The Board in the Machine
Podcast
Mostly the audio edition of the writing: articles on AI, governance, and the boardroom, read and expanded for the road. New episodes monthly.
Browse the episodes (35)
Ontologies and Knowledge Graphs: Why Structure is the Next Data Frontier
17 minute · The audio edition of the article.
Episode notes
Ontologies and Knowledge Graphs: Why Structure is the Next Data Frontier
Quality tells the organisation whether data is reliable. Structure tells the machine what it means, and structure is where durable AI advantage is now decided.
Most organisations have made their data reliable. Far fewer have made it explain itself, and that distinction is becoming the one that separates organisations that can reason with AI from those that can only retrieve with it.
In this episode of The Board in the Machine, Mario Thomas — Chartered Director and Fellow of the Institute of Directors — argues that the next frontier in creating durable AI value is structure: the ontologies and knowledge graphs that make the relationships between an organisation’s customers, contracts, suppliers, and decisions explicit enough for a machine to reason over rather than merely summarise.
Drawing on his own experience building an early knowledge graph from a regional newspaper archive in 1998, he shows why data quality and data structure answer two different questions, why the definitions encoded in a knowledge graph now carry the weight a chart of accounts has always carried, and why scalable proof under the FRC’s 2024 Code and the Data (Use and Access) Act 2025 depends on structure rather than quality.
This episode is for directors, chairs, and executives working out why their AI programmes stall, and what their data strategy assumes about structure. Read the full article at mariothomas.com
Read the article →AI and the Company Secretary: Operating the Boundary the Chair Polices
16 minute · The audio edition of the article.
Episode notes
AI and the Company Secretary: Operating the Boundary the Chair Polices
Board packs, agendas, and minutes now reach directors composed by systems the secretary cannot fully interrogate. The chair polices the boundary; the secretary operates it.
The information environment directors now use to make decisions is increasingly composed by AI systems whose framing decisions are not transparent. The company secretary is the only person with line of sight to the difference, and increasingly even the secretary cannot fully see it.
In this episode of The Board in the Machine, Mario Thomas — Chartered Director and Fellow of the Institute of Directors — examines how AI is remaking the company secretary’s role at the operational seam between board administration and the company’s disclosure obligations. He walks through four failure modes inside board administration, the personal exposure created by AI disclosure under the FRC Code and the EU AI Act, and the bifurcation between secretaries with genuine AI capability and those with only accumulated credentials.
The argument draws on the November 2024 GC100 minute-taking poll conducted with Norton Rose Fulbright, which found that 92% of 106 companies surveyed had not introduced AI to assist with minute-taking and 84% had no internal policy on its use; the McKinsey Global Board Survey 2024, which reported that 66% of directors say their boards have limited to no knowledge or experience with AI; PwC’s 2025 Annual Corporate Directors Survey; and the 2026 Protiviti and BoardProspects Global Board Governance Survey. Against that evidence the episode frames the secretary’s real choice through Mario’s Six Board Concerns and the constitutional principle Cadbury named in 1992 and the FRC’s 2024 Code carries forward.
This episode is for company secretaries, chairs, and non-executive directors working through the operational reality of AI governance under the FRC Code and the EU AI Act. Read the full article at mariothomas.com
Read the article →Ethical AI: When the Model Imposes Values Your Organisation Did Not Choose
15 minute · The audio edition of the article.
Episode notes
Ethical AI: When the Model Imposes Values Your Organisation Did Not Choose
A foundation model arrives with a value system its provider built and the Board did not choose. The decision: accept it, reject it, or build.
An AI model is in production somewhere in the organisation, handling a difficult decision: a customer complaint, a redundancy query, a medical underwriter reviewing a claim. The model settles what to refuse, how much candour the moment can bear, where the customer’s interest gives way to the policy. It does this the same way each time, because the judgement was made long before the question arrived — not by the organisation running the model, but by the provider that built it, for a global product, before the organisation signed up to use it.
In this episode of The Board in the Machine, Mario Thomas — Chartered Director and Fellow of the Institute of Directors — examines the value system every foundation model carries into deployment, why the familiar controls only partly contain it, and the strategic choice a Board is left holding once it sees the problem clearly.
The argument draws on the 2026 arXiv paper “Alignment Drift in Multimodal LLMs”, which found large and persistent differences in how model families handle ethically sensitive questions; the 2025 withdrawal of a major model update after it became excessively agreeable; Stanford’s Foundation Model Transparency Index, which scored major providers at roughly 40 out of 100; and the disclosure obligations of the EU AI Act. Against that evidence the episode sets out the real decision — accept, reject, or build — and frames it through the Six Board Concerns, the AI Sovereignty Trilemma, and the discipline of Minimum Lovable Governance.
This episode is for Boards and directors who want to govern the ethics their AI runs deliberately, deployment by deployment, rather than inherit it by default. Read the full article at mariothomas.com
Read the article →The Headroom Argument: Why AI Efficiency Means More Compute, Not Less
12 minute · The audio edition of the article.
Episode notes
The Headroom Argument: Why AI Efficiency Means More Compute, Not Less
Architectural efficiency expands AI compute demand rather than reducing it. Three forces converge on more inference. Boards should read efficiency news as capability, not cost.
A new AI architecture lands on 5 May. Subquadratic launches SubQ: a 12-million-token context window on a sub-quadratic sparse-attention architecture that reduces attention compute by roughly 1,000 times at full context. The interesting question is not whether AI is about to get cheaper. It is what efficiency news actually says about compute demand. The day after SubQ launched, Anthropic announced a partnership at SpaceX’s Colossus 1 facility adding more than 300MW of new capacity and over 220,000 NVIDIA GPUs. Both kinds of news end in the same place: more inference, not less.
In this episode of The Board in the Machine, Mario Thomas — Chartered Director and Fellow of the Institute of Directors — examines why architectural efficiency expands AI compute demand rather than reducing it. The episode walks through the three forces that drive demand faster than per-unit cost falls, why every prior era of computing tells the same story, and how Boards should read efficiency news to fund the right opportunity rather than the wrong budget.
The argument draws on the SubQ launch, the Anthropic-SpaceX Colossus 1 partnership, Mozilla’s disclosure that Anthropic’s Claude Mythos Preview identified twelve times as many Firefox vulnerabilities as Claude Opus 4.6 had found earlier in the year, Goldman Sachs’ Powering the AI Era, Deloitte’s TMT Predictions 2026, and Jevons’ nineteenth-century observation that improving the efficiency of a resource raises its total consumption rather than lowering it. The takeaway is operational: the Six Board Concerns, AI Stages of Adoption, and the AI Sovereignty Trilemma frame the question, and Minimum Lovable Governance answers the design question that follows when cheaper inference accelerates probabilistic decision-making into the regulated decision space.
This episode is for Boards and directors revisiting AI strategy in light of efficiency announcements and capacity commitments, and who want a capability-first framing rather than a budget-first one. Read the full article at mariothomas.com
Read the article →The Reasoning Gap: The Capability the Law Now Demands of Boards
12 minute · The audio edition of the article.
Episode notes
The Reasoning Gap: The Capability the Law Now Demands of Boards
UK law now requires four safeguards for solely automated decisions. Most Boards have approved probabilistic systems that cannot deliver them in operation.
A short statutory instrument lands on 12 May. It directs the Information Commissioner to prepare a statutory code on AI and automated decision-making. The interesting question is not what the code will say. It is what the law already requires. Since 5 February, UK law has required four safeguards for any significant decision taken solely by automated processing - information, representations, human intervention, and the right to contest.
In this episode of The Board in the Machine, Mario Thomas — Chartered Director and Fellow of the Institute of Directors — examines the capability gap that sits between those four safeguards and the systems most Boards have already approved. The episode walks through what the law actually asks for, why rule-based systems carry that capability on the surface and probabilistic systems do not, and where the gap will surface first when the first significant decision is contested.
The argument draws on the Data (Use and Access) Act 2025, the new Articles 22A to 22D of the UK GDPR, the CJEU’s SCHUFA judgment, the WP29 guidelines on automated decision-making and profiling endorsed by the EDPB, the IoD’s AI Governance in the Boardroom (2025), and practitioner analyses from Travers Smith, Bird & Bird, Debevoise, and Alston & Bird. The takeaway is operational: Minimum Lovable Governance is the operating principle through which a duty like this one actually gets delivered, and the Board’s job is not to build the capability but to refuse to approve systems that cannot deliver it.
This episode is for Boards and directors in financial services, employment, insurance, and any consumer context where significant decisions are being made by automated processing, and who want a capability-first framing rather than a compliance checklist. Read the full article at mariothomas.com
Read the article →AI and the Chair: Governing the Board Through The Great Remaking
16 minute · The audio edition of the article.
Episode notes
AI and the Chair: Governing the Board Through The Great Remaking
Existing chair responsibilities now require different execution as AI remakes both the Board's own work and the work the Board governs.
Chairs remain accountable for the Board’s effectiveness. They are no longer fully in control of how decisions are being formed. AI is remaking both the Board’s own work and the work the Board governs at the same time.
In this episode of The Board in the Machine, Mario Thomas — Chartered Director and Fellow of the Institute of Directors — examines how AI has changed the execution of the chair’s existing responsibilities. The episode walks through the two states of the duality the chair now sits between: AI in the preparation of board materials, and AI in the operations of the business the Board governs. Listeners will come away with a sharper view of where collective accountability is most at risk in their own boardroom, and what the chair’s existing responsibilities now require to keep it intact.
The argument draws on the Cadbury Report of 1992, the FRC’s 2024 UK Corporate Governance Code, the IoD’s NEDs Reimagined Commission of January 2026, and the 2026 Global Board Governance Survey from Protiviti and BoardProspects. The takeaway is operational: a chair who can name where the boundaries of agency and accountability are silently moving in their own boardroom is a chair who can hold them.
This episode is for chairs and senior independent directors operating in boards where AI has already entered both the preparation room and the operating environment, and who are looking for a constitutional framing rather than another tool list. Read the full article at mariothomas.com.
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