If we don't have an AI team, who is responsible for AI?
I've been thinking about this question a lot lately. Hiring AI specialists and creating a new team isn't always an option. So how can an organization successfully adopt AI without creating a new team?
As a central data team, we use a hybrid data mesh approach. We provide the central platform and governance, while data engineers and analysts sit in the business domain teams. The central team enables. The domains own their data products.
Why shouldn't we apply the same principle to AI? AI Mesh!
Imagine a similar model:
- The central team provides shared capabilities, technical guidance and security guardrails.
- Business teams identify and own their AI use cases, because they understand their processes and challenges best.
- Employees have the space to experiment, learn and discover where AI can help.
- The organization provides clear rules about what's allowed, what needs approval, and who is accountable.
The goal isn't to build another team or put every AI question on the data team's desk. It's to make AI adoption possible across the organization, with the right support and responsibilities in place.
I am curious: how does this work in your organization? Do you have a dedicated AI team, does the data team enable adoption across the business, or are you still figuring it out?
This is part of my "100 Days of Year One" series. Follow along as I share what I've learned in my first year as Head of Data and Cloud.