AI tools in digital product management: what is actually useful in 2026
Tom W Dixon · Senior Product Manager and Digital Platform Lead
AI tool adoption in product management sits somewhere between genuine productivity gain and security theatre, depending on how people are actually using it. The useful applications are narrower than the marketing suggests. But the narrow applications are earning their place.
Documentation and synthesis. Claude, Notion AI, and Atlassian Rovo are effective at turning a meeting transcript, a set of customer feedback, or a pile of research notes into a structured summary. This does not replace analysis. You still need to decide what the summary means. But it removes the mechanical overhead of organising information before you can think about it. For teams with high discovery velocity, that overhead adds up.
Writing first drafts. Acceptance criteria, brief templates, status updates, release notes. AI tools write fast, competent first drafts of anything that follows a known structure. The output needs editing. But editing a draft is faster than writing from scratch, and the discipline of reviewing an AI draft can surface gaps in your own thinking.
Exploring unfamiliar domains. When picking up a new product area, a new technology, or a new market, AI tools are useful for explaining concepts, mapping terminology, and shaping the right questions. They are less reliable when the question requires current or highly specific knowledge. Verify before acting on anything with real stakes.
Where they are not earning their place: strategic prioritisation, stakeholder relationship management, and anything that depends on organisational context the tool does not have. Rovo, which pulls from Confluence and Jira, gets closer to the latter than a general-purpose tool does. But it is still working from documented knowledge, not lived context.
The product managers getting the most from AI tooling are the ones who have a clear model of what requires human judgement and what is mechanical work that can be accelerated. The two categories are not the same size. Most of what gets called thinking in product management is actually information processing. That is where the tools are useful.