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

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 government Using dashboards and metrics to improve accountability Prioritizing outcomes over activity Leveraging AI to improve city services at scale Building 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 model Scaling peer-to-peer payments via PayPal/Venmo Building customer-centric discovery tools with GenAI Passport: Using NFTs to enhance travel experience Collaborating across engineering, legal, and compliance ” Discount your AI ROI because mileage always varies Learn more

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 creation AI’s impact on entry-level and knowledge work Workforce polarization and regional inequality Lessons from the Industrial Revolution for today’s leaders What it takes to align innovation with shared prosperity