AI is something that every business is using, and many have plans to get much deeper into it. At this point, which C-suite department tends to be handling AI in companies?

Hesters: At the first phase when AI showed up, everybody said, ‘AI is a thing. We must master this thing in order to become world class at whatever we do.’ Followed by, ‘We need a chief AI officer. We need a chief innovation officer.’ 

We’ve moved to phase two of that evolution. Companies are realizing what’s more important is creating the environment for individuals, departments, functions to evolve, and the mechanisms which allow them to do that. AI right now is a set of tools that we can all use to make us more efficient or produce a better product. The more sophisticated companies, the ones that are at the leading edge, have realized that the key is to let the individual employee have some authority to understand what might be able to help them do their job better. Then design the entire system to take these ideas, feed them into the system and be able to vet [privacy and security], but still allow for that micro-level innovation. 

It’s like crowdsourcing innovation inside a company. Leading companies have gotten over the arrogance that you could have one officer and one function inside a company to drive all of innovation for the company, when really it’s that 24-year-old that you just got out of the MBA program who says, ‘Hey, I heard about this new tool. Maybe we should look at it.’ 

What you’re seeing is the chief technology officer own the process. How do you set up the conditions inside a company that allow for good ideas to percolate and crowdsource? That’s the CTO’s job. 

If you have a chief innovation officer, their job is to prioritize what are the areas that we need top-level capital investment to innovate in. That’s the top-down approach. 

You’ve got a top-down/bottoms-up approach to AI now. The companies that are leading seem to be approaching it from that perspective. 

C-suite titles and responsibilities are always evolving. Where do you see AI going in terms of corporate responsibility? Do you see more chief AI officers in the future? Will AI get divided into different departments? Will it all come under the CIO?

You need leaders that understand that technology and innovation is not a nice-to-have. It’s required for survival in today’s environment. If they understand that, and are willing to try to adopt those potential efficiency gains in their functional areas and cross-functionally, you need to have the internal processes and capabilities to do it. You’ve got to have a chief person that knows how to conduct an innovation pipeline appropriately: responsible and safe and still allow a lot of freedom to innovate. They have to design the process, and then they have to have the actual systems in place. 

Let’s look at how much energy AI processes can utilize. Who owns that? If you all of a sudden are sitting on a bunch of data and you want to start crunching it and to use an AI tool, are you going to build your own data center? Are you going to co-opt it? Where do those energy prices go? Do you pass those onto your customers? Do you need it internally? What are you giving up to do that? There’s always a knock-on effect. It’s not just, ‘Look! We’ve got a new tool.’ When you want to roll out that new tool, that new way of doing business, you’ve got to bring all the other functional leaders into the room to look at the 360-approach to what it’s going to do.

The energy aspect of this is fascinating when you think about sustainability and how we tie it in. How do you ensure that the AI tools you’re using are not over-indexing some kind of bias that at a minimum is going to help you make poor decisions, but in a really scary world, create biases and risk and liabilities for your company? 

It’s almost foolish to assume you could appoint one person and call them the chief AI officer and it’s all going to be fine. It’s really got to be a management team mindset, and everybody’s got to be at the table. Then you’ve got to be willing to look externally as well. You’ve got to bring other stakeholders. 

What advice would you give to a CEO that is struggling with where to put AI leadership right now?

Don’t think about AI first. Think about what are the critical competencies that your organization has to have to achieve your strategy? That’s the answer to where we make investments in AI and innovation. You could outsource a lot of the secondary requirements and services your company has, but a CEO should be investing in the critical functions and capabilities it needs to achieve the strategy. When you’re looking where that extra dollar of investment goes, it should go to the tools and capabilities that allow you to achieve that strategy. 

It’s very easy to get distracted today. There’s so many cool products and AI tools out there that you could chase around, and at the end of the year have lots of new products that don’t really do much for your strategy. That’s the opposite of what a CEO should be doing. 

In the past six to eight months, we’ve looked at 40 different AI tools that could help us with our key critical functions. We’re staying focused on that. Only four or five made it through our innovation funnel, but that’s four or five different tools we’ve got that are really helping us execute for our clients the tasks that they’ve hired us to do. And we can do it with a much higher degree of quality and faster.