Do you Really Need a Chief AI Officer—or are you Skipping the Basics Again?

If you have spent any time in the data world, the current surge in hiring Chief AI Officers (CAIOs) might feel like déjà vu.  Companies are spinning up separate AI organizations, sometimes folding their data teams in, sometimes keeping them apart. Sound familiar? It should. 

Not too long ago, many of these same companies went all-in on data science before they thought about the state of their data foundations. That’s how we ended up with the infamous stat that 80% of a data scientist’s time is spent cleaning and fixing data. Back then, data science was cool. Now AI is even cooler. But how many times are we going to rebrand the same core challenge?

Here’s the perspective I keep coming back to: AI is a data capability. Especially when we’re talking about AI that can truly differentiate your company, not just giving everyone access to an in-house chatbot. And what do Chief Data Officers (CDOs) do? They build data capabilities. The great ones build them in the service of solving business challenges. If I were advising a CEO trying to decide whether they need a CDO, a CAIO, or a combined CDAIO, here’s where I’d focus:

1. Data management: the fundamentals still matter

Structured and unstructured data doesn’t magically manage itself. The same old friends—master data management (MDM), metadata, governance, data quality, records management—are as critical as ever. Without them, AI will struggle to scale and deliver value.

2. AI ethics: can we, and should we?

AI opens up new possibilities, but also new risks. 

Are we confident we have the rights to use the data the way we plan to? 

Are we thinking about bias and unintended consequences? 

Who’s accountable for making those calls?

3. Business alignment: why are we doing this?

The most important question: how will this move the business forward? 

Whether the leader has “Data,” “AI,” or both in their title, the goal must be delivering business outcomes—not shiny proofs of concept. This isn’t about titles. 

It’s about recognizing that AI is part and parcel of data capabilities. If your data foundation isn’t there, a CAIO won’t be a silver bullet. And if you do have strong data capabilities, then AI is a powerful new layer in your capability stack.

So, the real conversation isn’t CDO vs. CAIO vs. CDAIO.  It’s – Do we have the right capabilities and the right focus to actually deliver value with AI? 

What are you seeing in your organization or industry?  Is your data team getting folded into AI, or standing apart? Let’s compare notes—drop a comment or message me directly.

Stop Chasing Titles. Start Building Capabilities.

AI without strong data foundations is just expensive hype.