The Macro AI Podcast

The AI Guides - Gary Sloper & Scott Bryan

Welcome to "The Macro AI Podcast" - we are your guides through the transformative world of artificial intelligence.     In each episode - we'll explore how AI is reshaping the business landscape, from startups to Fortune 500 companies. Whether you're a seasoned executive, an entrepreneur, or just curious about how AI can supercharge your business, you'll discover actionable insights, hear from industry pioneers, service providers, and learn practical strategies to stay ahead of the curve.  

  1. Data Commons — The Emerging Infrastructure of AI

    3 DAYS AGO

    Data Commons — The Emerging Infrastructure of AI

    In this episode of The Macro AI Podcast, Gary and Scott dive deep into the emerging concept of Data Commons — shared, governed ecosystems that make data interoperable, trusted, and ready for AI.  They explain what a Data Commons is, how it differs from traditional data lakes, and why it’s essential to the next phase of AI transformation. From Google’s global Data Commons and the NIH’s biomedical repositories to emerging “Private Data Commons” inside enterprises, the hosts show how these ecosystems are reshaping trust, governance, and efficiency.  Listeners will learn how Data Commons reduce AI hallucination, enable grounding, improve reproducibility, and support ethical AI. Gary and Scott also explore governance models, global equity, and the rise of AI agents that automatically fetch verified data from commons networks.  If you’re a CIO, CTO, or business leader preparing your organization for AI, this episode offers the strategic framework you’ll need to understand the infrastructure of the future.  🔗 Links mentioned:  Google Data Commons Open Data Policy Lab — AI Data Commons Blueprint Therapeutics Data Commons NIH Data Commons     Send a Text to the AI Guides on the show! About your AI Guides Gary Sloper https://www.linkedin.com/in/gsloper/ Scott Bryan https://www.linkedin.com/in/scottjbryan/ Macro AI Website: https://www.macroaipodcast.com/ Macro AI LinkedIn Page: https://www.linkedin.com/company/macro-ai-podcast/ Gary's Free AI Readiness Assessment: https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness Scott's Content & Blog https://www.macronomics.ai/blog

    14 min
  2. AI & Jobs: Disruption Now, or Not Yet?

    6 DAYS AGO

    AI & Jobs: Disruption Now, or Not Yet?

    In this episode, Gary and Scott unpack one of the most critical questions for business leaders today: Is AI actually disrupting the labor market—or are we still waiting for impact to show up in the data?  They dive deep into Yale University’s Budget Lab study, “Evaluating the Impact of AI on the Labor Market: Current State of Affairs” (October 2025), which concludes that there has been no discernible economy-wide labor disruption since the launch of ChatGPT in late 2022. Using decades of labor data, the Yale team found that the pace of occupational change today looks remarkably similar to earlier waves of innovation like the PC and Internet eras.  But Gary and Scott don’t stop there. They explore contradictory findings from other top institutions:  Stanford’s Digital Economy Lab (Aug 2025): Early-career workers in AI-exposed jobs have seen employment drop by roughly 13%, signaling localized disruption. IMF (2024): Up to 40% of jobs globally are exposed to AI, especially in advanced economies. OECD & WEF (2024–25): AI is already reshaping skills demand, with executives expecting major restructuring by 2030. Throughout the episode, Gary and Scott translate these insights into an executive playbook for 2025:  ✅ Build an internal AI exposure map by task.  ✅ Track real adoption and productivity telemetry.  ✅ Reinvent early-career roles through apprenticeships.  ✅ Reinvest AI gains into upskilling and responsible adoption.  The takeaway? No broad labor shock yet—but localized tremors are real.  The smartest leaders are already using data to navigate the gray zone between augmentation and automation.  Referenced Research:  Yale Budget Lab (2025): Evaluating the Impact of AI on the Labor Market: Current State of Affairs Stanford Digital Economy Lab (2025): AI Exposure and Early-Career Employment Effects (working paper) IMF (2024): Generative AI and the Future of Work OECD Employment Outlook (2024): AI, Skills, and the Changing Labor Market World Economic Forum (2025): Future of Jobs Report Takeaway: AI is transforming how we work, not yet how many of us work. Stay adaptive, build visibility into your workforce data, and lead with metrics—not headlines.    Send a Text to the AI Guides on the show! About your AI Guides Gary Sloper https://www.linkedin.com/in/gsloper/ Scott Bryan https://www.linkedin.com/in/scottjbryan/ Macro AI Website: https://www.macroaipodcast.com/ Macro AI LinkedIn Page: https://www.linkedin.com/company/macro-ai-podcast/ Gary's Free AI Readiness Assessment: https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness Scott's Content & Blog https://www.macronomics.ai/blog

    21 min
  3. Privacy Engineers for AI: Protecting Data, Driving Trust

    6 OCT

    Privacy Engineers for AI: Protecting Data, Driving Trust

    Artificial Intelligence is moving fast—but privacy risks are moving just as quickly. In this episode of the Macro AI Podcast, Gary and Scott break down a role that’s quickly becoming indispensable: the Privacy Engineer for AI.  So what exactly is a privacy engineer? They’re the bridge between regulators and technologists. Their mission is to embed privacy by design into AI systems, turning complex laws like GDPR, HIPAA, California’s CPRA, and the EU AI Act into concrete technical safeguards. From minimizing sensitive data in training pipelines to stress-testing models for leaks, these engineers are the ones who make sure your AI is trustworthy, compliant, and resilient.  The timing could not be more urgent. The EU AI Act comes into full force in 2026, while in the U.S., the FTC is already forcing companies to delete models trained on tainted data. Without privacy engineers, businesses risk not just fines but also losing the very models they’ve invested millions in.  Gary and Scott dive into:  How privacy engineers protect the AI lifecycle—from data collection to model deployment. Why businesses of every size need this role, with different priorities for startups, mid-market firms, and global enterprises. The ROI story: Cisco research shows a nearly 2x return on privacy investments, driven by faster sales cycles and stronger customer trust. A practical roadmap for building privacy capacity—starting small with guardrails and scaling up to ISO 42001 certification readiness. And new in this episode: the talent pipeline challenge. Where do you find these people? The best privacy engineers often start as ML engineers, security professionals, or graduates of specialized programs like Carnegie Mellon’s Privacy Engineering track. But supply is thin, so forward-looking enterprises are upskilling internal talent, partnering with consultancies, and competing aggressively to hire the rare hybrid who can talk about both differential privacy and the NIST AI Risk Management Framework. The bottom line: Privacy Engineers for AI aren’t just compliance hires. They future-proof your AI investments, accelerate growth, and turn privacy into a strategic differentiator in an era where trust is the new currency.    Send a Text to the AI Guides on the show! About your AI Guides Gary Sloper https://www.linkedin.com/in/gsloper/ Scott Bryan https://www.linkedin.com/in/scottjbryan/ Macro AI Website: https://www.macroaipodcast.com/ Macro AI LinkedIn Page: https://www.linkedin.com/company/macro-ai-podcast/ Gary's Free AI Readiness Assessment: https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness Scott's Content & Blog https://www.macronomics.ai/blog

    17 min
  4. AI Workslop

    3 OCT

    AI Workslop

    Welcome to the Macro AI Podcast with Gary and Scott. In this episode, we dive into one of the newest and most important concepts hitting boardrooms and executive teams: AI Workslop.  AI Workslop describes polished, AI-generated work that looks good on the surface but lacks the substance, accuracy, or context to drive real decisions. It’s the long memo with no action, the glossy slide deck without insight, the email that shifts the burden onto the reader. And it’s not just annoying — it’s expensive.  Recent research from Harvard Business Review, BetterUp Labs, and Stanford found that:  40% of desk workers encountered AI Workslop in the last month. Each incident wasted nearly 2 hours. The hidden cost adds up to $186 per employee per month — over $9M annually for a 10,000-person company. Colleagues perceive Workslop senders as less creative, less capable, and less reliable. In this episode, Gary and Scott explore:  What AI Workslop is — and how it differs from AI hallucinations. Why it happens (old habits, new tools, and cultural pressure). How leaders can spot Workslop before it derails productivity. Why prompting skill matters — and why it’s not the full cure. The Anti-Workslop Playbook: leadership guardrails, workflow templates, training strategies, and metrics. Real-world examples of slop vs. substance in sales, operations, and contact centers. The single KPI executives should watch: time-to-decision. AI isn’t the problem. Workslop is. And leaders who build the right norms, culture, and skills will see ROI instead of sludge.    🔗 Resources mentioned in this episode:  Harvard Business Review article introducing “AI Workslop” (Sept 2025): https://hbr.org/2025/09/ai-workslop BetterUp Labs research and resources: https://www.betterup.com/resources/research/ai-workslop  Stanford Social Media Lab collaboration: https://sml.stanford.edu    Send a Text to the AI Guides on the show! About your AI Guides Gary Sloper https://www.linkedin.com/in/gsloper/ Scott Bryan https://www.linkedin.com/in/scottjbryan/ Macro AI Website: https://www.macroaipodcast.com/ Macro AI LinkedIn Page: https://www.linkedin.com/company/macro-ai-podcast/ Gary's Free AI Readiness Assessment: https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness Scott's Content & Blog https://www.macronomics.ai/blog

    22 min
  5. Michael Reid – CEO of Megaport

    26 SEPT

    Michael Reid – CEO of Megaport

    n this episode of The Macro AI Podcast, Gary and Scott sit down with Michael Reid, CEO of Megaport, to explore how network-as-a-service is reshaping the way enterprises connect to the cloud, scale their infrastructure, and prepare for an AI-driven future.  Michael shares his perspective on why agility and flexibility in connectivity are now strategic imperatives for CIOs, CTOs, and CFOs—and how Megaport is positioning itself at the heart of this transformation. We discuss the company’s recent global expansion, the impact of Project Centurion’s 400G backbone upgrade, and what enterprises need to think about as AI workloads demand more bandwidth, lower latency, and tighter integration across multiple clouds.  Listeners will hear insights on:  How enterprises can simplify multicloud strategies while maintaining performance and security. The role of software-defined networking in accelerating digital transformation. Why infrastructure investments like Project Centurion are foundational to AI adoption. Practical advice for decision-makers navigating the convergence of networking, cloud, and AI. Michael also highlights where Megaport is heading next, from enabling new AI-centric services to supporting the rapid evolution of edge computing. For executives thinking about how to future-proof their connectivity strategies, this episode delivers both strategic guidance and actionable insights.  Want more from Megaport? Don’t miss their own podcast, Uplink, where Michael and his team dive deeper into connectivity, cloud adoption, and the future of digital infrastructure. It’s the perfect complement to today’s conversation. You can listen here: https://www.megaport.com/uplink  If you enjoyed this episode, please subscribe to The Macro AI Podcast, share it with colleagues, and stay tuned for more conversations at the intersection of AI, infrastructure, and business transformation.    Send a Text to the AI Guides on the show! About your AI Guides Gary Sloper https://www.linkedin.com/in/gsloper/ Scott Bryan https://www.linkedin.com/in/scottjbryan/ Macro AI Website: https://www.macroaipodcast.com/ Macro AI LinkedIn Page: https://www.linkedin.com/company/macro-ai-podcast/ Gary's Free AI Readiness Assessment: https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness Scott's Content & Blog https://www.macronomics.ai/blog

    33 min
  6. The Future of Customer Experience in the AI Era

    22 SEPT

    The Future of Customer Experience in the AI Era

    Customer Experience (CX) is undergoing the biggest transformation in decades, powered by AI and accelerated by the shift to Contact Center as a Service (CCaaS). In this episode of The Macro AI Podcast, Gary and Scott break down where CCaaS is today, how AI is reshaping the landscape, and what business leaders need to do to prepare for the next ten years.  We start with the basics: what CCaaS actually is, why it matters, and who the leading players are — from established platforms like Five9, NICE, Genesys, and Avaya to innovators such as Verint, Talkdesk, 8x8, Microsoft, Zoom, eGain, and Observe.AI. This sets the stage for sourcing decisions and gives listeners a realistic view of the vendor ecosystem.  From there, we dive into where CX stands today. Companies have chatbots, transcription tools, and AI-driven coaching — but most of it is fragmented. The real future is orchestration: AI systems that not only interact with customers but orchestrate workflows across humans, machines, and enterprise systems.  Looking ahead, Gary and Scott explore four insights executives may not have considered:  Contact centers as insight engines — mining every customer interaction for churn risk, product feedback, and revenue opportunities. A shift in the economic model — from cost-per-seat to outcome-based pricing tied to resolution, containment, or customer satisfaction. Regulatory blind spots — how compliance, transparency, and trust will define CX success as much as speed and efficiency. The organizational shift — why CX won’t remain a siloed department but will evolve into an enterprise-wide orchestration function. The episode also highlights the role of independent AI consultants in bridging the gap between technology and business outcomes. From assessing data readiness and designing orchestration fabrics to implementing governance frameworks, consultants help companies avoid vendor lock-in and align AI to their unique business models.  For CIOs, COOs, and CEOs, the message is clear: the companies that start building AI fluency and governance now will be the ones delivering tomorrow’s customer experience. The future of CX is not just faster service — it’s intelligent, predictive, and woven into the fabric of the entire enterprise.      Send a Text to the AI Guides on the show! About your AI Guides Gary Sloper https://www.linkedin.com/in/gsloper/ Scott Bryan https://www.linkedin.com/in/scottjbryan/ Macro AI Website: https://www.macroaipodcast.com/ Macro AI LinkedIn Page: https://www.linkedin.com/company/macro-ai-podcast/ Gary's Free AI Readiness Assessment: https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness Scott's Content & Blog https://www.macronomics.ai/blog

    23 min
  7. Mastering AI Prompts

    12 SEPT

    Mastering AI Prompts

    In this episode of The MacroAI Podcast, Gary and Scott take a deep dive into one of the most overlooked yet mission-critical concepts in artificial intelligence: robustness.  What does it mean for an AI system to be robust? In simple terms, it’s the ability to keep performing under stress — when the data is messy, unexpected, or even deliberately manipulated. Without robustness, AI that looks flawless in a demo can fail spectacularly in production, creating business risks instead of business value.  Gary and Scott break it all down for business leaders, connecting technical concepts to practical outcomes. You’ll learn:  Why accuracy is not enough — accuracy is practice, robustness is game day. Real-world examples of AI failures across healthcare, finance, retail, and even autonomous vehicles. How organizations can build robustness into their AI systems through diverse data, stress testing, fallback mechanisms, and advanced methods like adversarial training and ensembles. Ways to measure robustness, from stress-test error rates to cross-domain testing and robustness curves. The growing role of third-party robustness testing, which is quickly becoming the AI equivalent of cybersecurity penetration testing. The high cost of ignoring robustness — from financial losses to reputational damage. Why future enterprise AI will require independent certifications, insurance validation, and proof of resilience to win trust. For executives, the message is clear: robustness equals trust. If you can’t trust your AI under pressure, you can’t scale it. Robustness is no longer a technical “nice-to-have” — it’s a business differentiator, a regulatory expectation, and the foundation for long-term AI success.  Whether you’re a CEO, CIO, CFO, or a technical leader building AI systems, this episode will give you the insights, analogies, and practical takeaways to put robustness at the center of your AI strategy.  Key soundbites:  “AI without robustness is like a self-driving car that only works in the sunshine.” “Accuracy is practice. Robustness is game day.” “Third-party robustness testing will soon be as common as penetration testing.” Good Reference Article:  Machine Learning Robustness A Primer  Tune in and learn how to future-proof your AI investments.      Send a Text to the AI Guides on the show! About your AI Guides Gary Sloper https://www.linkedin.com/in/gsloper/ Scott Bryan https://www.linkedin.com/in/scottjbryan/ Macro AI Website: https://www.macroaipodcast.com/ Macro AI LinkedIn Page: https://www.linkedin.com/company/macro-ai-podcast/ Gary's Free AI Readiness Assessment: https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness Scott's Content & Blog https://www.macronomics.ai/blog

    20 min
  8. AI Robustness Explained: How Business Leaders Can Build Trustworthy and Resilient Systems

    8 SEPT

    AI Robustness Explained: How Business Leaders Can Build Trustworthy and Resilient Systems

    In this episode of The MacroAI Podcast, Gary and Scott take a deep dive into one of the most overlooked yet mission-critical concepts in artificial intelligence: robustness.  What does it mean for an AI system to be robust? In simple terms, it’s the ability to keep performing under stress — when the data is messy, unexpected, or even deliberately manipulated. Without robustness, AI that looks flawless in a demo can fail spectacularly in production, creating business risks instead of business value.  Gary and Scott break it all down for business leaders, connecting technical concepts to practical outcomes. You’ll learn:  Why accuracy is not enough — accuracy is practice, robustness is game day. Real-world examples of AI failures across healthcare, finance, retail, and even autonomous vehicles. How organizations can build robustness into their AI systems through diverse data, stress testing, fallback mechanisms, and advanced methods like adversarial training and ensembles. Ways to measure robustness, from stress-test error rates to cross-domain testing and robustness curves. The growing role of third-party robustness testing, which is quickly becoming the AI equivalent of cybersecurity penetration testing. The high cost of ignoring robustness — from financial losses to reputational damage. Why future enterprise AI will require independent certifications, insurance validation, and proof of resilience to win trust. For executives, the message is clear: robustness equals trust. If you can’t trust your AI under pressure, you can’t scale it. Robustness is no longer a technical “nice-to-have” — it’s a business differentiator, a regulatory expectation, and the foundation for long-term AI success.  Whether you’re a CEO, CIO, CFO, or a technical leader building AI systems, this episode will give you the insights, analogies, and practical takeaways to put robustness at the center of your AI strategy.  Key soundbites:  “AI without robustness is like a self-driving car that only works in the sunshine.” “Accuracy is practice. Robustness is game day.” “Third-party robustness testing will soon be as common as penetration testing.” Good Reference Article:  Machine Learning Robustness A Primer  Tune in and learn how to future-proof your AI investments.  Send a Text to the AI Guides on the show! About your AI Guides Gary Sloper https://www.linkedin.com/in/gsloper/ Scott Bryan https://www.linkedin.com/in/scottjbryan/ Macro AI Website: https://www.macroaipodcast.com/ Macro AI LinkedIn Page: https://www.linkedin.com/company/macro-ai-podcast/ Gary's Free AI Readiness Assessment: https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness Scott's Content & Blog https://www.macronomics.ai/blog

    17 min
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Welcome to "The Macro AI Podcast" - we are your guides through the transformative world of artificial intelligence.     In each episode - we'll explore how AI is reshaping the business landscape, from startups to Fortune 500 companies. Whether you're a seasoned executive, an entrepreneur, or just curious about how AI can supercharge your business, you'll discover actionable insights, hear from industry pioneers, service providers, and learn practical strategies to stay ahead of the curve.  

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  • Creator
    The AI Guides - Gary Sloper & Scott Bryan
  • Years Active
    2K
  • Episodes
    48
  • Rating
    Clean
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    © 2025 The Macro AI Podcast
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