AI Tools for Product Managers
Navigate the AI tools that are most useful for PM work and build a simple, effective AI toolkit without the tool paralysis that slows many teams down.
In practice: Discovery synthesis: 2 weeks → hours
Step 1 of 4
Read
The PM AI Toolkit
You don't need many tools. The risk is spending more time evaluating and switching tools than doing the actual work. Most PMs can build an excellent AI workflow with three to four tools.
Tier 1: General-Purpose AI (Essential)
Claude or ChatGPT — Your primary AI assistant for writing, analysis, synthesis, and brainstorming. These are the workhorses. Either works; pick one and build fluency with it rather than switching constantly.
Use for: PRD drafting, user story writing, one-pagers, meeting summaries, research synthesis, competitor summaries, brainstorming.
Tier 2: Specialised PM Tools (High Value)
Dovetail / Maze / Notion AI — Research synthesis tools that integrate with your existing research workflow. Dovetail specifically is built for qualitative research analysis and tagging at scale.
Linear / Jira AI add-ons — Some PM tools now embed AI for ticket writing, sprint planning, and backlog management. Check what's available in your existing tools before adding new ones.
Tier 3: Analytical AI (Situational)
Perplexity or Claude with web access — For competitive intelligence that needs current data. General-purpose LLMs have training cutoffs; web-enabled tools can access current product announcements and competitor updates.
ChatGPT Data Analysis / Claude with CSV — For lightweight data analysis when you don't have data team support. Paste a CSV and ask questions.
Tool Selection Principles
- Start with what you have. Many organisations have ChatGPT Enterprise or Claude Team. Use those before adding new tools.
- Integrate, don't parallel-process. AI tools you use inside Notion or Linear are less disruptive than switching to a separate browser tab.
- Build fluency before variety. You get more from knowing one tool deeply than from knowing five tools shallowly.
The prompt
Claude's response
Quick check
Your organisation has ChatGPT Enterprise approved. You've been using Claude personally. A new research synthesis tool also looks useful. What should you do?
Key Takeaways
- 1A two to three tool stack (general AI + research tool + existing PM tool integrations) covers most PM AI needs
- 2Build fluency with one general-purpose AI before adding specialist tools
- 3Many organisations already have enterprise AI access — use what is approved before adding unapproved tools
- 4Integrate AI into existing workflows rather than creating parallel processes
- 5Web-enabled AI tools are better for competitive intelligence that requires current data
Your challenge this week
Apply what you learned in a real task
Audit your current AI tool usage: list every AI tool you've opened in the last two weeks. For each, write one sentence on the specific PM task it helps with. Identify any tools with overlapping use cases, then pick the one to stop using. Build fluency in the remaining tools by using each for a specific task this week.
Before you practise
How many AI tools have you tried in the last six months? Of those, how many are still in your regular workflow? What does that ratio tell you about your tool adoption strategy?
Next step
Put it into practice
You've read the lesson — now apply it in a guided hands-on exercise. It takes about 5 minutes.