AI Office Hours
Meet the Experts
Shapes company strategy in consultation with CoLab’s biggest customers.
Ex-iRobot ML & AI product leader holding 10 US Patents.
Runs AI readiness assessments for large engineering orgs.
Leads CoLab's AI product and knowledge model; ex-DarwinAI.
Leads CoLab's strategic initiatives; MBA.
Leads AutoReview, CoLab's AI design checker; ex-Tesla, patent holder.
Helps engineering teams apply AI to workflows; former Toyota manufacturing engineer.
1 million +
56+ years
9
The Full Series
Is your engineering data ready for AI, and how would you even know?
Many engineering organizations are hesitant to adopt AI out of fear their data isn’t ready. That’s a valid concern, but it shouldn’t prevent you from starting. This article covers practical ways to get your data AI-ready, and presents use cases to tackle right away.
Should a capable engineering organization just build its own AI?
Capable engineering teams can build valuable AI tools, and sometimes they should. What they tend to underestimate is the permanent work required to connect those tools to engineering systems, keep them current and secure, and create an experience engineers will actually adopt.
Why do I have to keep re-explaining my work to AI?
AI can only work with the context it receives or can access during execution. Here is why every new session feels like a reset, what that costs engineering teams, and the practical system leaders can build to carry knowledge from one task to the next.
Got a strategic AI question you want answered?
