Integrating Generative AI: Questions to Answer for an Existing Product

Generative AI is a powerful hammer, but that does not make every product problem a nail. Before adding it to an existing product, product leaders should answer a few practical questions.

• Is there a real customer need that generative AI can satisfy better or faster?
• Is AI genuinely better than the available non-AI alternatives?
• Is the goal competitive parity, speed to market, learning, or a durable advantage?
• Do you have proprietary data that can create meaningful differentiation?
• How will customer data remain private and secure?
• Do the economics work at production scale?
• Are response time, consistency, and uptime acceptable for the use case?
• How damaging would a hallucination or incorrect answer be?
• What safeguards, reviews, or secondary checks are required?
• What measurable outcome will define success?

A prototype can make generative AI look easy. The harder and more valuable work is deciding whether it belongs in the product strategically, economically, and operationally. Start with the customer problem, make the tradeoffs explicit, and define success before investing heavily.

This recovered article has been condensed from the original.