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

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