Engagement 03
AI Literacy for Executives
For executives who need to use AI without absorbing its confident wrong answers.
Frontier-aware AI literacy for the people making the decisions. Not prompt engineering. Not generic AI strategy. Specifically: where AI is trustworthy, where it isn't, and how to design decisions, teams, and governance around the boundary instead of hoping the boundary moves.
ExCo and board members who need a vocabulary that survives scrutiny.
CROs and CFOs sponsoring AI investments without an honest read on where the risk actually sits. Heads of strategy who need to absorb AI without letting it absorb the decision quality. Heads of People designing roles, hiring profiles, and team structures for an AI-altered workflow.
Less useful as a technical bootcamp. The curriculum assumes participants don't need to write code; they need to understand why a confident-sounding answer can still be wrong, and what to do about it inside their own decision rhythm.
What surfaces.
AI being adopted faster than governance and decision quality can absorb.
Executive conversations about AI that stall on definitions or drift into hype.
Decision flows where AI's confident wrong answers reach the human reviewer with more credibility than the right ones.
Pilots that succeed in demo and fail on production data because the failure mode wasn't named in advance.
"Should we use AI here" debates that have no shared framework for answering.
AI Literacy for Performance.
The named curriculum is AI Literacy for Performance — modular by audience and sector. Components selected and sequenced per engagement:
AI Literacy for Executives
Half-day or full-day workshop. Jargon-free, sector-relevant. Frontier mapping, decision risk, governance vocabulary. Designed for people who own the call, not the prompt.
AI Strategy for Banking & Insurance
Sector-specific frontier mapping. Where AML, credit risk, claims, and underwriting workflows sit relative to the AI frontier — and what that means for governance and capital.
The Anti-Overreliance Triad
Three disciplines: frontier-position awareness, disconfirming-signal authoring, anti-confirmation review. Hard skills, not soft principles.
AI-Augmented Decision Architecture
Designing decision flows where AI augments human judgment rather than replacing it. Where the human stays on the path. Where the human gets out of the way.
Agentic Workflow Design
For knowledge work: task decomposition, verification loops, routing. Beyond prompt engineering — into the shape of how the work actually gets done.
Governance briefing pack
Board-ready material: what your AI risk framework should answer, what it currently doesn't, and what to instrument before the next reporting cycle.
Modular. Common shapes:
Single executive workshop
Half-day or full-day for an ExCo, board sub-committee, or senior leadership team. Tailored to the sector and the live decisions on the table.
Sector-specific programme
Four to six sessions across two months. Anchored in the operating model and decision flows of a specific business line — usually credit, claims, or underwriting.
Anti-overreliance triad deployment
Three short sessions plus one decision-flow audit. Outcome: a named discipline running inside the executive cadence with explicit anti-confirmation checkpoints.
Agentic workflow co-design
Three to eight weeks. Working with a specific team to redesign one knowledge-work workflow around verification, routing, and reflexive checkpoints.
From "should we use AI" to "where is AI on the frontier for this decision."
Executive teams develop literacy in where AI is and isn't trustworthy, and structure their decisions accordingly. Decision flows acquire explicit checkpoints for catching confident-wrong outputs. Governance frameworks answer questions they currently don't. Pilots survive contact with production data because the failure modes were named in advance.