I’ll be honest with you — a year ago I was skeptical about AI tools for product managers.
Not because I didn’t believe in AI, but because most “AI for PMs” content felt like lists made for clicks, not for real work. So I did what any PM would do: I tested these tools inside my actual workflow — PRDs, roadmaps, stakeholder updates, research notes, and the messy in-between.
I’m writing this as someone who ships features at work, and also builds on the side — including a platform for gamers and iterate on like a real product (user feedback, content, SEO, continuous improvements).
Here’s what actually stuck.
Why AI tools matter (for PMs)
PM work is full of context switching. One minute you’re in a sprint discussion, then you’re explaining a tradeoff to leadership, then you’re writing a doc that needs to be “clear enough” for engineering and “simple enough” for non-tech stakeholders.
AI helps most when it removes the blank page problem and the “busywork tax”:
- Turning messy notes into structured docs
- Summarizing calls and threads
- Generating first drafts you can improve
- Speeding up research and comparisons (without you opening 20 tabs)
Used correctly, it doesn’t replace thinking — it buys you time to do more thinking.
My context (so you know where this is coming from)
I’m currently a Product Growth Manager, and I care a lot about building products, not just reporting numbers.
I also recently migrated my personal site (anukulsaini.com) from WordPress to Ghost CMS so I could ship faster, stay lightweight, and get out of the plugin/bloat trap. That migration pushed me into a more “product engineer” mindset: own the full experience, prototype quickly, and optimize end-to-end.
I’m also building an “AI Citations” style tool concept that checks where a website is mentioned across AI search assistants and gives suggestions to improve visibility. That project alone taught me how powerful AI becomes when you combine product thinking + research + automation.
The AI tools I actually use (and why)
1) ChatGPT — my thinking partner
I use ChatGPT the most, but not as an “auto-writer.” I use it as a thinking partner.
What it’s great at:
- Turning bullet points into a PRD outline
- Creating multiple positioning angles for the same feature
- Writing “first-pass” stakeholder updates I can tighten
- Stress-testing a roadmap decision by arguing both sides
How I use it: I give it context + constraints + audience. Then I ask for structure first (outline, headings, decision options), and only then ask for a draft.
2) Notion AI — where my docs live
If your docs already live in Notion, Notion AI is an easy win.
What it’s great at:
- Summarizing messy meeting notes into clear action items
- Turning scattered thoughts into readable docs
- Creating reusable templates (specs, retros, weekly updates)
It’s not magic — but it reduces the friction of documentation, which means you actually do it.
3) Perplexity — fast research with sources
When I need to research something quickly and I want citations/sources I can cross-check, I use Perplexity.
What it’s great at:
- Competitive research
- Market scanning
- Finding recent references without drowning in tabs
- Getting a quick “what’s the landscape?” answer before I go deep
This is especially useful when you’re writing a strategy doc and you need external context without guessing.
4) Gamma — decks without wasting your life
I used to lose hours making decks. Gamma makes it fast to go from outline → clean presentation.
What it’s great at:
- Roadmap/strategy decks
- Stakeholder updates
- “Here’s the plan” narratives
It’s not perfect for pixel-level control, but it’s perfect for speed.
5) Dovetail — turning interviews into patterns
If you do user interviews (or even internal stakeholder interviews), Dovetail can save you a lot of manual synthesis.
What it’s great at:
- Finding repeated themes
- Grouping feedback
- Summarizing what changed across conversations
PMs don’t lose time in interviews — they lose time after interviews, when insights stay trapped in notes. This helps unlock that.
6) Zapier (or automation in general) — the glue
Automation isn’t flashy, but it’s the difference between “we should do this” and “we actually do this.”
What it’s great at:
- Sending feedback to a central place
- Creating tasks automatically from forms/emails
- Keeping your workflow consistent
If you feel like you’re “copy-pasting your job” between tools, fix that first.
What I tried and dropped
Not everything is worth it.
- Tools that force a full workflow change just to use the AI feature (high switching cost).
- “PRD generator” tools that look nice but don’t beat a strong ChatGPT prompt + your own context.
- Anything that adds another subscription but doesn’t clearly save time every week.
My bias is toward a lean stack: fewer tools, deeper usage.
How to adopt AI without overwhelming yourself
Here’s the approach that worked for me:
- Pick one workflow (PRDs, research, meeting summaries).
- Use one tool for 2 weeks in that workflow only.
- Track whether it actually saved time or improved quality.
- Keep what works; drop what doesn’t.
- Only then add the next tool.
The goal isn’t “use AI.” The goal is “ship faster with less stress.”
The bigger shift: PMs who build will win
In 2026, the most valuable PMs aren’t just great at writing docs. They can prototype, automate, and ship MVP-level output faster.
That doesn’t mean everyone must become a full engineer. But having a builder mindset — and using AI to close gaps — is becoming a real advantage.
That’s the direction I’m personally leaning into: product thinking + execution speed + enough technical depth to move without waiting on a full team.
Bottom line
If you’re a PM and you feel like your days disappear into docs, meetings, and “alignment,” AI tools can give you time back.
Start with one:
- ChatGPT for docs and thinking
- Perplexity for research
- Notion AI for writing and structure
- Gamma for decks
- Dovetail for synthesis
- Automation to remove repetitive ops
Use them to remove friction, not to outsource judgment.
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