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Business AI Ads: Growing adoption ~70×

Year
2025
Company
Meta
Role
Lead product designer
Key details
Adoption strategy, Product design, Product management
Ads Manager's Advantage+ creative enhancements: five cards switched on, and Add Business AI, switched off, in the middle of them.
Snapshot

A new AI feature almost nobody had turned on. Six months later, adoption had grown ~70×. I ran the workstream as its designer and PM.

~70×
Adoption growth in six months
8×
Faster path to launch
3×
Initial opportunity after I expanded the scope

Business AI was live, but almost nobody was turning it on. The only entry point was an off by default toggle buried inside Ads Manager.

The places that could actually drive adoption required proof the product was too new to have. Waiting for that proof meant missing the goal.

I mapped every place we could put Business AI in front of advertisers, then worked with data science to size the opportunity. Eleven ideas became seven bets. Five didn't require proof, so we shipped those first.

I'd like to say that was strategy. Mostly, it was a cost decision.

Adoption grew ~70× over six months.

More importantly, the work gave us a repeatable path for getting new products into Ads Manager's highest impact recommendation surfaces. I co-wrote that approach into an adoption playbook now used by other teams.

Unlocked two high impact recommendation surfaces that had previously required proof we didn’t yet have.
Turned the approach into a reusable playbook, co-written with the team and now used by others launching new products in Ads Manager.
Started the work on a dedicated Business AI entry point, which became the next chapter of the product.

With no PM on the workstream, I took on product direction alongside design.

Mapped and prioritized the adoption strategy, working with the tech lead and data science to turn eleven possible levers into seven bets.
Designed the adoption experiences, from lightweight discovery patterns to the recommendation surfaces that became the biggest opportunities.
Wrote the requirements and decision docs needed to get the larger bets built and approved.
Ran each feature through launch approval, including making the case for a streamlined process when the standard path would take too long.
Expanded the opportunity, finding additional recommendation surfaces and sizing them with data science.
Turned what we learned into a playbook other teams could reuse when launching new products in Ads Manager.
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