A new framework for creating original ideas with AI
“Give me 20 headlines.” “Create 30 research questions.” “Generate 50 business ideas.”
Beneath these requests lies an intuitive assumption about large language models: that originality emerges automatically from quantity. If an AI can generate ideas faster than humans, then perhaps creativity becomes a problem of volume. Yet anyone who has brainstormed with ChatGPT or another LLM has quickly discovered the limitations of this approach. The outputs are often confident and polished, but also slightly repetitive and just off the mark. An important prompting challenge, then, is how to think with AI in ways that intelligently boost novelty. The paper “Ideation with Generative AI—in Consumer Research and Beyond,” published in the Journal of Consumer Research and co-written by HBS AI Institute Julian De Freitas, offers a new framework for understanding both what LLMs bring to brainstorming and where they fall short. The result is a practical roadmap for supercharging creativity.
Why This Matters
The authors explain that current LLMs excel primarily at producing incremental variations (“small ideas”) rather than paradigm-shifting breakthroughs (“big ideas”), so organizations that completely replace human-driven work with AI-generated output face an unseen ceiling on true innovation. Leaders and executives making decisions about product innovation, customer research, marketing strategy, or organizational change, should encourage their employees to use LLMs as configurable collaborators. The companies that benefit most will not simply produce more ideas, they’ll keep their employees engaged, test assumptions, and find real insights that merit investment.
Link to the HBS AI Institute Insight Article
Link to the Research Paper
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