We all know AI is the big dog in tech right now. It was mentioned in 35% of all PlatformCon content after all. Organizations are racing to integrate AI features, and platform teams are feeling the heat in a huge way. Everyone from the C-suite to product owners is demanding AI-enhanced tools and workflows.

My friend Ben Potter from Coder (Def one of the best people to learn from in the community) breaks down this exact phenomenon, and what needs to be done in his new article, ”The rising pressure on platform teams to operationalize AI”. 

Here are some of the challenges he highlights. Sound familiar?

• From AI POCs to production: What starts as an LLM hackathon ends with leadership asking, “When’s this shipping?” But most (all?) teams lack the actual foundations for their platforms.
• Security & compliance pressure: Training and serving AI models create new risks. Sensitive data, proprietary models, and shadow deployments, platform teams suddenly become the gatekeepers of AI risk management.
• Developer productivity vs. AI sprawl: Ironically, trying to help developers with AI often slows them down. Poorly integrated tools and unclear ownership lead to friction rather than flow.

Not everyone is struggling, though. The platform teams that are successfully managing this pressure and operationalizing AI all share similar characteristics.

Go check out what they are.