Monday.com guide says AI can sharpen product roadmaps and decisions

AI should speed up the work before the meeting, not replace the meeting itself

Product managers at monday.com live in the gap between too much signal and too little certainty. Customer feedback arrives in fragments, sales wants one priority, engineering sees another risk, and leadership still needs a roadmap that looks deliberate rather than improvised. The smartest use of AI in that environment is not to make product judgment disappear, but to make the evidence easier to see.

That is the core idea behind monday.com’s guide for product managers: AI should automate research and planning, sharpen roadmapping, and make product decisions more data-driven. For a company built around workflows, the logic is practical. If a PM spends hours synthesizing notes, comparing options, and translating messy feedback into something the team can act on, AI can take the first pass and give back time for the harder part, tradeoffs, sequencing, and alignment.

Where AI belongs in the product manager workflow

The best workflow playbook starts before anyone opens the roadmap doc. AI can help collect customer pain points, summarize feature requests, and group similar themes so PMs are not manually stitching together dozens of comments from support, sales, and design. That matters at monday.com because product decisions rarely stay inside one function. Engineering needs clarity on scope, sales needs language for prospects, and customer-facing teams need to know what is coming next.

AI can also help compare scenarios instead of forcing PMs to argue from memory. If one option improves retention but slows enterprise rollout, and another helps onboarding but creates engineering complexity, the job is to make those tradeoffs visible fast. The value is not just faster writing. It is better decision quality, clearer evidence, and fewer meetings that happen because no one has done the synthesis work yet.

Why monday.com is pushing this beyond a single feature

This is not a standalone productivity story for monday.com. On February 10, 2025, the company said its AI vision would rest on three pillars: AI Blocks, Product Power-ups, and the Digital Workforce. Daniel Lereya, the company’s Chief Product and Technology Officer, said monday.com was “reimagining how work gets done,” which is a useful clue to how the company wants customers, and its own teams, to think about AI.

The message is that AI should be embedded into the product suite, not bolted on as a novelty. monday.com said that approach would include modular actions such as Categorize and Extract, plus specialized digital workers that can analyze project risks, unlock stuck sales deals, and identify recurring customer-service issues. For product managers, that framing matters because it treats AI as infrastructure for workflow design and decision-making, not just as a writing assistant.

The platform shift is moving from work management to work execution

That broader strategy became more concrete on July 10, 2025, when monday.com introduced monday magic, monday vibe, and monday sidekick as part of what it called a shift from work management to work execution. monday magic can generate a workflow or board from a single plain-language prompt, while monday vibe lets users build secure custom business apps without writing code.

For PMs inside monday.com, that is more than a product launch. It is a signal about how the company thinks the future of work software should behave. Less time goes into translating a business idea into structure, and more time goes into acting on the work once the structure exists. That same logic applies to product management itself: AI should turn scattered input into boards, workflows, and decisions that teams can actually use.

The customer proof point behind the strategy

monday.com has also tried to ground the AI narrative in actual customer behavior. At Elevate 2024, the company said it had received 1,700 feature requests since the previous Elevate. It also said its more than 225,000 customers had saved 1.5 billion minutes annually by automating 380 million tasks and generating 33 million cross-team interactions.

That is the kind of scale that makes the AI-for-PM argument feel less abstract. If customers are already using the platform to cut time and automate repetitive work, then the next step is helping the people who shape the roadmap work with cleaner evidence and faster synthesis. The company’s own roadmap emphasis on stronger infrastructure, smarter reporting and analytics, and more advanced workflows suggests it sees AI as part of the same product-led engine.

What the research says about adoption inside real organizations

The company’s World of Work report, commissioned by Qualtrics and published on January 27, 2025, adds another layer. It found that 73% of millennials were adopting AI, compared with 59% of Gen Z respondents. It also found that 82% of respondents use work and project-management software, and 57% said the number of tools they use increased year over year.

That is a useful reminder for any PM designing an AI workflow: the problem is not simply access to tools. It is getting people to trust them, use them, and fold them into actual work. monday.com’s research also points to a human challenge around change management, especially in larger enterprises where utilization tends to lag. If the roadmap team wants AI to improve decisions, it has to make the tool feel reliable, transparent, and tied to a real outcome.

The sticking point is still trust, not novelty

A later monday.com report with Nielsen sharpened that point further. In November 2025, after surveying 500 directors in the US and United Kingdom and analyzing millions of monday.com workflows, the company said the top drivers of AI adoption were speed at 59%, accuracy at 56%, and productivity at 53%. The biggest blocker was data privacy and security concerns at 40%.

That combination says a lot about where product teams are heading. People do want AI to make them faster, but they will not hand over decisions unless the output is accurate enough to trust and secure enough to defend. monday.com described this as the “Operational Era of AI,” which fits the way product managers actually work: the winning tools are the ones that survive contact with real workflows, real approvals, and real risk.

What this means for monday.com teams trying to ship better

The clearest takeaway for product managers, engineers, sales teams, and customer-facing leaders at monday.com is that AI should remove friction from the path to a decision. Use it to summarize demand, cluster feedback, compare scenarios, and keep the roadmap tied to measurable outcomes. Use it to reduce manual synthesis so the team can spend more time on strategy, tradeoffs, and stakeholder alignment.

The business case is getting harder to ignore. On February 9, 2026, monday.com reported fourth-quarter revenue of $333.9 million, up 25% year over year, with full-year 2025 revenue up 27% and a 14% non-GAAP operating margin. The company also said monday vibe was the fastest product in its history to surpass $1 million in ARR, while customers with more than $50,000 in ARR represented 41% of total ARR and record net adds came from customers with more than $100,000 in ARR.

That is why this AI story matters inside monday.com. It is not about replacing product judgment with software output. It is about giving product teams a cleaner path from customer signal to shipped work, so the roadmap reflects evidence instead of noise. With more than 250,000 customers worldwide, the company is betting that better workflow execution will become the new definition of product discipline.