Unlike traditional product management that relies on existing user data, building next-generation AI products often lacks historical data. In this ambiguous environment, the ability to craft a compelling narrative becomes more critical for gaining buy-in and momentum than purely data-driven analysis.

Hiding the use of AI to create product artifacts is a mistake born from insecurity. Google AI PM Marily Nika advises PMs to be transparent, even sharing their custom PRD generators. This normalizes AI usage and reframes the PM as an efficiency leader, as those who don't adopt these tools will be left behind.

The skill of storytelling isn't just for marketing or user narratives. Its most powerful application in product management is internal: convincing diverse stakeholders and team members to rally behind solving a specific problem. It's a tool for alignment and motivation before a single feature is built.

A technical AI background isn't required to be a PM in the AI space. The critical need is for leaders who can translate powerful AI models into tangible, human-centric value for end users. Your expertise in customer behavior and problem-solving is often more valuable than model-building skills.

The most effective way to improve a PM's storytelling isn't through courses, but by giving them more "at-bats"—real opportunities to pitch their initiatives. This must be followed by a strong, structured feedback loop from peers and managers, using tools like Lattice to solicit and collate input on what was and wasn't impactful.

Because PMs deeply understand the customer's job, needs, and alternatives, they are the only ones qualified to write the evaluation criteria for what a successful AI output looks like. This critical task goes beyond technical metrics and is core to the PM's role in the AI era.

A product manager's role extends beyond development. The customer stories and problem statements gathered during discovery are powerful sales assets. Packaging these insights and sharing them with the sales team helps them communicate the product's value more effectively.

AI is rapidly reducing the complexity of building software. Consequently, a product manager's value is shifting away from being a Gantt chart master. The most critical, high-leverage skill is now influence: generating good ideas, bringing people along, and getting buy-in to fund projects beyond the V1.

As AI automates 'hard' product management tasks like data synthesis and spec writing, the role’s value will shift. PMs who thrive will be those who master uniquely human skills like stakeholder influence, creative problem-solving, and critical thinking, which AI cannot yet replicate.