AI Product Management: Levels, Tasks & AI Scope 🪜

As AI weaves its way into more and more products, companies are realizing they need dedicated product leaders to guide the way. Enter the rapidly evolving role of the AI Product Manager. 

But how exactly does the AI Product Ladder change as your org climbs the career ladder?

Let's dive in, as per image above, at the most junior level, the Associate Product Manager (APM) or Product Manager (PM) (L3/4) primarily focuses on working hand-in-hand with AI/ML eng teams to shepherd the development and deployment of AI models. Key tasks include monitoring model performance, ensuring data pipelines are in place, adhering to AI governance and ethics guidelines. The scope is tactical - making sure that AI "machinery" is integrated into an AI-powered experience, for example owning the implementation of an AI chatbot for Zappos.

As you step up to the Senior Product Manager level (~L5), the role broadens. Now you're not just focused on shipping AI features, but defining the holistic AI product roadmap and strategy. You'll work xfn with design, data science, and go-to-market teams to actually identify and prioritize the most impactful AI use cases to bring to life. Evangelizing the product vision to both internal and external stakeholders becomes critical. Here, the scope expands to weaving multiple AI capabilities together into a cohesive product offering, for example launching a personalized recommendations feature for Netflix.

Move up to the Principal Product Manager or Group Product Manager level (~L6/7), and the responsibilities get meatier. You're setting the multi-year vision for where AI can take the product, and rallying the entire team around that north star. Securing buy-in and resources from executive leadership is part of the job. You'll also be more involved in defining the AI infrastructure and data strategy to enable cutting-edge innovation. The scope covers the full AI lifecycle of taking major AI initiatives from concept to market success, for example leading a discovery platform at Pfizer.

Finally, at the Product Director, VP and CPO level, the focus zooms all the way out to defining the company's overarching AI strategy and roadmap. 

• What AI-powered products and businesses should we be betting on to secure our future? 

• What investments, partnerships and acquisitions do we need to make that happen? 

Responsibilities span influencing board-level decisions, driving key strategic initiatives, and positioning the firm as an AI thought leader. The ultimate scope is leveraging AI to disrupt industries and shape the company's long-term competitive advantage, for example overseeing AI across Google’s product suite or shaping Amazon’s 10-year vision.

While the day-to-day of an AI PM may look quite different from level to level, there are common threads across the board: a passion for transformative innovation, a commitment to responsible AI practices & the ability to lead teams around an ambitious vision while keeping them motivated throughout an experimentation-first culture towards continuous iteration for long-term success.

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Note: This representation of the AI Product Management ladder reflects my personal perspective from my 10+ years in Big tech and does not correspond to any specific company or team. The structure and responsibilities can vary widely across organizations. What are your thoughts?