Whether it's in the form of generative AI services, such as ChatGPT or Bing, or in machine-learning-led initiatives that allow organizations to undertake large-scale data analytics, AI is a step change in the way organizations use technology. Our businesses and the way we work for these companies are being changed forever.
The priority now is for enterprises to ensure AI is introduced in a well-governed manner. So, who should be responsible for making sure the business makes the most of AI? Should it be the CIO, the CDO, or someone else?
The bad news, according to industry experts, is that there's no straightforward answer.
"It's a really complex question," Lily Haake told ZDNET. Haake is the head of technology and digital executive search at recruiter Harvey Nash. She recognizes the increased use of AI comes at a time when the roles and responsibilities of CIOs and their IT teams are contested.
While CIOs have traditionally been the executives most likely to lead technology initiatives, there's been a shift during the past five or so years, where line-of-business managers have taken more responsibility for sourcing and procuring IT systems and services.
Cloud computing sits at the heart of this shift. Professionals across the business now use the cloud to buy technological solutions to their business challenges on demand.
In this era of decentralization, the key role of CIOs and their IT departments is to engage with the rest of the business, offer advice on technology purchases, ensure the right governance is in place, and build strong ecosystems of internal and external support.
The rapid rise of AI -- and generative AI in particular -- brings a further layer of complexity to this technology management conundrum.
And Haake says her firm's research suggests AI in most organizations is still at a nascent stage. "There's a chunk of organizations that haven't even considered AI," she says. "About 60% have piloted it in some way, but it's certainly not everyone."
In this preliminary phase of testing, it's more likely than not that the CIO picks up the leadership slack for all kinds of AI projects. There are some variations: In a large business with a mature data organization, the CDO might oversee AI on a day-to-day basis.
But even in these cases, the CDO is likely to report into the CIO, so the accountability for AI ultimately rests with the CIO. And, right now, given the uncertainty around how emerging technology is likely to be brought into the business, that's no bad thing.
"The CIO is the one executive who has the helicopter view of the different needs of the organization and, of course, AI has the power to impact every single facet of the business," says Haake. "So, we're tending to see the CIO in charge of AI. They want to be the person to control this area and have accountability for it."
But while CIOs are taking the lead for AI in many organizations, they're not the only people with an interest in the technology. Just as the cloud has allowed line-of-business professionals to expand their interest in technology, people across the organization are having a say on how AI is used.
Haake refers to this joined-up approach to AI as "a joint effort," which is a strategy that resonates with Avivah Litan, distinguished VP analyst at Gartner. "AI really is a team sport, so you can't just put it on one unit," Litan told ZDNET. "In fact, it's always been like that -- AI crosses business units. So, if you're talking about the opportunities or the risks, it's across the lines of business – its compliance, its privacy, its marketing, its customer service."
Véronique van Houwelingen, solution manager for conversational technology at Air France-KLM, also told ZDNET a joint effort is the best way to develop an enterprise-wide approach to emerging technologies such as AI.
"There are all kinds of initiatives going on in a big business like ours. So, how do you keep track of them?" she says. "If you see this happening, then a workforce or task force is key, because then at least you know what's going on in your company."
The message from industry experts is straightforward: For whoever leads AI developments in the longer term, every department must be involved in short-term discussions about how AI is applied to business use cases.
For example, HR will think about how AI affects job roles and retention rates, marketing will concentrate on content and personalization, and legal will focus on ethics and governance.
Take Carter Cousineau, vice president of data and model governance with Thomson Reuters, who explained to ZDNET recently how she's helping her firm reap the rewards from AI without taking risks. "When we look at responsible AI, we look at it for all of our use cases," she says. "So, whether it's in a testing phase or we're looking to actually create a true model and move it into production, there's governance and ethics stages that we put in place."
Some organizations, therefore, are already bringing different departments into the discussions around how AI is adopted and adapted. But one executive will still be expected to bring these cross-organization efforts together -- and most organizations will expect the CIO to fulfill this role, says Gartner's Litan.
"When you have your whole team working together across the organization, you end up with more proof of concepts moving into production," she says.
"But when it comes to the budget, if you put it with the CIO, then projects tend to move faster into production. What's happened with AI projects is that the higher up the budget goes, the better off the project is, which is not rocket science."
That's a view that chimes with Cathrine Levandowski, global head of operations at lifestyle management company Quintessentially. CIOs have oversight of all business operations, and their understanding of technology and data could prove crucial as AI begins to make its mark.
"Personally, I do think it should be the CIO. And I think that's because I feel like they have an overlapping view of, not only data, but also operations," she told ZDNET. "I think it's key that whatever AI decisions you make are operational because they should be positive for the business. We would want to use AI to enhance our operations and efficiencies."