AI is quietly taking over strategic decisions and that’s a mistake. If strategy is going to stay human, then it has to stay messy, says Paul Armstrong

Automation used to mean invoices, scheduling and sorting PDFs. Now it means suggesting layoffs, flagging underperforming units, reshaping go-to-market strategy, and proposing M&A targets. AI isn’t just in the back office anymore, it’s creeping into boardrooms around the world, sometimes quietly, sometimes invisibly, starting to do the one thing it wasn’t supposed to: think.

Generative AI and large language models (LLMs) have moved beyond tactical support and are being trained on financials, market signals, competitive intelligence, ESG performance and internal strategy decks. Tools like Salesforce Einstein, Palantir Foundry, and Microsoft Copilot are already being embedded into executive workflows, surfacing recommendations that look less like analytics and more like direction.

McKinsey’s internal AI platform Lilli was one early case. Consultants use it to pull insights from tens of thousands of case studies, internal documents and industry data points. It doesn’t just summarise; it proposes answers. In client sessions, Lilli can now offer strategy recommendations, reducing the time required for discovery phases and even influencing the scope of consulting engagements.

At everyone’s favourite cardboard abuser, Amazon, AI plays a role in shaping logistics and infrastructure investment decisions. Palantir has claimed its models helped advise UK health officials on vaccine distribution strategy. JPMorgan is reportedly experimenting with AI tools to

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