Generative AI
What is generative AI?
Generative AI refers to AI technology—such as ChatGPT, Claude, and Gemini—that can create new content, including text, images, or other outputs, based on prompts and training data. Unlike traditional software that follows predetermined rules, generative AI models can produce original responses and artifacts tailored to user requests.
In product work, generative AI tools can assist with tasks like summarizing data, analyzing content, and serving as thought partners. However, they should augment rather than replace human thinking and discovery work with real customers.
How should product teams use generative AI?
The key is to use generative AI to enhance human capabilities, not replace them. Product teams can leverage these tools to summarize large datasets, challenge their thinking, and identify gaps in their research plans. For example, a team might use generative AI to review their interview questions and spot potential blind spots before conducting customer research.
However, teams should avoid using generative AI to replace fundamental discovery activities like customer interviews or to generate artifacts like opportunity solution trees without real customer data. The value of discovery comes from the learning process, not just the artifacts it produces.
Why does thoughtful use of generative AI matter?
While generative AI technology is rapidly evolving and can significantly enhance productivity, its effectiveness depends on how teams deploy it. When used appropriately, these tools can help teams work faster and think more critically. When misused as a replacement for human judgment and customer contact, they undermine the core purpose of product discovery: building products based on real customer needs and behaviors.
Learn more:
- Don't Use Generative AI to Replace Discovery with Real Humans
- AI-Generated Opportunity Solution Trees - All Things Product Podcast with Teresa Torres & Petra Wille
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