Editor's Synopsis
Amanda Pratt and Melissa Valentine argue in Harvard Business Review that driving AI adoption requires more than prompt engineering or context engineering skills. While crafting effective inputs for large language models is useful, the real value emerges when employees learn to apply generative AI to improve their actual workflows. This demands capabilities like defining valuable problems, evaluating possible solutions, rapid experimentation, and sustainable integration of new practices into daily work—disciplines that are fundamentally core to product management.
The article reframes the AI skills gap not as a technical challenge but as an organizational one. Rather than focusing narrowly on how to talk to AI tools, teams should build the product management mindset needed to identify where AI creates genuine value, test solutions quickly, and embed changes into ongoing processes. This perspective shifts the conversation from tool proficiency to workflow transformation, suggesting that companies investing in product management competencies across their teams will see far greater returns from their AI investments.
