put on a facade of empathy and compassion, but it really can't have it because it's robotic." For bookkeepers, the practical focus areas are AI supervision (checking outputs rigorously), advisory thinking, digital and data fluency, and transparent client communication. The Human in the Loop Is Not Optional Ben's background in healthcare data — building algorithms to predict sepsis risk from bedside monitors — gives him a sharp view on why human validation matters. A small data error that goes unchecked can cascade into a much larger problem. "A mistake, especially for a small business owner, could cost tens of thousands of dollars." Bookkeepers already understand this: the work is either right or it isn't. That precision mindset is exactly what responsible AI use demands, and it is a genuine competitive advantage for practitioners who carry it into their AI workflows. Data Is the Oil — Build a System, Not Just a Stack of Tools One of Ben's clearest points: buying an AI tool is not an AI strategy. The framework he outlines is straightforward — start with your data (client records, call transcripts, templates, Google Sheets), run it through a system you build and control, apply AI to it, then validate and iterate. "Just because you buy an AI tool doesn't mean you have an AI strategy or even an AI business." He encourages bookkeepers to build their own processing systems rather than relying entirely on third-party integrations that can change without warning. Start small — something as simple as having AI draft follow-up emails from call transcripts is a low-risk, high-value first step. Practical First Steps and Client Communication For bookkeepers ready to start, Ben's advice is to pick a low-stakes problem, solve it, and let that build confidence. Use AI to profile prospective clients from call transcripts, automate follow-up reminders, or create a client-facing dashboard from existing data. On the client side, transparency is non-negotiable: communicate that you are using AI, explain how it benefits them, and teach them how to give better inputs so they get better outputs. "By providing inputs and encouraging your customers to use AI to show them the benefits of it, they're going to become less resistant over time." That kind of teaching deepens the client relationship well beyond what traditional bookkeeping alone can offer. Links Mentioned Ben Tasker AI: bentaskerai.com Ben Tasker on LinkedIn World Economic Forum Skills Taxonomy (AI skills and human skills tracks) The Successful Bookkeeper Pure Bookkeeping About the Guest Benjamin Tasker is an AI strategist, educator, and speaker with over 10 years of experience in data science and artificial intelligence. His background spans healthcare predictive analytics, higher education, and enterprise AI strategy. Today he helps entrepreneurs and large organizations build the skills and systems they need to navigate the AI revolution. You can find his prompting frameworks, podcast appearances, and upcoming events at bentaskerai.com. About the hostMichael PalmerMichael Palmer is the host of The Successful Bookkeeper podcast and co-founder of Pure Bookkeeping and The Successful Bookkeeper. He started this work because of his father — a brilliant electrical contractor who worked twice as hard as he should have had to, because nobody on the financial side was in his corner. That gap is what The Successful Bookkeeper exists to close. His view: bookkeepers are the most undervalued force in small business — and every bookkeeper who builds a real business changes two families: theirs, and their clients'.

AI is changing how people discover, evaluate, trust, buy, create, hire, and compete. The bigger question is whether your business model is built to survive a future where attention is fragmented, trust is harder to earn, execution is easier to automate, and buyers have more options than ever. Learn how to activate the M.A.S.S. Effect Business Model, a strategic ecosystem built around: • Media to create attention, trust, authority, and discoverability • Assets to create scalability, leverage, and income beyond your direct time • Strategy to create clarity, alignment, interpretation, and better decisions • Systems to reduce friction, support consistency, and keep the business moving Many businesses are addicted to acquisition because they never built retention. In an AI accelerated world, that becomes dangerous because information is easier to access, skills are being compressed, and execution is becoming automated. The real value now shifts toward trust, experience, clarity, influence, systems, and community. The future belongs to adaptive businesses that can evolve with the market, keep customers connected, turn trust into retention, and scale without breaking the founder, team, or customer experience. If your business grew tomorrow, could it actually hold the growth, or would the model collapse under the weight of what you asked for? Beyond The Episode Gems: Buy Troy's Book, Strategize Up: The Blueprint To Scale Your Business StrategizeUpBook.com Discover All Podcasts On The HubSpot Podcast Network Get Free HubSpot Marketing Tools To Help You Grow Your Business Grow Your Business Faster Using HubSpot's CRM Platform Support The Podcast & Connect With Troy:  Rate & Review iDigress: iDigress.fm/Reviews Follow Troy's Socials @FindTroy: LinkedIn, Instagram, Threads, TikTok Subscribe to Troy's YouTube Channel For Strategy Videos & See Masterclass Episodes Need Growth Strategy, A Keynote Speaker, Or Want To Sponsor The Podcast? Go To FindTroy.com

The Prime Minister unveils a new AI strategy that he says will help Canada catch up with the rest of the world. Our guest says it's a start, but it could use some fine-tuning. Hezbollah has rejected a ceasefire deal brokered between Israel and Lebanon; our guest in Beirut tells us people there were already referring to it as a "less-fire" anyway. A protestor in Albania tells us a crucial stopover for migrating birds is in danger of being destroyed — because Jared Kushner and Ivanka Trump want to build a resort. Trixie and Nacho have been busy getting busy — which is great, because the prolific parakeet couple are almost singlehandedly rebuilding New Zealand's kākāriki karaka population.A scientist explains how the late Nobel Prize-winning physicist Richard Feynman devised a mathematical solution to the eternal question: stick with your favourite restaurant, or risk trying somewhere new?Blanket forts aren't just a quilt draped over some stuffed animals on the couch anymore — now that some students in Las Vegas have definitively shattered the world record for building the biggest one ever."As It Happens", the Thursday Edition. Radio that's usually suspicious of blanket statements.

You know the moment. Your project plan is solid. The scope is defined. The team is ready. Then an executive walks by and casually asks: "Can we just make this AI?" Suddenly you're no longer managing a project. You're managing expectations, buzzwords, corporate excitement, and whatever article someone just read on the flight home from a conference. In this episode, Kim and Kate tackle the question nearly every project manager is hearing right now: What's your AI strategy? They discuss why this isn't the first technology hype cycle we've lived through, how to respond when leaders want AI without knowing what they actually want AI to do, and why saying "yes" doesn't mean committing to anything. Along the way, they unpack executive AI buzzwords, governance concerns, AI productivity myths, vibe coding, project management tools, and where AI genuinely helps versus where it's mostly creating noise. Most importantly, they share practical ways to stay credible, keep your projects grounded, and avoid getting swept up in the latest technology frenzy. So grab a drink, pull up your RAID log, and let's talk about surviving the AI gold rush without losing your mind.