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AI Strategy

AI strategy is where governance and ambition meet. These articles help leaders set priorities, manage the risk, and build a plan they can defend to a board.

All AI Strategy Posts (6)

Frequently asked questions

How should a board approach AI strategy?

Treat AI as both an opportunity and a governed risk: name who owns it at board level, decide where you'll use it and where you won't, and set the guardrails before teams build. The NIST AI RMF and ISO/IEC 42001 give boards a structure for oversight without needing deep technical detail. The failure mode is delegating AI entirely to engineering and only seeing it when something breaks.

How can Responsible AI be a competitive advantage rather than a cost?

Because trust is becoming a buying criterion: enterprise customers, regulated sectors and procurement teams increasingly ask how your AI is governed before they'll sign. Being able to show documented safety testing, bias audits and clear accountability wins deals that competitors relying on unchecked AI can't. Done well, governance shortens sales cycles instead of slowing delivery.

What AI risks should the C-suite worry about most?

The ones that reach the outside world: biased or unsafe decisions affecting customers, misleading AI-generated claims, data misuse under UK GDPR, and regulatory exposure under the EU AI Act for higher-risk uses. These carry legal, financial and reputational cost, and they usually trace back to a governance gap rather than a technical bug. The C-suite's job is to make sure ownership and controls exist before deployment, not after an incident.

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