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AI & Strategy

AI Strategy vs. AI Features: Where Most Companies Get It Wrong

November 3, 20258 min readBy Ali Shafiei

Bolting a chatbot onto a legacy workflow is not an AI strategy. Here is the framework I use with executive teams.

Every board deck in 2025 had an 'AI initiatives' slide. Very few had an AI strategy. A feature answers 'what can the model do'; a strategy answers 'what structural advantage does this buy us in three years'.

The framework I bring into strategy sessions has three layers: data moat, workflow compression, and decision augmentation. Most companies stop at the first layer and call it done.

Data moat is necessary but not sufficient — proprietary data without a compressed workflow is just an expensive archive. Workflow compression is where AI actually removes headcount-hours, not headcount.

The final layer, decision augmentation, is the one executives underinvest in: giving humans better judgment, not just faster output. That is where the durable advantage lives.

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