The Rise of the Chief AI Officer (CAIO)

**Ray Rike** (0:08)
Welcome back to another episode of the AI to ROI Big Story Edition. I'm Ray Rike, founder and CEO of Benchmarkit, and joining me as always is my cohost, Peter Buchanan.

**Peter Buchanan** (0:21)
Yep, I'm Peter Buchanan. I'm the founder of Newplan. It's great to be here. And today our topic is one our listeners have been waiting for, the rise of the Chief AI Officer.

**Ray Rike** (0:34)
That's right. This week's Big Story is focused on that rise of the Chief AI Officer, which, by the way, I'm just excited to see how this rolls out over the next one, two, three, to five years. But we're going to get a little help from IBM's Institute of Business Value, because they conducted a research that included almost 600 plus Chief AI Information Officers, or maybe I should say Chief AI Officers, across 22 geographies and 21 industries. The headline? That AI leadership is becoming non-negotiable for enterprises. So, hey, let's dive into our top five takeaways from this week's edition. Sound good, Peter?

**Peter Buchanan** (1:13)
It does. Sounds great.

**Ray Rike** (1:15)
Okay, so the first one we've kind of characterized under the chief AI officer gap is costing companies real money. So let's talk about what are the stats. So 26% of companies currently have a chief AI officer. And let's be fair, that's 26% of the 600 plus companies that IBM actually conducted a survey with. Now, the good news is that is up from 11% in 2023 So almost 2.5 times more. So the number is growing, but it also means that about three quarters of enterprises are still trying to operationally AI without a dedicated executive at the helm. And to me, Peter, that may create some issues. What do you think?

**Peter Buchanan** (2:05)
Well, I mean, the first thing is there's basically a price gap or business penalty attached to it. So companies with a chief AI officer get 10% greater ROI out of their AI spend. And that ROI goes to the bottom line or it goes to increased revenue or it goes to increased productivity. And they're 24% more likely to report outperforming their peers. So the ones that have gone to chief AI officer early are getting a competitive advantage against their rivals. It's sort of like the difference between using AI to win a cool science fair experiment competition in high school versus actually getting a meaningful competitive advantage that put your company ahead.

**Ray Rike** (2:56)
Well, for the AI to ROI podcast, it's really good to see this data. It sounds like maybe we named it right. And I really appreciated how, because you write a lot of the newsletter and this one from Monday, March 2nd. I love how you framed it that most companies don't lack AI ideas. What they lack is the ability to turn those ideas into projects, the transition to production scale initiatives to deliver measurable ROI. And often what was founded to research is that chief AI officer was the executive in charge of fixing that, in charge of fixing what hasn't yet turned into ROI.

**Peter Buchanan** (3:41)
Right. So now the question becomes, who becomes a chief AI officer? Where do they come from? So Ray, let's bust a myth here. These aren't techno geeks that have been in the lab, you know, coming up to go home to their families, and you never see them otherwise. When you hear that, you picture that, but they're actually coming from a different place. It's a different hiring area. So where do they come from?

**Ray Rike** (4:13)
Well, it makes sense that 73% of existing chief AI officers from this research had more of a data-focused background, data science, statistics, analytics, and some level of AI research. But it was clear that the most effective chief AI officers are truly hybrid leaders, equal parts business strategists and data scientists. So that's where it translates AI capabilities into that measurable business value and be able to communicate that value to the board and honestly to the investors. And to me, that's really important.

**Peter Buchanan** (4:58)
It is. And here's the part that's really interesting is 57 percent of the CAIOs in this category were actually promoted from within. They're not coming from outside. And so what enterprises are realizing is that cultural fluency and institutional knowledge really matter as much as technical expertise. Because a lot of these AI projects have succeeded, have failed to generate ROI or have crashed and been shut down because for business and cultural reasons as opposed to technology reasons. So the CAIO who doesn't understand the business is at a real disadvantage and it really hurts the enterprise.