Short answer: no.

But to explain why, I need to start with a different role first – programmers.

I truly believe that people whose only skill is writing code are going to be needed far less in the very near future.

If your value is translating requirements into code, AI is already doing this remarkably well, and it’s only getting better.

Within a year or two, companies that have one or two strong software architects will need far fewer traditional programmers. Not zero. But significantly fewer.

Why?

Because programming mostly operates within well-defined rules, frameworks, and paradigms. AI excels in exactly these environments. There is also an enormous amount of existing code and documentation to train on.

This is only partially true when it comes to software engineering and architecture, but that’s out of scope for today.

So the real question becomes:

If coding-heavy roles are at risk, why wouldn’t product managers be next?

What makes product management different

The key difference is simple:

Most of a product manager’s work is not thinking. It’s communication.

I’ve written about this in depth before, but it’s important enough to briefly restate here (here is the link to the post).

Real product management is not about writing documents. It’s about working with people, constantly.

A product manager’s job includes:

• Understanding real customer pain through interviews, research, and discovery
• Translating company goals into strategy, roadmaps, and quarterly plans
• Working day-to-day with engineering, design, and product marketing
• Driving execution through planning, prioritization, and delivery
• Iterating continuously based on feedback, usage, and business outcomes

Each of these areas hides dozens of concrete activities: PRDs, sprint planning, estimations, wireframes, stakeholder negotiations, launches, and more.

What AI can do very well (and will get even better at)

AI is already extremely capable, and it will absolutely change how product managers work.

AI can already, or soon will:

• Generate reasonable product strategies and roadmaps given constraints
• Propose quarterly plans and sprint structures
• Analyze feedback, usage data, and research artifacts
• Draft PRDs, specs, and release notes

This is impressive.

It can easily double a good PM’s productivity.

But here’s the critical distinction:

These are inputs. Not outcomes.

Where AI stops short

In practice, here’s what happens:

AI can suggest a product strategy.

But a product manager still needs to get buy-in from managers and, often, the executive team. That requires persuasion, context, and addressing objections in real time. No one follows a strategy just because “the AI said so”.

AI can propose a quarterly plan.

But the product manager must adjust it based on people, dependencies, history, and politics, and then take it through multiple stakeholders to align expectations. Quarterly planning is hard precisely because it’s human.

AI can suggest sprint structures.

But it can’t run sprint planning, negotiate scope, react to pushback, or read the room when tensions rise.

AI can write a PRD.

But it can’t conduct the spec review meeting, handle disagreements, or converge a team around trade-offs.

AI can suggest new initiatives.

But it can’t reliably filter out ideas that will fail due to organizational reality, nor can it convince the right people to back the good ones.

AI can’t interview customers effectively.

Even if it could talk, customer conversations require empathy, nuance, small talk, and the ability to hear the pain behind the proposed solution.

AI can do research.

But it can’t run a full discovery process for the same reason: discovery is messy, emotional, and deeply human.

And AI certainly can’t orchestrate delivery.

That requires constant communication, context switching, responding to Slack messages, resolving conflicts, and putting out fires.

Where AI will continue to fail (for now)

AI struggles not with reasoning, but with social reality.

Yes, it can speak.

Yes, it can explain.

Yes, it will never lose its temper.

But effective communication is not about saying the right words.

It’s about tone, timing, trust, empathy, and knowing who you’re talking to.

That’s exactly why communication is such a core skill for product managers, and why it’s so hard to automate fully.

The real takeaway

AI is going to eliminate jobs. No doubt.

But roles built around human interaction, judgment, and influence are far more resilient than roles built around well-defined rules.

Product managers are not safe because of their title.

They are safe if they are good at working with people.

Bad PMs, passive PMs, and document-only PMs should absolutely be worried.

Good PMs should not relax.

They should adapt.

Because the next feature is already waiting.