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AI leadership course
AI training for executives, because accountability does not delegate
Practical AI training for executives and boards, run as an AI leadership course on strategy, risk, vendor questions and the oversight that stays with you.
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AI handles0
A person decides0
Large UK firms (250+) using AI0%Against 28% of firms with 0 to 9 staff.
Source: Office for National Statistics ↗Where the line sits
Leaders set the rules that everyone else follows
AI decisions made in the boardroom shape how safely it is used on the shop floor.
Yet many senior leaders are asked to approve AI spend and AI risk without a clear picture of either.
Our AI training for executives and senior leaders fixes that in plain language, without turning directors into engineers.
We focus on the decisions only leaders can make: where AI fits the strategy, how much risk to accept and who is accountable when it goes wrong.
Sessions work for full boards, executive teams or a mix of executives and non-executives.
Where you need ongoing senior AI leadership rather than a course, see our fractional Chief AI Officer service.
What AI can take off a leader’s desk
- Briefing packs and summaries of long reports
- First-pass comparison of vendor proposals
- Draft policies and scenario write-ups
- Keeping an AI use-case register up to date
What stays with the board
- Strategy and where AI fits in it
- Risk appetite and approval of high-risk uses
- Named accountability for each AI system
- Challenging management and vendors
- Stopping a system that is causing harm
Directors’ duties
AI training for executives starts with duties you already have
There is no special AI duty for UK directors, but the existing ones still apply.
Under section 174 of the Companies Act 2006, a director must exercise reasonable care, skill and diligence.
Approving an AI system you do not understand, or never asking how it is checked, sits uneasily with that standard.
The Institute of Directors says AI is now a strategic, operational and legal priority for every board.
Its board paper sets out 12 principles, from auditing AI use to embedding accountability and ethical oversight.
Our AI training for executives uses that kind of framework to give your board a shared language and a short list of questions it will actually use.
85%
AI acts alone
130
65% of 200 tasks
Goes to a person
70
35% of 200 tasks
Illustrative batch with a typical confidence spread. Your real split comes from a pilot on your own work. Some decisions go to a person whatever the score.
What we cover
An AI leadership course built around real board decisions
We start with what current AI can and cannot do, using examples from your sector.
We then work through strategy: which processes to change first and what success would look like.
We cover risk, including data protection, bias, security and the EU AI Act if you sell into Europe.
We spend real time on human oversight, because that is where accountability is won or lost.
We also cover how to read AI performance claims, since accuracy in a demo rarely matches accuracy in live use.
For deeper work on controls, your risk and compliance leads can follow on with our AI governance course.
- Strategy: where AI fits and where it does not
- Risk appetite and which uses need board approval
- Accountability: a named owner for every system
- Oversight: what meaningful human review looks like
- AI training for board members, including non-executives
AI drafts
Check
Person decides
Learns
01 / 04
Vendors
What to ask vendors before you sign
Most AI risk arrives through procurement, not in-house builds.
Part of our AI training for executives is a short set of questions to put to any AI supplier.
Where does our data go, and is it used to train the vendor’s models?
How is accuracy tested, and what happens when the system is wrong?
Where are the human checkpoints, and can our people override or stop the system?
The EU AI Act’s human oversight article is a useful benchmark even for UK-only firms: people must be able to monitor, override and stop high-risk AI.
Most AI risk arrives through procurement, not in-house builds.
How it works
Four steps, one owner
Each system ships with a named person accountable for what it does.
01
01
Brief the board
We agree the questions your board is facing and the AI uses already live or planned.
02
02
Run the session
A focused session in person or remotely, using your own use cases and vendor proposals.
03
03
Agree the guardrails
Leaders leave with a draft risk appetite, approval thresholds and named owners.
04
04
Follow through
We help turn decisions into a policy, a use-case register and a reporting rhythm.
Questions
Asked and answered
Further reading
From the source
Institute of DirectorsAI Governance in the Boardroom: the essential governance questions ↗Twelve principles and board questions for governing AI.legislation.gov.ukCompanies Act 2006, section 174: duty to exercise reasonable care, skill and diligence ↗The director’s duty that AI oversight sits inside.Department for Science, Innovation and TechnologyIntroduction to AI assurance ↗The UK government’s primer on assuring AI systems.Information Commissioner’s OfficeHow do we ensure individual rights in our AI systems? ↗Why a rubber-stamp review is not meaningful human oversight.European Commission AI Act Service DeskEU AI Act, Article 14: Human oversight ↗High-risk AI must let people monitor, override and stop it.
Keep reading
Related pages
TrainingAI governance course →An AI governance course for the people who design the controlsConsultancyFractional chief AI officer →A fractional chief AI officer, accountable a few days a monthGovernanceAI assurance →AI assurance, with evidence a person can stand behindTrainingAI training for business →AI training for business, with people who know when to step in
Next step
Tell us the work. We’ll show you where the line goes.
A 30-minute call. We map one workflow, what the AI could take, and where a person must stay in the loop.