Simon Torrance

Why organisations work with Simon Torrance

• He frames AI as a board-level operating model decision, with named categories of strategic, financial, operational and regulatory risk, rather than a technology selection exercise.
• He brings four working frameworks that executive teams can sit inside the same week: The Agentic AI Accelerator, The AI Maturity Model, The Agentic AI Enterprise Blueprint, and The Agentic AI Stack.
• The platform and ecosystem track record is real and named. He co-authored Fightback with Felix Staeritz, served on the World Economic Forum’s Digital Platforms and Ecosystems working group, and teaches the same material at Singularity University.
• His client work concentrates in financial services and insurance, with named corporate audiences including Allianz, AXA, Zurich Direct and Huawei, so insurance and banking boards do not have to translate his references.

Biography highlights

• Founder of AI Risk, a London-based strategy and innovation firm focused on the strategic deployment of agentic AI in large enterprises.
• Co-author of Fightback: How to Win in the Digital Economy with Platforms, Ventures and Entrepreneurs, with Felix Staeritz, LID Publishing.
• Member of World Economic Forum agenda councils, including the Digital Platforms and Ecosystems Working Group and the Accelerating Digital Transformation executive working group.
• Listed Expert at Singularity University on Digital Platforms and Ecosystems, Corporate Venture Building, and Embedded Finance and Insurance.
• Author of named industry frameworks including The Agentic AI Accelerator, The AI Maturity Model, The Agentic AI Enterprise Blueprint and The Agentic AI Stack.
• Keynote credits include the Financial Times Future of AI Summit, MIT Digital Economy Summit, Insurtech Insights and InsureNXT, plus internal events for Allianz and AXA.

Biography

The hard part of agentic AI is not building the agents. It is deciding what the firm will look like once they are running, and what the board is prepared to underwrite while that transition happens. Most leadership teams have not yet answered that question with the same discipline they apply to a major acquisition.

Simon Torrance built his firm AI Risk around exactly this gap. It advises boards in banking, insurance and TMT on the strategic, financial, operational and regulatory exposure created by AI adoption, and on how to redesign the operating model so the economics actually move. His frameworks, including The Agentic AI Accelerator, The AI Maturity Model, The Agentic AI Enterprise Blueprint and The Agentic AI Stack, give executive teams a shared structure for those conversations.

His authority on AI risk sits on top of two decades of work on business model transformation. He co-authored Fightback: How to Win in the Digital Economy with Platforms, Ventures and Entrepreneurs with Felix Staeritz, served on the World Economic Forum’s Digital Platforms and Ecosystems working group, and is a listed expert at Singularity University. The platform thesis, that incumbents must redesign their model rather than bolt on technology, is the same thesis applied to agents.

Boardroom audiences and conference platforms reflect that focus. Torrance has spoken at the Financial Times Future of AI Summit, MIT Digital Economy Summit, Insurtech Insights and InsureNXT, and runs closed sessions for firms including Allianz, AXA and Zurich Direct, where the conversation is less about AI as a topic and more about which decisions the board has to take in the next twelve months.

Key speaking topics

• Agentic AI in the enterprise
• AI risk and board governance
• Business model transformation
• Platform and ecosystem strategy
• Embedded finance and insurance
• Operating model redesign in financial services
• Corporate venture building

Ideal for

• Bank, insurer and asset manager boards weighing the next phase of AI investment.
• CEO, CSO and CDO leadership groups in financial services, insurance and TMT.
• Chief Risk and Chief Audit officers responsible for AI risk frameworks.
• Strategy and innovation leads running platform, ecosystem or corporate venturing programmes.

Audience outcomes

• A named taxonomy of AI risk that audiences can take into their own risk committee discussions.
• A clear distinction between AI pilots, AI productivity tooling, and an agentic operating model, with the implications of each for cost base and competitive position.
• A view of where platform and ecosystem economics intersect with agentic AI, and what that means for incumbents in regulated sectors.
• A short list of decisions a board should take within the next twelve months on talent, vendor exposure, and capital allocation toward AI.