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

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

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

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

Gary and Scott sat down with Sarah Craynon Zumbrum, Sr. Manager of Cloud Engineering with Oracle to discuss AI, careers and much more. She’s also a Gen AI Board member at Webber International University offering expert guidance to the faculty and students. Sarah's a wealth of knowledge as her team are on the forefront of AI as part of Oracle, one of the best tech companies in the world.

Sarah provides excellent insight into how organizations can begin their AI journey breaking down areas to focus including in some instances using CPUs over GPUs.

Have a listen and hear about Sarah’s journey in AI. Oh, and she’s an amazing Tri-athlete.

Sarah’s profile: https://www.linkedin.com/in/sczumbrum/

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

The Macro AI Podcast Episode: America’s AI Action Plan – A Summary

In this episode of The Macro AI Podcast, hosts Gary and Scott dive into America’s AI Action Plan, a July 2025 White House roadmap to secure U.S. leadership in the global AI race. This 28-page document outlines three pillars—Accelerating AI Innovation, Building AI Infrastructure, and Leading International AI Diplomacy—to drive economic growth, national security, and technological dominance.

Segment 1: Why It Matters
The plan positions AI as a catalyst for an industrial, information, and cultural renaissance, emphasizing that the nation with the largest AI ecosystem will set global standards.

Segment 2: Pillar I – Accelerating AI Innovation
The first pillar focuses on unleashing private-sector innovation by removing bureaucratic barriers, like rescinding Biden’s Executive Order 14110. Regulatory sandboxes and AI Centers of Excellence enable rapid testing of AI tools, especially in healthcare and energy. The plan promotes open-source AI models, ensuring startups can innovate without relying on big tech. Federal funding will enhance access to compute resources, and workforce initiatives, including tax-free AI training reimbursements, aim to upskill workers, complementing rather than replacing jobs.

Segment 3: Pillar II – Building AI Infrastructure
AI demands robust infrastructure—data centers, semiconductors, and energy. The plan streamlines permitting for data centers via NEPA exclusions and FAST-41 reforms, ensuring faster deployment. It addresses energy needs by stabilizing the U.S. grid and preventing power source decommissioning. The CHIPS Act bolsters domestic semiconductor production, reducing reliance on foreign supply chains. Cybersecurity is prioritized with secure-by-design AI and a skilled workforce trained for infrastructure roles.

Segment 4: Pillar III – International AI Diplomacy
This pillar aims to make American AI the global standard by exporting to allies and countering external influence in governance bodies. Strengthened export controls protect AI compute and chips, while biosecurity investments address risks in synthetic biology. The TAKE IT DOWN Act combats synthetic media, ensuring trust in AI.

Segment 5: Technical Deep Dive
For tech enthusiasts, the plan invests in AI interpretability via DARPA, enhancing trust in high-stakes applications like defense. NIST’s AI Evaluations Ecosystem standardizes reliability metrics, and secure compute environments at NSF and DOE protect sensitive data. Open-source support and hackathons foster innovation.

Segment 6: Practical Advice
Business leaders should join sandboxes, upskill teams with federal programs, secure AI stacks with U.S. tech, and align with American AI standards for global markets. Visit whitehouse.gov for the full plan. Tune in for actionable insights to le

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

Description: In this episode of The Macro AI Podcast, hosts Gary and Scott dive into the transformative world of AIoT (Artificial Intelligence of Things), where IoT’s connected devices meet AI’s analytical power to revolutionize industries. Aimed at business leaders and tech professionals, this episode unpacks AIoT’s mechanics, real-world applications, and future potential, offering practical insights to lead in the AI era.Gary and Scott explain AIoT’s symbiotic relationship: IoT sensors collect real-time data (e.g., factory vibrations, traffic patterns), while AI processes it to predict outcomes and automate decisions, creating a self-improving ecosystem. They explore the technical backbone—sensors, edge/cloud processing, and protocols like MQTT and CoAP—emphasizing open standards to avoid vendor lock-in. Real-world examples include Siemens’ predictive maintenance (20% fewer outages), Singapore’s traffic optimization (15% less congestion), and AIoT wearables reducing hospital readmissions by 25%. In agriculture, AIoT achieves 99% accuracy in crop disease detection, boosting yields.Looking to 2025–2035, they highlight trends like 6G’s terabit speeds, Federated Learning for privacy-preserving AI, and digital twins for virtual system modeling. Challenges include scalability, security (60% of IoT devices have vulnerabilities), and ethical risks like algorithmic bias. Leadership strategies focus on governance, upskilling, and aligning AIoT with business goals.Key Takeaways:

• Business Leaders: Start with a high-impact AIoT pilot (e.g., smart logistics) to drive ROI.
• Tech Teams: Prioritize secure, interoperable systems using MQTT/CoAP and robust data pipelines.
• Future-Proofing: Prepare for 6G and decentralized AI to stay competitive.

With a 2025 McKinsey report estimating AIoT’s $5 trillion GDP impact by 2030, Gary and Scott urge listeners to act now. Tune in for actionable advice and inspiring use cases to transform your business with AIoT!

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

In this episode of The Macro AI Podcast, hosts Gary and Scott explore the transformative impact of artificial intelligence on the global economy. They dive into how AI drives short-term disruption and long-term prosperity, drawing parallels to Schumpeter’s creative destruction. The discussion highlights AI’s task-specific focus, augmenting rather than replacing jobs, with studies suggesting only 4% of jobs are fully automatable while 46% of tasks could be AI-driven. Productivity gains are projected to add $7-13 trillion to global GDP by 2030, though adoption rates and labor dynamics will shape outcomes.The episode examines AI’s geopolitical implications, with the U.S. and China leading the race for dominance, while regions like India and the EU carve out niches. AI is reshaping trade, supply chains, and global alliances, creating both opportunities and challenges for businesses. Workforce transformation is another focus, with AI creating new roles and demanding skills like critical thinking and AI literacy. The hosts discuss reskilling solutions, including AI-driven training platforms and public-private partnerships.AI’s influence extends to monetary policy, potentially driving deflationary pressure and transforming financial instruments like dynamic bonds and micro-financing. Industries like logistics, healthcare, and finance are undergoing major shifts, with AI unlocking precision medicine and democratizing wealth management. Long-term, AI could redefine economies through decentralized autonomous organizations (DAOs), personalized education, and new governance models, raising questions about taxing AI-generated wealth.With a bullish outlook, Gary and Scott emphasize AI’s potential to amplify human potential and create abundance, urging business leaders to invest in skills, adaptability, and strategic innovation. Tune in for a deep dive into AI’s economic promise and challenges. Connect with the hosts on LinkedIn or at macroaipodcast.com.

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