Technovation with Peter High (CIO, CTO, CDO, CXO Interviews)
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Twice-weekly conversations with top executives and thought leaders at the intersection of business, technology, and innovation. Each episode of Technovation explores the technology trends that are transforming business, and the leaders driving digital change inside their organizations. Produced by Metis Strategy and hosted by firm President Peter High, Technovation is the premier podcast for IT and technology professionals with the largest collection of interviews with elite CIOs, CTOs, and CDOs.
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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 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
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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
Most enterprises aren’t struggling with AI because of technology. They’re struggling because they’re trying to scale pilots instead of platforms.
In this episode of Technovation, Peter High speaks with Atilla Tinic, CIO of Qualcomm, about how the company is moving beyond one-off AI use cases to build an enterprise AI platform designed for scale. Tinic explains why unified and validated data is essential for AI accuracy, how Qualcomm enables developers and business teams through a centralized AI marketplace, and why security must be embedded into AI architecture from day one.
Key topics include:
Why data governance is foundational to AI success
How Qualcomm structures AI as a reusable enterprise platform
The rise of AI agents and autonomous systems
Cybersecurity challenges introduced by AI and how AI helps defend against them
What does it actually take to move AI from experimentation to enterprise-wide impact?
In this episode of Technovation, Peter High speaks with Leigh-Ann Russell, Chief Information Officer and Global Head of Engineering at Bank of New York (BNY), about how one of the world’s most systemically important financial institutions is operationalizing AI at scale. Leigh-Ann shares how BNY trained 99% of its 50,000-person workforce on AI, moved beyond pilots into deep enablement, and empowered employees across technical and non-technical roles to build AI agents that drive real productivity gains.
Key topics discussed include:
Training nearly the entire workforce to become AI-literate
Moving from AI pilots to enterprise-wide enablement
Empowering employees to build and deploy AI agents
Reducing cognitive load while improving speed and resilience
Leading AI adoption through hands-on executive behavior
What if the key to enterprise AI wasn’t a tool, but a mindset?
Mark Bloom, Global CIO at AJ Gallagher, joins Technovation to share how the 70,000-person insurance giant is scaling AI by leading with data quality and cultural alignment—not flashy tools.
In this episode, Bloom details:
How Gallagher eliminated 800+ data silos to centralize insight and enable AI
Why crowdsourcing use cases from employees unlocked adoption at scale
The shift from efficiency gains to revenue-focused AI
How culture helped overcome resistance to data consolidation
His dual perspective as both CIO and board member
What really drives cybersecurity investment and why is “threat” often the last reason?
In this episode, Rakesh Loonkar, co-founder of Transmit Security and general partner at Picture Capital, shares a contrarian take on how cybersecurity product categories emerge and why compliance and platform shifts often matter more than actual threats. Drawing on decades of experience as both operator and investor, Rakesh explains how he evaluates risk timing, founder mindset, and market inflection points.
Key highlights from the episode:
Why most cyber spend starts with compliance, not attacks
How to invest ahead of platform shifts like AI and cloud
A three-part model for understanding cyber spending behavior
The risks of financial-only boards in technical startups
Lessons from building Trusteer, Transmit, and Picture Capital
What if your AI strategy is your business strategy?
In this episode, three top tech leaders share how they’re embedding AI not as a standalone initiative, but as a lever for enterprise transformation.
Mojgan Lefebvre (Travelers), Pawan Verma (Cencora), and Glenn Remoreras (Breakthru Beverage) reveal how they’ve partnered with boards, business units, and frontline teams to scale AI from proof of concept to performance.
Highlights include:
How Travelers reduced onboarding from 2 hours to 2 minutes
Cencora’s framework for board-level AI education
Breakthru’s use of summits to build AI literacy across leadership
The role of generative AI in operational redesign
Balancing experimentation with responsible governance
What does it really take to design for resilience in an AI-first world?
In this panel from the Metis Strategy Summit, Amtrak CDO Judith Apshago, GE Aerospace CIO David Burns, and Zoetis CDTO Keith Sarbaugh explore how resilient infrastructure is becoming the backbone of enterprise trust, uptime, and AI scalability.
Tune in to learn how these leaders are:
Responding to cloud outages and software disruption in real time
Building AI literacy, governance, and use-case portfolios at scale
Extending cyber defense and IT support to vulnerable supply chain partners
Using edge computing and sensors to enable predictive diagnostics
Converging IT and OT teams to enhance infrastructure intelligence
1036: What does it mean to manage a digital workforce?
In this episode of Technovation, we feature a panel from our most recent Metis Strategy Summit where three top executives explore how AI is reshaping work, both automating tasks, and changing the nature of management itself.
Peter High speaks with:
Jennifer Charters, Chief Information Officer at Lincoln Financial
Prasanna Gopalakrishnan, Chief Product & AI Officer at ADP
Daniel Marcu, Global Head of AI Engineering at Goldman Sachs
Together, they discuss:
Why AI agents require new thinking about team structure and oversight
How CIOs and CHROs must partner to build enterprise AI fluency
The risks of shadow AI and the need for secure platforms
How habit loops and performance incentives impact AI adoption
What it takes to balance innovation speed with organizational readiness
Our broadcast today features a panel from our most recent Metis Strategy Summit on the topic of Delivering the Product Operating Model (and Mindset) at Scale.
In this panel episode, we explore the limits and lessons of scaling the product operating model. Sal Companieh (Cushman & Wakefield), Jim Fowler (Nationwide), and Diane Schwarz (Smurfit WestRock) reflect on where product thinking thrives and where it breaks down.
Here are 5 takeaways from their candid discussion:
Why “readiness” must come before model
The risks of forcing product teams into fragmented structures
When to co-create with business leaders—and when to slow down
How agile funding models can clash with CapEx culture
What to do when the organization “doesn’t want the service”
What if the most defensible companies of the AI era aren’t the ones building the infrastructure—but the ones using it to rethink workflows?
In this Technoventure episode, Peter High speaks with Jamie Montgomery, Founder and Managing Partner of March Capital, about why the firm is investing heavily in the AI application layer—not chips, not clouds, but the companies delivering real task-based outcomes.
Key topics explored:
Why workflow-based moats beat data moats in the new venture cycle
How application-layer companies are scaling faster with leaner GTM
The ripple effects of AI CapEx on the U.S. economy and tax base
March Capital’s bets on open-source LLMs and scientific discovery
Why Montgomery believes AI “bailed out” the U.S. and VC industry alike
What’s stopping AI from scaling across the enterprise? For Madhu Ramamurthy, CIO of Zurich North America, it’s not the technology. It’s the culture.
In this episode, Madhu shares how he’s navigating the paradox of AI: a tool with unprecedented potential, surrounded by institutional resistance, unclear regulations, and cultural misalignment. He outlines Zurich’s approach to responsible AI deployment, organizational change, and ethical tech use.
Key highlights include:
How “organizational antibodies” can kill innovation before it scales
The case for explainability and governance in AI development
Why domain expertise is more valuable than tech fluency
Building AI-native teams outside of legacy systems
Madhu’s warning on digital flattery and sycophantic AI
What does it really take to scale AI across a global enterprise?
In this episode, Jaime Montemayor, Chief Digital and Technology Officer at General Mills, shares the AI playbook behind the company’s digital transformation from foundational investments in cloud and data governance to business-led innovation across supply chain, e-commerce, and marketing.
With 96% of General Mills’ supply chain data now clean and governed, Jaime’s team is shifting from predictive analytics to agentic architectures that enable scalable, AI-powered automation.
Key insights include:
Why cloud migration came before ERP modernization
How trust and business integration drive AI adoption
Building a connected data foundation to serve every segment
Agentic AI use cases in supply chain and marketing
Org design strategies to “lift and shift” innovation at scale
What does it take to transform IT from a bottleneck into a business accelerator?
In this episode, Waco Bankston, Chief Information Officer at NiSource, shares how he’s repositioning the IT organization to support growth, enable speed, and shift decades of technical and cultural inertia. Leading a 6.5-year enterprise transformation effort, Waco discusses the discipline required to modernize legacy systems while instilling a new execution culture.
Key insights from the episode include:
Building a modern tech foundation to support future acquisitions
Restructuring outsourced/insourced IT mix through platform consolidation
Shaping team behavior through leadership-by-experience
Establishing unified governance across AI, cybersecurity, and innovation
Leading with operational safety and customer-back design
What does it take to reimagine a 10,000-employee enterprise for a digital-first future?
In this episode, Unum CTO Gautam Roy breaks down how he transformed the company’s operating model, culture, and technology foundation by reshaping experiences from the customer backward.
Gautam shares how Unum evolved from applications to journeys to value streams; how AI, data, and automation have become levers for acceleration; and how innovation culture and continuous learning drive enterprise adaptability.
Highlights:
Unum’s shift to digital-first architecture and “moments that matter”
How AI, data, and automation remove friction across operations
Building predictive, proactive technology employee experience
Creating safe spaces and recognition models for innovation
Developing a future-focused, cross-functional learning culture
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