Why the AI Industry Needs Product Managers: Mastering the New Skillset

As a VP of Product Management deeply involved in the AI space, I’m constantly thinking about how this technology is changing our profession. I share many of my ongoing thoughts and projects in my daily journal, and today I want to talk about something crucial for all of us in the product world:

Why AI makes skilled product managers more valuable, not less.

The Game is Changing Fast

We're seeing product development cycles shrink dramatically. Ideas that once took weeks or months to prototype and test can now often be explored in days, sometimes even hours, thanks to AI tools. Think about generating user stories, drafting initial designs, analyzing feedback, or even building basic functional code.

AI accelerates all of it.

At the same time, almost every company wants to incorporate AI features into their products—not to mention the surge of new AI-native startups. This creates a huge demand for deciding what to build.

If ideas can be built and tested faster than ever, and there's a massive push for AI features, who becomes responsible for figuring out:

• What problems are truly worth solving with AI?

• What's actually possible with today's AI (and where is it going)?

• Which AI vendors or models are the right fit?

• How do we ensure AI features deliver real customer value and can be monetized?

• How do we manage the unique risks and ethical considerations AI brings?

That’s where we—the product managers—come in.

AI Demands More Sophisticated Product Management

Now, it's worth acknowledging the argument that AI could automate some routine PM tasks, like summarizing user feedback or drafting basic documentation. Some worry this might reduce the need for PMs.

However, I think the opposite is true. The increased complexity, strategic considerations, ethical navigation, and the sheer speed AI introduces will far outweigh any task automation. This ultimately demands more sophisticated PM skills, not fewer. 

AI doesn't replace the need for strategic guidance; it makes that guidance even more critical. With the ability to build more things faster, the decisions about what to build, why, and how to do it responsibly become paramount.

This means product managers are likely to be in higher demand, but the required skills and mindset are evolving.

New Skills and Mindset for the AI-Powered PM

Thriving in the AI era requires more than just adding tools. It demands evolving our skills and adopting a forward-thinking mindset. Here’s a breakdown of the key areas:

1. AI Technical Foundations

• Understand AI Technologies: Grasp the basics of different AI approaches (LLMs, RAG, fine-tuning) and their strengths/weaknesses.

• Master Prompt Engineering: Learn how to effectively guide AI models to get reliable and useful outputs for product tasks.

• Know ML Workflow Basics: If working directly with data science on custom models, understand the essentials of ML Ops and data lifecycles.

2. Navigating the AI Landscape

• AI Vendor and Tool Selection: Develop the ability to assess and choose the right AI platforms, models, and tools for your specific needs.

• Manage AI Costs: Understand the financial implications of API calls, context windows, and model choices to optimize spending.

• Handle AI Limitations and Roadmaps: Recognize current AI shortcomings and anticipate future developments to avoid wasted engineering effort.

• Embrace Ambiguity: Get comfortable navigating uncertainty and rapid change.

• Commit to Continuous Learning: The AI field evolves daily; staying curious and learning is non-negotiable.  Evaluate AI claims realistically and focus on genuine value.

3. Responsible AI Leadership & Strategy

• Champion Ethics & Compliance: Deeply understand and apply principles of fairness, transparency, bias mitigation, and privacy regulations (like GDPR).

• Prioritize Security: Be aware of and mitigate risks like data leakage or insecure processing.

• Develop Long-Term AI Strategy: Integrate AI thoughtfully into your overall product vision, building with flexibility.

Core Product Management is Still King

While new AI skills are essential, they augment rather than replace the fundamental pillars of product management. These core competencies become even more critical for navigating the AI landscape successfully:

1. Strategic Leadership

• Product Strategy and Vision: Define a clear direction and purpose for your product, especially regarding AI's role.

• Roadmapping and Prioritization: Make tough choices, balancing innovative AI features with core user needs and business value.

• Business Acumen and GTM: Understand the market, monetization strategies, and how to successfully bring products (including AI features) to market.

2. Customer Centricity

• Deep Market Research and User Understanding: Ground AI initiatives in real user problems and needs.

• Keen User Experience Sensibility: Ensure AI features are intuitive, helpful, and seamlessly integrated into the user journey.

• Building Strong Feedback Loops: Actively gather, interpret, and act on user feedback specifically related to AI features to drive continuous improvement and build trust.

3. Effective Execution & Collaboration

• Crisp Requirements Definition: Clearly articulate what needs to be built, even when dealing with complex AI functionalities.

• Strong Cross-functional Collaboration: Work effectively with engineering, data science, design, marketing, sales, customer success, legal, and other teams.

• Rigorous Experimentation and A/B Testing: Validate hypotheses and measure the true impact of AI features.

• Data Analysis and Metrics: Define and track the right metrics to understand AI performance and user impact.

• Compelling Storytelling and Persuasion: Communicate the “why” behind your AI strategy to stakeholders and your team.

AI might help execute some tasks within these areas, but the strategic thinking, judgment, empathy, and leadership behind them remain firmly human.

How to Level Up Your AI Game

The best way to learn is by doing:

1. Raise your hand: Volunteer for the next AI-related project at your company. Partner with AI tools as if they were team members assisting you.

2. Build something: If work projects aren't an option, create your own AI-powered MVP. It doesn't need to be complex, but try to apply your full PM skillset. Align it with your interests to stay motivated.

I recently built an AI voice agent myself. The process taught me countless nuances about different technologies, frameworks, and the challenges of making an AI reliable and valuable. Getting an LLM to be concise (essential for voice!) or stay on topic is harder than it looks. This hands-on experience is invaluable.

Your Turn

AI is reshaping our field, presenting a massive opportunity for product managers willing to learn, adapt, and lead with strategic clarity and ethical responsibility. It requires us to build new skills, adopt a growth mindset, and sharpen our core strategic abilities.

How are you planning to embark on your AI product management journey?

About the Author

Filip Szymanski has over 20 years of experience as a product leader and is passionate about leveraging AI to power a new generation of product managers. Follow my journey at productpath.ai or add me on LinkedIn.

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