AI Tool Sprawl Is the Real PM Productivity Crisis

Adoption was additive, not integrative

The way most teams adopted AI over the past two years follows a pattern I've watched repeat itself. Someone finds a tool that solves a specific pain. It gets adopted for that slice of the workflow. Then another tool arrives for a different slice. Then another. Each one genuinely useful in isolation. None of them talking to the others.

The result is that insight lives in one place, decisions in another, and delivery context in a third. A user interview gets summarised in your AI notes tool, the pattern gets spotted there, someone copies it into a Notion page, that page gets referenced in a Slack thread, and by the time it reaches a prioritisation conversation, half the nuance is gone. The handoff friction between tools has replaced the problem the tools were supposed to solve.

Shreyas Doshi put it clearly when he wrote about the difference between high-agency and low-agency ways of working. The tooling itself is not the bottleneck — the connective tissue between tools is. That gap is where PM time disappears in 2026.

The consolidation bet is real, but the fit is wrong for most European teams

The platforms repositioning as full PM operating systems — Aha!, Productboard, Pendo — have spotted the same problem. Their answer is to become the single layer that connects insight to decision to delivery. That logic is sound. Consolidation does win when the alternative is three disconnected tools each generating their own context.

But for lean European product teams, typically 20 to 200 people, those platforms bring their own problems. Enterprise pricing structured for US companies with large budgets. Data residency defaults that sit outside the EU. Onboarding complexity that requires a dedicated rollout to get value. My experience is that teams in this segment try one of these platforms, hit the complexity wall inside 60 days, and end up back where they started — except now they have a fifth tool on the stack.

Data sovereignty is worth naming explicitly here because US-centric tool comparisons almost always ignore it. For a European SaaS company handling user research data, product analytics, or customer conversations inside an AI platform, where that data lives is not just a compliance question. It is a product strategy input. Choosing a tool that requires legal to get involved every time you want to expand usage is a real cost, even if it does not appear on the product analytics dashboard.

The right question is not which tool to adopt next

The framing most teams use when they feel the sprawl is to evaluate more tools. Maybe there is a better AI meeting tool, a smarter roadmap assistant, a prioritisation layer that finally integrates with everything else. The search continues and the stack grows.

The question that actually helps is different: where does your team lose time between insight and action?

For most teams I've worked with, the answer is specific. It is not the meeting notes tool. It is the gap between what comes out of user research and what makes it into a roadmap decision. Or the gap between a validated opportunity and the delivery team having enough context to build it well. The AI layer that matters is the one that closes the specific gap your team has — not the one with the most features in a comparison table.

This means mapping your workflow before evaluating any tool. Write out what happens from the moment insight arrives to the moment a decision gets made and handed to engineering. Mark the places where context degrades or time disappears. That map tells you exactly where one well-chosen tool, or a deliberately simplified stack, would actually help.

Start with subtraction

Before you adopt the next AI tool, remove one. Pick the one your team uses least consistently, the one that requires the most manual work to connect to everything else, and turn it off for a month. See what you actually miss.

The teams pulling ahead are not the ones using the most AI tools. They are the ones who got ruthlessly honest about where their workflow breaks and fixed that specific break. Start there.