Technovation with Peter High (CIO, CTO, CDO, CXO Interviews)

Can trust be engineered into digital systems or is it purely cultural? In this episode of Technovation, Peter High speaks with Jimmy Wales, co-founder of Wikipedia and author of The Seven Rules of Trust, about designing platforms that scale without sacrificing integrity. From neutrality policies to radical transparency and human-in-the-loop AI governance, Wales shares how trust must be built, not assumed. Key highlights from the episode: Why trust operates at a human scale, even inside global platforms How incentives shape behavior, and why ad-driven models distort integrity Lessons from Airbnb’s early trust crisis Managing generative AI with human oversight Neutrality as a strategic discipline in polarized times

Is AI really eliminating jobs, or is it redefining skills? In this episode of Technovation, Peter High speaks with Ehren Powell, Chief Digital Officer of Marathon Petroleum Corporation, about leading digital transformation at one of America’s largest and most complex industrial enterprises. Powell shares how he is building a skills-first organization—decomposing roles, augmenting capabilities with AI, and reassembling work around differentiated processes. Key topics include: Why AI should be treated as a value multiplier—not a strategy How data contextualization unlocks massive sensor environments The creation of data domain ownership across the enterprise Applying edge technology and AI to improve safety and reliability Why curiosity and reinvention define the future workforce

You can’t scale AI on fragmented data. In this episode of Technovation, Peter High speaks with Ogi Redzic, Chief Digital Officer of Caterpillar, about the foundational platform transformation that made rapid AI innovation possible across a $65B industrial enterprise. Ogi shares how retiring legacy systems, consolidating data into the Helios cloud platform, and establishing trusted data pipelines enabled CAT Digital to launch an enterprise AI assistant in just 10 months. Key topics include: Building Helios to process millions of data pipelines daily Turning unplanned downtime into predictive maintenance at scale Scaling $5B in industrial e-commerce Partnering with NVIDIA on edge AI and digital twins Aligning digital teams to measurable business outcomes

In this episode of Technovation, Peter High speaks with Saam Motamedi, General Partner at Greylock Partners, about the evolving role of artificial intelligence within the enterprise technology stack. They discuss how venture capital approaches enterprise AI companies at an early stage, how large enterprises are evaluating changes to their technology stacks, and what implications AI may have for workforce dynamics. Saam shares perspectives on how AI may influence infrastructure decisions, application development, and software business models over time. Key insights include: Shifts in enterprise infrastructure strategy Usage- and outcome-based software economics The future of AI agents What large enterprises should understand about emerging AI startups

Is your AI strategy ready for scale or headed for failure? In this episode of Technovation, leaders from Norfolk Southern, McCormick & Company, and Vulcan Materials joined us at our Metis Strategy Summit to discuss what it really takes to move from AI pilots to enterprise impact. From AI factories and predictive transportation platforms to hybrid operating models and reward system redesign, this conversation dives into the operational and cultural realities of scaling AI in complex organizations. Key highlights: Why 2026 is shaping up as the “scale or fail” year for AI How to industrialize AI with data platforms and governance Embedding technologists in business functions for contextual impact The critical role of AI literacy and trust Aligning incentives to drive behavioral change

Innovation isn’t slowing down, but in many enterprises it’s becoming invisible. In this episode of Technovation, Peter High speaks with Sean Murphy, Founder and CEO of DemoHop, about why distributed work is trapping great ideas inside organizations and what CIOs can do to fix it. Sean explains how weak ties across enterprises have eroded, why peer-to-peer discovery beats status meetings, and how visibility is becoming the missing ingredient for scaling AI. Key topics include: Why innovation gets trapped in distributed organizations How science fair–style demo days reduce duplication The hidden role of weak ties in creativity and breakthrough Making enterprise AI work visible and scalable Building credibility for technology teams with business leaders

Innovation in healthcare doesn’t start with AI. It starts with operational stability. In this episode of Technovation, Peter High speaks with Chad Wasserman, CIO of HCA Healthcare, about leading technology at massive scale while keeping patient care at the center. Wasserman explains why “operational quiet” is the foundation that makes AI, data, and digital transformation possible and how HCA balances innovation with reliability across thousands of sites of care. Key topics include: Why stability is a prerequisite for innovationTreating IT as an extension of the care teamScaling AI responsibly in clinical and engineering domainsBuilding data platforms to support generational changeDeveloping technologists through deep business immersion

What if the real driver of digital disruption isn’t technology, but unit economics? In this episode of Technovation, Peter High speaks with Dan Gill, Chief Product Officer of Carvana, about how disciplined unit economics power one of the most ambitious e-commerce models in retail. Rather than leading with engineering for its own sake, Carvana focuses relentlessly on eliminating friction, capturing profit pools, and reinvesting those economics back into customer value. Key highlights from the episode: Vertical integration and competitive advantage Deterministic, self-service digital experiences Proprietary platforms vs. off-the-shelf tools AI-human collaboration at scale

How can early-stage investors deliver repeatable, outsized returns—without chasing hype? In this episode of Techoventure, Mark Fernandes, Managing Director at Sierra Ventures, shares the disciplined model behind one of the industry’s most consistent early-stage venture firms. Sierra’s strategy is designed for repeatable 3–5x returns by focusing on founder-market fit, tight portfolio construction, and tech-savvy sectors like AI, cloud, and cybersecurity. Key insights include: The four-part rubric Sierra uses to vet early-stage founders Why fund size discipline is critical to long-term VC performance How Sierra balances seed and Series A checks with portfolio theory The power of “AI enablers” in healthcare, legal, and vertical SaaS The 20-year evolution of Sierra’s CXO Board and its enterprise value

Is AI coming for your job—or just changing how you work? In this episode, Wall Street Journal technology columnist Christopher Mims shares a grounded, deeply informed perspective on how AI is reshaping productivity, creativity, jobs, and knowledge work. From the pitfalls of overhyping generative AI to the rise of agentic systems and the enduring role of classic AI, Christopher unpacks what leaders need to know now. He also highlights how experts benefit most from AI, what happens when organizations anchor too heavily on AI tools, and why handwritten notes, walking meetings, and skepticism are critical in the AI age. Key highlights from the episode:

How does a 100-year-old manufacturing leader reinvent itself through autonomy and AI? In this episode, Caterpillar CTO Jaime Mineart shares how her team is transforming industrial work sites using robotics, machine intelligence, and real-time data. From mining to construction, the company is applying decades of engineering expertise to modern digital challenges, partnering with customers to co-develop scalable automation solutions. Key highlights from the episode: How autonomy is expanding beyond mining into quarries and constructionWhat makes Caterpillar’s AI adoption strategy unique—and replicableInside the Helios platform and NVIDIA partnership powering data-driven insightsWhy the company pledged $100M to upskill the workforce of the futureLessons from scaling R&D with real-world customer involvement

1048: What if the hiring process wasn’t broken—but reimagined? Anthony Moisant, Chief Information Officer and Chief Security Officer at Indeed, details how his teams are building trusted systems, tackling AI bias, and leveraging background agents and AI sourcing to solve the “black hole” of hiring. He also reflects on the importance of early-career talent, skill-based hiring, and the balance of self-learning and leadership-led growth. The conversation covers:

1047: What does it take to lead tech—and the enterprise—in 2026? In this episode of Technovation, we feature a panel from our October 2025 Metis Strategy Summit where Steven Norton speaks with three top executive recruiters: Craig Stephenson (Korn Ferry), Jamey Cummings (JM Search), and Scott Robbin (Heidrick & Struggles). Throughout the conversation, each recruiter gives their perspective on the evolving mandate of the CIO. The conversation covers: The convergence of data, security, digital, and operations under the CIOHow talent strategy and succession planning are changingWhat makes a technology leader board-readyThe rise (and ambiguity) of the Chief AI OfficerOffshore workforce trends and leadership development

Enterprises aren’t failing at AI. They’re failing at data. Daniel Docter, Managing Director at Dell Technologies Capital, shares why the biggest barrier to enterprise AI isn’t models or talent—it’s the fractured, unstructured, and context-free data that most companies still struggle to harness. In this episode of Technovation, Daniel and Peter High explore: Why data context is critical to enabling enterprise reasoning How Redis and other startups are fixing the AI performance gap What Dell Technologies Capital looks for in early-stage enterprise AI How corporate VC has evolved into a founder-enabling force Why the next five years will reward enterprises that fix their data layer

Digitization was just the first step. True digital transformation in healthcare is only beginning. Dr. Michael Pfeffer, Chief Information and Digital Officer at Stanford Health Care, shares how he and his team are moving beyond electronic health records to deliver real-time, AI-powered care. From building ChatEHR, a secure, embedded LLM interface, to developing Stanford’s FIRM framework for responsible AI, Pfeffer provides a behind-the-scenes look at one of the nation’s most advanced digital health systems. In this episode, you’ll learn: Why “digitized” isn’t the same as “digital” How Stanford built the first integrated LLM in clinical workflows What makes healthcare AI safe, useful, and equitable Where AI adds real clinical value and where it doesn’t The vision behind precision health at scale

1045: AI is no longer a side experiment—it’s a core capability. But are your people, partnerships, and governance models ready for it? In this special Metis Strategy Summit panel episode, three seasoned technology leaders explore what it really takes to build trust, scale talent, and lead responsibly in the age of AI: Paul Ballew, Chief Data & Analytics Officer, National Football League Lakshman Nathan, EVP & CIO, Paramount Mark Sherwood, EVP & CIO, Wolters Kluwer Moderated by Peter High, the conversation dives into transformation through the lens of distributed governance, workforce readiness, and the human element behind every AI ambition. Key themes from the panel include: How the NFL’s “One-to-One” fan engagement model blends personalization and privacy What happens when $2B in savings depends on department-level AI strategy (Paramount) Why “value realization” starts with your CFO and ends with trust (Wolters Kluwer) The limits of centralization—and why distributed innovation may win out How to balance Copilot rollouts with responsible AI guardrails

What happens when a former startup CEO brings performance management discipline into city government? In this episode of Technovation, Peter High speaks with San José Mayor Matt Mahan about applying data-driven decision-making, KPIs, and accountability—practices familiar to tech leaders—to the public sector. Drawing from his experience running venture-backed startups, Mahan explains how focus, measurement, and feedback loops are reshaping how City Hall operates. Key topics include: Applying startup-style performance management to governmentUsing dashboards and metrics to improve accountabilityPrioritizing outcomes over activityLeveraging AI to improve city services at scaleBuilding a workforce ready to use new technology responsibly

How do you build and scale digital innovation inside a 170-year-old company? Luke Gebb, EVP of Global Innovation at American Express, joins Peter High to share how Amex Digital Labs brings emerging technologies to market through a disciplined stage-gate process. Gebb outlines how his team incubates and graduates products that become core to Amex’s customer experience—from peer-to-peer payments to blockchain-based travel rewards. He also shares lessons in navigating cross-functional execution, partnering with big tech, and launching products customers actually use. Key topics include: Amex’s stage-gate innovation modelScaling peer-to-peer payments via PayPal/VenmoBuilding customer-centric discovery tools with GenAIPassport: Using NFTs to enhance travel experienceCollaborating across engineering, legal, and compliance

AI can’t fix what the healthcare system fundamentally gets wrong. In this episode, Liam Donohue, Co-Founder and Managing Partner at 406 Ventures, shares why his firm is betting on value-based care—and why AI risks breaking the system if applied to the wrong incentives. From launching EdTech’s earliest funds to shaping 406 Ventures’ sector focus in healthcare, cybersecurity, and infrastructure, Liam offers hard-won lessons in disciplined investing, operator-first teams, and systemic transformation. Key highlights: Why fee-for-service economics undermine care innovation How value-based care reshapes both incentives and outcomes The real reason AI is booming in revenue cycle management Lessons from WelbeHealth: rethinking elder care and payments Liam’s take on what makes a founder truly backable

What if AI is repeating the same mistakes society made during the Industrial Revolution? In this episode of Technovation, Peter is joined by Nobel Prize Laureate in Economics and Ronald A. Kurtz Professor of Entrepreneurship at the MIT Sloan School of Management Simon Johnson. Throughout their conversation, they explore why automation has historically failed to deliver shared prosperity and why artificial intelligence may be following the same path. Drawing on centuries of economic history, Johnson explains how mechanization once displaced workers faster than new jobs were created, fueling inequality and social unrest. Together, they discuss what today’s AI leaders must learn from history, why institutions matter more than technology alone, and how workforce anxiety is an early warning sign of deeper structural problems. Key topics include: Automation vs. job creationAI’s impact on entry-level and knowledge workWorkforce polarization and regional inequalityLessons from the Industrial Revolution for today’s leadersWhat it takes to align innovation with shared prosperity