Updated: October 29, 2025- 12 min read
No, AI isn’t at the point of replacing product managers outright. These are not the words of comfort; this is my opinion based on realistic observations and decades of leadership.
Sure, the PM role will evolve. But AI will handle routine PM tasks, workflows, and analyses. The strategic, creative, and human parts of the job remain firmly in human hands.
In practice, AI is more of a super-smart assistant than a substitute. An AI product manager can move faster on grunt work (like drafting specs or crunching data) while focusing their own time on vision, leadership, and teamwork.
That said, the old product playbook is outdated. It’s not so much that you’re in danger of losing your job to AI, but rather to another PM who uses AI better than you. According to a recent report from MIT (1), about 95% of generative AI initiatives fail to generate meaningful financial returns or scalable impact. Becoming AI-native is the best—the only—to protect your career prospects.
Here are all the details you need to know and what makes me think this way.
AI for Product Managers Certification
Adopt an AI-first mindset: design AI-native UX, build agents, define modern PRDs, and ship trustworthy AI-powered products.
Enroll now
What Can AI Do Today That “Puts PMs in Jeopardy”?
AI tools today can automate parts of a PM’s workflow. For example, summarizing user research, analyzing product metrics, drafting documents, and generating ideas.
AI “can speed up the grunt work” of product management. It can summarize feedback, write drafts of specs or user stories, and brainstorm feature ideas. But “it still can’t lead a team, build alignment, or understand the nuance behind user pain points”.
AI can draft epics and user stories in Jira, and thus cut planning time by half. AI can even suggest OKRs or mock up low-fidelity wireframes, speeding up early-stage design. But in each case, the AI output had to be checked, guided by clear prompts, goals, and context from the human PMs who know what they need.
Will product managers get replaced by AI?
No, AI won’t replace product managers outright. It can automate parts of the job like research summaries, spec drafts, and data analysis, but leadership, vision, and human judgment remain firmly in human hands.
McKinsey’s 2024 global AI report backs this up (2). While 43% of companies report productivity gains from AI, only 11% have realized measurable ROI at scale.
What AI can’t do (yet) is determine the “why” or manage the “who” of products. Crucially, AI doesn’t understand a company’s mission, competitive nuances, or customer relationships, so it can’t truly own the product vision.
It can’t sit in a product brainstorming session or negotiate a trade-off between users and engineers with real-world context. It won’t intuitively read between the lines in user interviews, sniff out hidden pain points, or build team trust (all core parts of the PM role).
In short, AI can handle data-heavy tasks (like crunching numbers or summarizing reviews), but strategic thinking, empathy and leadership remain human strengths. As one veteran PM put it (3):
“Replacing PMs with LLMs is about as likely as replacing accountants with spreadsheets.”
Yes, the tools do part of the job, but only people understand the context and are accountable.
AI is definitely changing the product management
As AI grows more capable, it will shift the PM role rather than erase it. Experts argue that the biggest impact of AI will actually be on higher-level PM skills like product strategy and product vision. In a recent industry survey, 65% of product professionals report they’ve integrated AI into their workflows (4). This underscores that the AI-plus-PM combo is already real.
Microsoft CTO, Kevin Scott, a noted PM author, predicts that AI will become strong at analyzing huge amounts of market and user data. But he added that PMs remain essential to developing and training AI agents, especially in building feedback loops and domain expertise.
In his view, a PM’s job will evolve. The AI might generate a draft strategy, but the PM must decide what data to feed it and ultimately make the final call.
Dave Bottoms, GM and VP of Product at Upwork, also aligns with Kevin on The Product Podcast:
I think we're interestingly a long way from AI replacing people, but AI doing 50, 60, 70% of the work and then the people coming in to refine, customize, augment what exists. You're getting a work product much more quickly and efficiently.
In practice, this means PMs will guide AI tools with better questions, use AI to jumpstart reports and documents, and spend even more time on the human-side skills (product sense, communication, creativity) that machines lack.
Product managers on the ground agree that AI is an aid, not a replacement. One PM forum user quipped that AI “can replace mediocrity, it can rarely replace good, let alone great product managers” (5).
Others point out that AI might create more PM roles by making development cheaper (an “ATM effect”. Just as ATMs didn’t eliminate bank tellers; they changed the job, allowing the development of "relationship banking" that we take for granted today).
A common theme is that AI will automate routine and tedious tasks, forcing PMs to be more efficient, but never making the core role disappear. In fact, many product teams report hiring for new AI-focused PM roles. Right now there are hundreds of specialized “AI product manager” openings, and we urge you to start from this AI Product Manager piece to get a better sense.
Will product managers become obsolete?
No, product managers won’t simply disappear. Even as some tasks shift to machines, companies still need people to define goals, inspire teams, and make final decisions.
We might see parts of the PM role get redistributed or “commoditized” (e.g., smaller companies using AI-powered PM assistants for checklists), but the role itself adapts.
Evidence suggests that while automation may handle the heavy lifting on metrics or documentation, the need for human oversight remains. If you have ever used AI agents as a PM, you know that AI is still a long way from working independently as a product manager.
In practice, the more AI tries to write strategy or analyze markets, the more we’ll want a human in the loop to question its assumptions. In other words, PMs become the quality control and vision-setters for AI-generated ideas.
Plus, many of a PM’s daily challenges involve messy people-work (aligning stakeholders, motivating engineers, pivoting with incomplete info). Scenarios where an AI lacks real-world accountability. As one PM bluntly said (6): AI has the most experience and creativity”, in theory. But in reality, only humans can translate that into empathy and context.
In summary, PM roles won’t become obsolete; they’ll be redefined. The rising trend is not to eliminate PMs, but to combine AI tools with PM leadership. Companies still list thousands of PM openings worldwide, indicating strong demand for people who can leverage AI outputs, ask the right questions, and steer products.
In fact, replacing PMs en masse would be akin to “replacing accountants with spreadsheets”. Technically, the tool does some tasks, but accountants (and PMs) still oversee the process. In short, great product managers will use AI to multiply their impact, not be replaced by it.
Do product management careers have a future?
Absolutely, the future of product management looks active and evolving. Far from fading out, PM roles are projected to grow.
Industry data shows that open PM roles have rebounded strongly after recent tech layoffs. On LinkedIn, there are currently around 23,000 open product manager roles worldwide. Even a conservative industry analysis projects 10–20% growth in product-related roles over the next five years (7).
In the US, “management occupations” (which include PMs) are expected to grow faster than average from 2025–2034 (8). These numbers reflect that companies still need product leaders.
The nature of the PM role is shifting, not dying
New niches like “AI product manager” are high in demand (often with very high salaries) and require PMs who understand data and AI trends.
At the same time, core product management skills (market savvy, customer empathy, and team leadership) remain essential. Many PMs report upskilling in AI tools because the role is literally evolving: PMs who can speak the language of AI gain an edge.
In other words, PM careers now include mastering AI data analytics and agile product management. In practice, a PM might spend part of their day fine-tuning an AI model’s analysis of user data, and the rest of the day running design sprints with their team.
Product managers definitely have a future (and a strong one)
AI isn’t killing PM roles but actually increasing their leverage. This is changing how teams are structured. Experts like Andrew Ng have suggested the developer-to-PM ratio could soon flip to 2:1, as opposed to the previous norm of 1:4-6.
The best PMs will be those who integrate AI into their workflow while emphasizing the human skills AI lacks.
In fact, the era of AI could make product management even more strategic. PMs will spend less time on routine tasks and more time figuring out why a feature matters and how to rally teams around it. The rise of AI is making product managers’ roles more empowered, not obsolete.
Which PM Skills Can AI Agents Automate?
AI agents can already take over some of the repetitive, structured, or data-heavy tasks in product management.
As coding accelerates exponentially, the bottleneck in product development is no longer engineering; it’s product. Experts like Andrew Ng have suggested the developer-to-PM ratio could soon flip to 2:1, compared to the previous norm of 1:4–6, meaning PMs will need to move much faster to keep up with engineering velocity.
As Glen Coates, the VP of Product at Shopify, points out on The Product Podcast:
I've now started doing the thing where I take a screenshot and ask AI to create a prototype. It speeds up the feedback cycle and helps me realize how dumb my ideas are before my team has to waste time on them.
While Coates is interacting directly with an LLM rather than an automated agent, it perfectly illustrates how AI can help PMs iterate faster and remove friction from the creative process. This allows product teams to match the overall increased speed of development across engineering, design, and data.
These are areas where algorithms can process faster and more accurately than humans:
Summarizing research: AI can scan through surveys, interview transcripts, and reviews to generate quick insights and recurring themes.
Drafting product specs and user stories: Tools like ChatGPT can produce first drafts of epics, acceptance criteria, and requirement docs that PMs can refine.
Analyzing product metrics: AI can quickly process user behavior data, identify patterns, and suggest anomalies that deserve attention.
Generating ideas: Large language models can brainstorm potential features, design solutions, or even product positioning angles.
Creating mockups or prototypes: Some AI-driven design tools can produce low-fidelity wireframes or interface suggestions from text prompts.
Automating reporting: Weekly dashboards, KPI updates, and OKR progress summaries can all be produced faster with AI support.
But while AI can speed up these tasks, it still needs human direction, context, and judgment. PMs provide the “why,” ensure alignment with strategy, and manage the messy human dynamics that machines can’t replicate.
AI Prototyping Certification
Go from idea to prototype in minutes. Build, debug, and scale AI prototypes with the latest tools to integrate APIs securely and hand off to engineering fast.
Enroll now
Which Product Management Skills AI Cannot Replace
AI is great at speeding up routine work, but it can’t do the human parts of product management. These skills hinge on context, trust, accountability, and judgment that emerge from real relationships and real stakes.
Product vision and product strategy: Choosing non-obvious bets, setting direction, and saying no when the data is noisy.
Problem framing and prioritization: Defining the real problem, writing crisp problem statements, and deciding what not to build.
Customer empathy and judgment: Reading nuance in interviews, reconciling conflicting signals, and understanding unstated needs.
Cross-functional collaboration, leadership. and influence: Aligning design, engineering, and go-to-market; negotiating trade-offs; earning trust without authority.
Decision-making under uncertainty: Weighing incomplete data, reversibility, timing, and second-order effects when the answer isn’t in a dashboard.
Narrative and storytelling: Crafting a compelling story for executives, teams, and customers that drives alignment and action.
Ethics, risk, and compliance calls: Making judgment calls on privacy, safety, fairness, and regulatory constraints—and owning the consequences.
Change management: Driving adoption, managing expectations, improving team effectiveness, and landing new behaviors across the org.
Product sense and taste: Evaluating solutions qualitatively, insisting on simplicity, coherence, and a bar for quality that data alone can’t set.
Sequencing and portfolio management: Allocating resources across bets, pacing delivery, and balancing short-term wins with long-term platform health.
Market and competitive interpretation: Reading weak signals, partner dynamics, and macro trends to adjust strategy before the numbers show it.
Relationship building: Developing trust with customers, design partners, and internal stakeholders that opens doors and surfaces truth.
Learning loop design: Deciding what to measure, how to experiment, and when to pivot, so the team learns the right things faster.
AI can assist each of these areas with data and drafts. It can’t replace the lived context, credibility, and judgment that make a product manager effective.
Redefine Yourself, So It Doesn’t Replace You
The story of AI in product management is about redefinition. Yes, AI can write specs, analyze feedback, and even sketch a wireframe faster than most humans. But it can’t see the future of your product, rally your team behind a bold bet, or empathize with a customer who doesn’t even know how to articulate their pain point.
Those parts are still yours.
The real risk is that AI will expose PMs who don’t evolve. If you keep doing the role exactly as you did yesterday, you may find yourself competing with an algorithm that does it faster and cheaper. But if you redefine yourself (lean into strategy, vision, storytelling, and human leadership) you’ll stand on ground that AI simply cannot cover.
So, will product managers be replaced by AI? No. But product managers who don’t redefine themselves might. The choice is simple: let AI replace your tasks, or redefine your role so it amplifies your impact.
Advanced AI Agents Certification
Design and implement adaptive, multi-agent AI systems with memory, collaboration, and risk safeguards. Deploy production-ready AI agents at scale.
Enroll now
(1) https://fortune.com/2025/08/18/mit-report-95-percent-generative-ai-pilots-at-companies-failing-cfo/
(2): https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai
(3): https://www.reddit.com/r/ProductManagement/comments/1dz5093/how_close_is_ai_to_replacing_product_managers/
(4): https://testdouble.com/insights/ai-product-management-survey-data
(5): https://www.reddit.com/r/ProductManagement/comments/1dz5093/how_close_is_ai_to_replacing_product_managers/
(6): https://www.reddit.com/r/ProductManagement/comments/1dz5093/how_close_is_ai_to_replacing_product_managers/
(7): https://generalassemb.ly/education/how-will-the-role-of-product-managers-change-in-2030/online
(8): https://www.bls.gov/ooh/management/
Updated: October 29, 2025
