The next competitive advantage won’t come from “having AI,” but from orchestrating it, turning fragmented experiments into a governed, value-creating portfolio. That orchestration is the job of the AI Strategist: a leader who translates enterprise goals into an investable roadmap of AI products, embeds governance by design, and measures value with the same rigor as financial performance. Recent work on AI-enabled strategy underscores how AI reshapes the full strategy cycle - from sensing and simulation to resource reallocation - if leaders intentionally design for it.
What an AI Strategist really does
Portfolio architect, not use-case collector.
The strategist curates a balanced portfolio (efficiency, growth, risk), sets stage gates, and kills work that fails to clear value and risk thresholds. They prioritize decision flows, not demos.Translator at executive altitude.
Think of the “analytics translator” role, now elevated to enterprise scope. The strategist frames problems as decision hypotheses, specifies the minimum viable data/controls, and ensures solutions embed into operations.Governance by design.
Compliance cannot be bolted on. The strategist maps initiatives to the principles such as OECD AI Principles (human-centered, fair, transparent) and operationalizes it across the lifecycle.Operating-model engineer.
They align product, data, and platform teams; define ownership (who builds, runs, and signs off); and create an “action path” from signal, threshold, to action. Strategy is meaningless without an execution spine.Value and risk scorekeeper.
They instrument benefits (time saved, revenue lift, risk reduction) and decision latency improvements; they publish model lineage, data sources, and policy adherence alongside ROI.References
2. https://www.mckinsey.com/capabilities/quantumblack/our-insights/analytics-translator#/
https://oecd.ai/en/ai-principles
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