Research: The Innovation Problems AI Can’t Solve

Generative AI can accelerate innovation, but the article argues that its default use often reinforces the human bottlenecks it is meant to solve. In ideation, models steer teams toward familiar ideas and make people more fixated on them. In screening, polished AI-generated pitches can be mistaken for better ideas, while AI recommendations may encode existing bias. In consumer research, simulated customers can speed testing but miss the irrational behaviors that shape real adoption. After launch, AI can summarize vast feedback, yet still help teams justify prior beliefs. The authors’ central advice is diagnostic: before applying AI, leaders should ask whether the bottleneck is informational, judgment-based, or incentive-driven, and preserve direct contact with customers where it matters most for grounding.

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