Stop Chasing Every AI Breakthrough (What CIOs Should Do Instead)

Alexis Hueringa (0:00)

Welcome to Gartner ThinkCast. I'm Alexis Hueringa. Today, we're welcoming back Gartner Senior Director Analyst, Deepak Seth, for a follow-up on the state of AI. The last time Deepak joined us, we explored what comes next for Enterprise AI and the idea of AI-free trust revolution.

Since then, the AI landscape has continued to rapidly evolve with new models, new capabilities, and some major headlines competing for our attention. But beneath all that, business leaders are still asking some very practical questions. How should they make sense of the constant stream of AI news? What does all this mean for jobs and organizational structures? And as the cost of AI grows, how can they ensure they're actually getting value from the technology?

Deepak has been wrestling with these very questions as he prepares to present at this fall's Gartner IT Symposium Expo. So, Deepak, welcome back.

Deepak Seth (0:51)

Yeah, Ereksis, thanks.

Excited to be back again. And you're right, it means things are not only just been rapidly changing, they have been on what speed, especially with the announcements just coming out over the last few days about people leaving OpenAI and Anthropic and talking about how AI can bring an end to human civilization by the end of the decade kind of stuff. So, I think it's an opportune time to reflect and talk about what's going on.

Alexis Hueringa (1:17)

Yeah. So, last time we spoke, we were looking ahead at the future of Enterprise AI. We'd love to get your reaction and overall assessment of where AI stands right now, especially thinking about the agreed slowdown between biggest players. What else is going on?

Deepak Seth (1:29)

So, I think in the last session also I had spoken about how companies need to be grounded in their legacy systems. They should focus on the mission critical priorities of today, and they should have an eye out on the future kind of thing. So, there is no need for any company to be chasing the shiniest objects at every point of time. One thing which came up in conversations with and I was speaking with the CIO of leading my global mining organization recently, and I said, hey, for what you do, if you need a jeep or a Land Rover, or a big caterpillar truck, why are you worried about what's happening in the world of Ferraris and Lamborghinis? So, that part, that message, I think, it has resonated well with almost all clients. Like, hey, focus on fit-for-purpose models. Things will keep on changing in the ecosystem around you. There is still a lot of value, even if we leave the scary parts of AI aside, there's a lot of value to be realized even from traditional machine learning applications of AI.

Alexis Hueringa (2:38)

One thing we've heard repeatedly is that people feel overwhelmed by the pace of all this change. How should CIOs and business leaders stay grounded amidst all this AI chaos to exactly what you're saying, to focus on the exact models they're actually using?

Deepak Seth (2:51)

So a lot of it again means like any other technology in the past, it requires them to be very well grounded in all three dimensions. They are the people, the process, and the technology. On the people side means that people have a lot of fears around AI.

They need to assuage those fears. They need to follow an approach of making people realize that this is not something, means that fear which we talked about earlier, it's not going to kill them kind of thing. On the process side means even the fastest, if you think of the Indy cars or you think of Formula One racing cars, they have great brakes. The brakes are what enables them to get good speed. So braking and speed both go hand in hand with each other. So a lot of focus on governance would need to be there. And I remember talking about governance a bit last time also, where I said, hey, governance is not just about enforcement and compliance and controls.

Governance is as much about engagement and enablement. And I'll add another E to it, which is evidence. Yeah. So you in the engagement and enablement part, through literacy and other stuff, you are assuaging the fear of your employees. You're telling them what can work and what cannot work. What are the guardrails within which they have to operate. In the enforcement part, when you're getting ready to implement a production-wise stuff, you have to be mindful of making sure that things stay within the guardrails. Yeah, that's when you are making sure that everything stays within the policies and the controls. And then the evidence is observability of all as it is happening. If things go wrong, why did they go wrong? You need to have an evidence base for that. So all these three things will come into play.