AI is the Engine, but Product Managers Are the Drivers

AI isn’t replacing PMs - it’s changing how they win the race

It seems that at least once a week, a client asks: “How do we use AI without losing our product soul?” Or a student asks: “Do you think AI is replacing product managers?”

I don’t have a crystal ball. But I have seen that for some orgs already integrating AI, launching more products with leaner teams is imminent. For many others, it’s still a ways off. Either way, one theme is clear: AI is no longer optional. It’s a force multiplier for product teams - and it’s about shifting how we build, not why product management exists.  So what’s my hypothesis?  AI won’t replace PMs, but it will kill bad product management.

We’ve Seen This Movie Before…

Product management has weathered many shifts that changed how we work: Agile replacing waterfall, Lean Startup forcing MVPs and hypothesis testing, DevOps reshaping release cycles, Design Thinking putting empathy at the center, OKRs reframing outcomes, cross-functional pods driving autonomy, remote work reshaping rituals, and data-driven decision-making raising the bar.

Each wave changed the methods – how we work, not why PMs exist. None eliminated the need for product managers. If anything, they made the role more critical.

What AI Can Really Do for Product Teams

Yes, overheads have dropped dramatically. In fact, “1 in 5 product leaders have already reduced PM headcount thanks to AI gains” (Product Collective / Lenny’s Community Poll, 2024). Yet the broader picture points in the opposite direction. Paradoxically, the most successful companies are actually expanding their investment in PM roles - not necessarily in numbers, but in compensation and influence. As one recent survey noted,

“Executives in IT and product development are more likely to expect headcount increases - not cuts - as AI becomes embedded” (McKinsey, State of AI, 2024).

Why? Because the enduring value of product management has never been writing Jira tickets or summarizing delivery status. It’s about orchestration: aligning leaders around shared goals & target outcomes, choosing the right problems to tackle at the right time, and inspiring teams to move in unison. It requires fluency at the intersections - between market dynamics and competitive shifts, business strategy and operational readiness, tech capabilities and constraints, quantitative data and qualitative user behavior. And it demands the art of rallying people: crafting a vision, creating conviction, and helping teams believe in where they’re headed even when the path is uncertain. AI doesn’t replace that orchestration.

What it does is clear the low-value, repetitive work off the table so PMs can focus on higher-value activities.  If I had a dollar for every PM who told me they know how to build better products but don’t have time… AI finally gives us a way to fix that.

Over the years during training, coaching, or product transformation work I’ve repeatedly heard: “Everything you’re teaching me sounds amazing - I know I should be doing it.  That it will help me make better decisions, build better products, meet customer needs, and drive business value… but I don’t have time!” Instead, they’re knee-deep in writing Jira tickets, updating slide decks, looking for a needle in the haystack of mounds of (trustworthy?) data, or chasing down status updates.

AI gives us a shot at clearing that noise, so PMs can finally spend more of their energy where it matters: discovery (talking to users and finding unexpected insights), alignment (with stakeholders about competing priorities or impacts to operations), building trust and cohesion within teams, evangelizing strategy & vision across the org, and inspiring and acting as true thought partners with engineers and UX designers.

The steps to make good product decisions haven’t changed. AI just helps us do them faster.

As Robert Michaels, a product leader at Kroger, put it:

“When code can be delivered in a week instead of six months, product can’t afford to figure things out on the fly anymore. We need more details upfront - data hierarchies, rule logic, visualizations - so we can feed the engineering beast and keep pace.”

Will PMs Be Left Behind?

Some worry that faster delivery cycles mean product managers will be left behind. But the opposite is true: the faster the build, the more critical it becomes to have clarity, alignment, and orchestration upfront. Speed without direction just leads to rework.

Here’s the paradox: AI is speeding up the build side of product so much that it’s pushing us back toward what feels, at first glance, a little more “waterfall-ish.”

But that doesn’t have to mean slowing down. It means being intentional.  The most successful products will come from teams that do more planning before they accelerate - so when it’s time to build, they can move at full speed with confidence.

Think of it this way: Agile taught us to learn fast and adapt. That doesn’t go away. But as delivery cycles compress, product teams need to balance agile responsiveness with thoughtful upfront strategy.  Even with AI accelerating delivery, you still need product managers orchestrating across functions - syncing go-to-market and business readiness so that when it’s time to move, the engine revs without delay.

This clicked for me last night when I finally watched the F1 movie: the car may be lightning fast, but the outcome still depends on the pit crew coordinating flawlessly, the technical team anticipating conditions, and the driver having conviction in the race strategy. Product managers play that role - ensuring everything is aligned so when the lights go green, the team can perform at full speed. And because we build products for real people, not just systems, empathy and understanding remain just as critical as horsepower.

Formula 1 teams don’t win on speed alone. They win because the pit crew, engineers, and driver are aligned on strategy. Product is no different: AI gives us the horsepower, but PMs provide the orchestration and empathy that turn speed into victory.

The Reality of Layoffs - and What Comes Next

Despite this, it’s impossible to ignore that many product managers have been caught up in recent waves of layoffs across tech. Some of this is directly tied to AI efficiencies, and some reflects broader market corrections. For those affected, it’s natural to feel that AI is an existential threat to the role.

But here’s the perspective I’d offer: while there is certainly fat to trim in many organizations, much of what we’re seeing now is the turbulence of transition. Organizations are still figuring out how to harness AI, where it adds real value, and where its gaps remain. As the dust settles, companies will learn that the real opportunity isn’t replacing PMs - it’s re-focusing them.

"77% of product teams spend more time reporting than delivering" (Pendo, State of Product Leadership, 2023).

AI will handle more of the repetitive, low-value work. But the need for product leadership - to orchestrate across teams, align stakeholders, and make judgment calls when the data is incomplete - only grows as AI raises the bar for what “good” looks like.

So while some teams are contracting today, the long-term trend points to something different: fewer PMs doing tactical work, and more PMs stepping into elevated, strategic roles.

The Limits of AI in Product Work

So if AI won’t eliminate PMs but does force a shift, what are its blind spots?   AI struggles with context, nuance, and ambiguity. It won’t know that getting input from the quiet lead engineer now will save you three weeks of churn later. It won’t persuade executives to de-risk a big bet, or rally a skeptical team around a disruptive vision.

Product managers are more than process keepers - they are catalysts of conviction. They spot when team motivation is slipping, and re-anchor everyone in the “why.” They make judgment calls when the data isn’t clear. They craft narratives that inspire belief and alignment, even in the face of uncertainty. Product managers keep the vision clear and help the team navigate back to true north when distractions or competing priorities pull them off path.  AI can crunch data, but it can’t build trust, negotiate trade-offs, or spark shared conviction. 

This is why the age of AI is not the end of product management. It’s the end of bad product management.

What AI Can’t Shouldn’t Touch (and PMs Must Own)

I almost titled this section “What AI can’t touch,” but let’s be honest: it’s moving so fast I’d probably be proven wrong before this article goes live. Still, the spirit stands - even as AI advances, strong product managers remain essential for the parts of the job that are deeply human:

• Making judgment calls when the data isn’t clear.

• Understanding context, nuance, and edge cases.

• Building trust with teams and execs.

• Crafting narratives people can rally behind.

• Recognizing unmet needs before the data is obvious.

Let’s look at some tangible examples I’ve seen manifest lately in the teams I’m working with…

Talking to users & uncovering unexpected insights. Automated user interview scheduling, powered by AI-generated SQL and workflow automation, has cut busywork by 90%, freeing up teams to think deeply (Alan).  And AI can help synthesize feedback - summarizing interviews, clustering comments, or surfacing patterns - but it can’t replicate the serendipity and empathy of human-led discovery. Even the best research-assistant tools still need a person to probe emotional cues, nuance, and the “why” behind user behaviors (Maze, Test Double). 

Aligning stakeholders amid competing priorities. AI can summarize positions or simulate trade-off outcomes, but it can’t navigate politics, build trust, or negotiate compromises across executives. Consensus-building and leadership remain firmly in the human domain (The Times).

Building trust & cohesion within teams. It's the PM, not the algorithm, who notices when team energy dips and responds. AI may surface signals - like burnout risk from DevEx metrics - but humans must interpret them empathetically and act.  As Upwork research emphasizes, “productivity gains are only sustainable when AI augments, not replaces, human connection, purpose, and growth.”

Evangelizing strategy & vision across the org. Vision is emotional, not logical. AI can help draft FAQs or decks, but it can’t inspire belief, shape culture, or create conviction. That’s product leadership work.  “While AI automates many technical tasks... it also shifts the spotlight onto something AI cannot replicate: empathy, communication, and the ability to inspire teams - the very hallmarks of successful PMs (Omdena).”

Acting as a thought partner with engineers. AI can generate code snippets or insights, but it doesn’t understand the unstated norms, architecture constraints, or legacy debt inside a specific org. Human trust and partnership are still central.  A joint “understanding (of) the ‘why’ behind a product not only builds trust but increases motivation” (ProductPlan).

The Bottom Line

There’s no credible example where AI replaces the emotional or strategic work of product managers - and for good reason. AI is fast-becoming a powerful tour in our belts – that can amplify insights but not replace intuition. That can surface patterns, but we still need product managers to interpret them in context – market dynamics, team emotions, nuanced strategic priorities, politics, individual & team strengths and blind spots. So rest easy: AI isn’t rendering PMs obsolete. It’s refining how they contribute most meaningfully. 

As one of my favorite client product leaders recently said: "Every single product team should be using AI. The shift is that dramatic – akin to the difference between working pre-email and post-email. Once you’ve crossed that line, you can’t imagine going back."

And she’s right. This isn’t just about PMs - it’s about how entire product teams work. Automating low-value tasks frees space for the work that truly matters: evangelizing strategy, inspiring teams, aligning stakeholders, and making sharper, faster decisions.

“AI is no longer optional - it’s the engine steering the future of product management. If you’re not onboard, you’re already drifting behind.”  (Pragmatic Institute, State of Product Management & Marketing Report, 2024)

But it is a critical tool that can help us do more, better, faster. The PMs who can orchestrate outcomes, rally teams, and lead with conviction will be the reason AI-powered initiatives move beyond flashy demos to durable products that matter.

AI gives us horsepower - but horsepower alone doesn’t win races. The fastest cars in Formula 1 still need a driver with vision and a team orchestrating every move to convert speed into victory. The same is true in product: AI accelerates the build, but it’s product managers who set the strategy, rally the crew, and keep the team aligned on what matters most. That’s how you cross the finish line first - not just with speed, but with purpose.

AI isn’t coming for product managers. It’s coming for the low-value tasks holding them back.

If your product value is in your Jira prowess, the future looks rough. But if you’re obsessed with solving the right problems and leading strategically, you’re not obsolete. You’re more essential than ever.

If you’re a product manager (or leader) who wants to build confidence in using AI without losing your product soul, I can help. From 1:1 coaching to team workshops, I work with PMs to become AI-literate, elevate their impact, and focus on the work that truly drives outcomes.

Curious? Let’s riff. I’m happy to talk through what might fit – you can reach out at janel@peerlesspartners.net.

And for now, just this: AI isn’t replacing product managers - but PMs who learn to harness it will be the ones driving outcomes.

📚 Further Reading

• McKinsey — The State of AI in 2024

• Pragmatic Institute — State of Product Management & Marketing Report, 2024

• Pendo — State of Product Leadership Report, 2023

• Lenny’s Community / Product Collective — AI & Product Management Headcount Poll, 2024

• Product School — 10 Product Management Skills That AI Will Never Automate

• ProductPlan — How Product Teams Build Trust

• Omdena — Building Empathy & Vision in an AI-Driven World

• Business Insider — How Uber’s CPO Uses AI at Work

• Alan — Automating User Interview Scheduling with AI

• Medium (Gedis) — AI-Powered Product Management: User Research at Scale

• Upwork Research — AI & The Human Work Dynamic, 2025