The Road to Accountable AI

Could a private insurance market play a significant role in compensating for AI-related harms and incentivizing companies to engage in more effective AI governance?

Phil Dawson of Armillla AI explains why AI insurance is emerging as a distinct product category, why traditional policies aren't effective at addressing AI risks, and what AI insurance actually covers. Dawson details Armilla's journey from AI testing platform assurance provider to, managing general agent for AI insurance policies, arguing that the company's AI audit experience gave it the risk data and evaluation capabilities needed to underwrite AI systems. A key turning point, he says, was realizing that as companies received reports showing how their models performed or underperformed, they became more concerned about risk, and insurance emerged as the next logical step to build trust.
Dawson identifies the absence of claims data as the central challenge for AI underwriting, which forces insurers to rely on proxy signals. He argues that policymakers can help by incentivizing transparency, disclosure, and third-party assessment. Drawing on lessons from cyber insurance, Dawson contends that risk-based pricing must be grounded in system-level governance evaluation. He also describes Armilla's partnership program, which connects insured companies with AI governance platforms, auditing firms, and certification bodies, ultimately driving improved AI governance maturity across the sector.
Philip Dawson is Head of AI Policy and Partnerships at Armilla AI, an MGA and Lloyd's cover holder that provides dedicated AI insurance products. A lawyer and public policy adviser, he has spent nearly a decade working on AI governance, including early involvement in the drafting of the OECD AI Principles and roles at Element AI, the United Nations, and the Harvard Kennedy School's Carr Center for Human Rights Policy.

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Ready or Not: The Impact of Artifician Intelligence on Insurance Risks (Armilla AI and Lockton, February 2026)
Armilla AI Raises Lloyd's-Backed Coverage to $25M as Traditional Insurers Retreat from AI Risk (Fintech Finance News, January 22, 2026) 
Gen AI Risks for Businesses: Exploring the Role for Insurance (Geneva Association, October 2, 2025)

Walter Haydock draws a direct line from military risk management to the enterprise AI challenge. His argues that organizations need to stop doing "math with colors," and move toward quantitative assessment that assigns dollar values to potential AI failures. Much of the conversation in this episode focuses on ISO 42001, the global standard for AI management systems, which Haydock has championed and which his own firm has gone through. He draws a three-part taxonomy of AI governance frameworks: legislation you either comply with or don't, voluntary self-attestable frameworks like the NIST AI RMF, and externally certifiable standards like ISO 42001 that bring independent verification.

Haydock outlines a forward-looking vision in which certification, insurance, and legal safe harbors reinforce one another. Machine-readable audit data will eventually allow insurers to make informed underwriting decisions about AI risk, reducing uncertainty for both enterprises and their customers.  Though, as he acknowledges, we are still far from that environment, with AI audits today still roughly 90% manual.
Walter Haydock is the founder of StackAware, which helps AI-powered companies manage security, compliance, and privacy risk. Before entering the private sector, he served as a reconnaissance and intelligence officer in the U.S. Marine Corps, as a professional staff member for the Homeland Security Committee of the U.S. House of Representatives, and as an analyst at the National Counterterrorism Center. He is a graduate of the United States Naval Academy, Georgetown University's School of Foreign Service, and Harvard Business School.
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Deploy Securely (Haydock's Substack)

Richa Kaul breaks down the AI risk landscape for enterprises, and argues that the key to managing all of them is resisting the urge to sensationalize. Kaul offers a candid assessment of where enterprise AI governance committees are falling short, noting that many  lack the technical fluency to ask vendors the right questions, such as where customer data goes, whether it trains other clients' models, and what specific steps reduce hallucination. She suggests that market-driven security standards like SOC-2 and ISO 27001 often matter more in practice than government regulation, creating a "beautiful ecosystem" where risk management runs ahead of the law. Looking forward, she addresses the growing challenge of agentic AI systems that make decisions autonomously, offering a deceptively simple prescription: Map every action an agent can take, know where your highest risk sits, identify the critical decision points, and demand human sign-off at each one/
Richa Kaul is the founder and CEO of Complyance, an AI-native enterprise governance, risk, and compliance (GRC) platform. Before founding Complyance, she was Chief Strategy Officer at ContractPodAi, a legal technology company, and previously served as Managing Director at the Virginia Economic Development Partnership and as a management consultant at McKinsey.
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Complyance Raises $20M to Help Companies Manage Risk and Compliance (TechCrunch, February 11, 2026)

How AI is, could, and shouldn't be used in military and other national security contexts is a topic of growing importance. Recent conflicts on the battlefield, and between the U.S. military and a major AI lab, are forcing conversations about legal, ethical, and appropriate business limitations for increasingly powerful AI tools. Michael Horowitz, a Political Science professor and Director of Perry World House at the University of Pennsylvania, is one of the world's leading experts on military AI and autonomous weapons. In this episode, drawing on his two stints in the U.S. Department of Defense, Horowitz walks through the major buckets of military AI use. He explains why militaries are, in some ways, more incentivized than any other institution to get AI governance right, but genuine tensions among speed, effectiveness, and meaningful human control can make responsible military AI difficult in practice. We cover Anthropic's recent dispute with the Pentagon as a case study in the fragile and increasingly consequential relationship between Silicon Valley and the defense establishment. 
Michael C. Horowitz is the Richard Perry Professor of Political Science and Director of Perry World House at the University of Pennsylvania, and a Senior Fellow for Technology and Innovation at the Council on Foreign Relations. From 2022 to 2024, he served as U.S. Deputy Assistant Secretary of Defense for Force Development and Emerging Capabilities, where he was the principal author of the U.S. Political Declaration on Responsible Military Use of AI and Autonomy. He is the author of The Diffusion of Military Power: Causes and Consequences for International Politics and co-author of Why Leaders Fight.
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Battles of Precise Mass: Technology Is Remaking War — and America Must Adapt (Foreign Affairs, 2024)
The Ethics & Morality of Robotic Warfare: Assessing the Debate over Autonomous Weapons (Daedalus, 2016)
Rules of Engagement (Penn Gazette, 2025)

Tanvi Singh draws on over two decades of building and governing AI systems inside global banks to make a provocative case: you cannot be accountable for decisions you do not control. Enterprises are consuming intelligence through models they don't own, can't explain, and didn't train. Singh reframes sovereignty beyond data center locations and infrastructure, to control across the entire stack, so that an organization's AI reflects its own values, laws, and culture. Whlile frontier LLMs will continue to dominate the consumer and retail market, she argues that domain-specific models will be important for enterprise and regulated use cases, offering better accuracy at dramatically lower cost. The conversation also touches on Singh's engagement with the Vatican's Pontifical Academy of Sciences around AI ethics, which has worked on benchmarks that reflect institutional values rather than defaulting to the cultural norms baked into large internet-trained models.
Tanvi Singh is the Co-Founder and CEO of Ekta Inc., a sovereign AI platform company building domain-specific foundation models for governments and regulated industries. She previously served as Group Head of AI, Data & Analytics at UBS and held senior technology leadership roles at Credit Suisse, GE, and Monsanto. She is the founder and managing partner of Nirmata-ai Ventures, a Zurich-based deep-tech venture fund, and serves as a board member of the Global Blockchain Business Council and GirlsCanCode. 

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Sovereign AI: Why States and Institutions Have to Take Back Their Digital Intelligence (HSToday, co-authored with Thomas Cellucci)
Ekta AI