AI Strategy Briefing for Executives
Executive teams, board members and the people who prepare papers for them
Prerequisites: None. Module 101 helps but is not required; this session is designed to stand alone.
Last verified 2026-09-17
Learning objectives
By the end, participants can:
- Describe what changed in the last eighteen months across the four assistants and why it matters for an ordinary organisation
- Set a ninety-day plan with three commitments the organisation can actually keep
- Take a defensible position on build versus buy and on capability versus tools
- State a risk posture that names the acceptable-use rules, the data terms and the regulatory floor
- Commission a measure of return that a finance director will accept
- Ask the board-level questions that separate an AI strategy from an AI budget
What's in this module
7 lessons · 5 exercises · ~8 min reading
Starts withWhat changed in the last eighteen months~2 minExecutive summary
You will learn what has changed in the assistants over the last eighteen months, what an organisation should do in the next ninety days, and how to frame build versus buy, capability versus tools, risk posture and return on investment so the board can decide rather than defer. End state is a one-page ninety-day plan for your organisation, a risk posture you can say out loud, and a list of questions you will ask at the next board meeting. After this module you can explain the shift from chat to agents in two sentences, choose a position on build versus buy for your context, commission the measures that show whether the money worked, and hold the people delivering it to account.
Sources
- European Commission, the regulatory framework for AI, the risk-based approach and the application timeline the board needs to know: https://digital-strategy.ec.europa.eu/en/policies/regulatory-framework-ai
- EU AI Act explorer, Article 4 (AI literacy), the duty that applies to every deployer today: https://artificialintelligenceact.eu/article/4/
- Anthropic, Claude pricing, an example of what a business tier now includes on a standalone assistant: https://claude.com/pricing
- OpenAI, Business data privacy, security and compliance, the no-training-by-default commitment and the admin controls on the business tiers: https://openai.com/business-data/
- Microsoft Learn, Data, privacy and security for Microsoft Copilot, the suite-assistant position on data, permissions and compliance: https://learn.microsoft.com/en-us/copilot/microsoft-365/microsoft-365-copilot-privacy
- Google Workspace, Generative AI in Google Workspace Privacy Hub, the same for Gemini: https://knowledge.workspace.google.com/admin/gemini/generative-ai-in-google-workspace-privacy-hub
Prefer the live room?
This module also runs inside our in-person bootcamps and workshops in Copenhagen.
Rolling this out across an organisation?
We run this material as executive briefings and team programmes, tailored to your stack, your data policies, and your pace.
More in Track I
Measuring AI Adoption
What the admin dashboards on all four assistants actually measure, how to take a time-saved baseline that survives a finance review, which quality signals to collect, and what good looks like at three, six and twelve months.
Gemini for Leaders
What a Gemini rollout across Workspace actually involves: which licences buy what, which switches the admin console has and what they default to, what Google commits to about your data, how adoption is measured with the reports you already have, what Google's own training and certification landscape offers, and how to sequence the first ninety days.
ChatGPT for Leaders
How to roll ChatGPT out across an organisation: which plan ({{fact:chatgpt_business_plans}}), what the workspace admin surface controls, where the data and training defaults sit, how to measure adoption with what OpenAI provides, what OpenAI's training and certification landscape offers your people, and a 90-day plan that survives contact with a real company.