• As companies deploy generative artificial intelligence, they're also adding new titles like chief AI officer. Doing so could be muddying already blurry waters.
• New research shows that employees are confused about where to turn for data and tech services and issues.
• Even leaders themselves often lack clarity about their own responsibilities, with nearly a third of respondents reporting they don't fully understand their roles in relation to other technology executives.

As businesses implement generative artificial intelligence, they're also adding new C-suite titles such as chief AI officer. But simply slapping on a new label to the organizational chart could be muddying already blurry waters.

According to a new study from Thoughtworks, whose authors include an MIT expert, 87% of people say employees in their organization are confused to a certain degree about where to turn for data and tech services and issues. Most of the organizations whose leaders responded to the survey had multiple executive roles in the tech and data spaces. This includes chief information, technology, data, information security, digital, analytics and AI officers, and sometimes more. Even those leaders themselves often lack clarity about their own responsibilities, with nearly a third of respondents reporting they don't fully understand their roles in relation to other technology executives.

John Spens, director of data and AI for the Americas at tech consultancy Thoughtworks, which co-authored the study along with IT experts from MIT, Babson College and the University of Arkansas, says this confusion makes sense given the trajectory of generative AI. He likens the technology to a hockey stick, where it touches so many parts of a technology organization from the data space to software, engineering and even client interaction. It's "an unsurprising result that people are confused about where this resides and who is responsible for it," he said.

Spens has been a data practitioner for more than 30 years, and this confusion is familiar to him. In the 1980s, CIOs were the big trend, then the 1990s brought popularity for CTOs, with other technology executive acronyms following suit.

"We've seen, as technology becomes more and more part of the business," said Spens, "the need for that responsibility to bleed out to another part of leaders, and the emergence of different leaders to address those issues." The AI renaissance of sorts exacerbates the situation, he says.

Supertech superstars

Just because Spens expects confusion about who to report to in the tech leadership space doesn't mean he thinks businesses should accept it. "It's something that organizations need to think about seriously," he said.

As generative and other types of AI increasingly become organizational underpinnings, the conversation around who will own the various aspects of it may spark a new conversation around a company's overall architecture.

Spens says identifying so-called "supertech leaders," or integrated technology leaders that combine at least two traditional tech titles into one, is key. Supertech leaders are "heavily business-oriented, with a technical underpinning," according to the report. Spens goes further by describing this person as an opinionated interpreter between the business and technical ends of the spectrum. More than anything, they're advocating for the different sides of the organization and generating "enthusiasm at the executive levels, enthusiasm at the team levels, and getting the technologists to work together more effectively and achieve the business outcomes," he said.

Keith Ferrazzi, speaker, founder of Ferrazzi Greenlight and author of books including "Never Eat Alone" and "Never Lead Alone" says the issue of confusion about who to report to on the tech side boils down to a lack of coordination.

"Teaming has nothing to do with org charts. It has nothing to do with titles," said Ferrazzi. "It has to do with, we should be aligning our work around key KPIs [key performance indicators]. We should be aligning our work around initiatives. We should be aligning our work and therefore our teams around the work itself. And that's anybody's job."

Ferrazzi believes adding a new role in and of itself doesn't get anything done. To be productive, whether it's around AI or another initiative entirely, "requires anybody who has a horse in the race to be responsible for stepping up and co-creating, coordinating and managing across the silo," he said. "Drawing boundaries in org charts is a recipe for failure."

Ferrazzi is referencing a popular business methodology dubbed "agile," which McKinsey & Company defines as "a way of working that seeks to go with the flow of inevitable change rather than work against it." The framework has been around since 2001, when software developers published the "Manifesto for Agile Software Development," which prioritizes things like "responding to change over following a plan" and "individuals and interactions over processes and tools."

Spens advocates for agile, too. "You need a little bit of that bureaucracy for people to feel comfortable and know what their responsibilities are," he said. "But the more that you can break that down, the more that you can enable people to collaborate together and drive some of the greatest outcomes."

In Ferrazzi's new book "Never Lead Alone," he looks at a concept he calls "teamship," in which organizations shift "from traditional hierarchies to teammates co-leading teams," he writes. Functioning at maximum capacity, Ferrazzi has found that teamship can free up to 30 percent of a leader's time. This in and of itself could minimize the need for more tech executive labels.

Ferrazzi has coached companies like Unilever and Lincoln Financial Group, and even national governments like that of Bhutan, on how to incorporate this thinking. Key factors on well-functioning organizations, he writes, include decision governance ("who will drive the process, who will be consulted, who will be informed, and who will make the final decision").

For example, Amazon is one company that uses a framework called DACI (driver, approver, contributor, informed) to clarify every individual's role and decision-making responsibilities. This eliminates confusion and maximizes efficient collaboration.

A solution to organizational confusion — for now

The reality is that businesses are confusing their employees with too many tech executive labels — and new roles, like CAIO, are threatening to ambiguate roles further. But agile, consolidated architectures can change that. What Ferrazzi calls "teamship ambassadors," or what Spens refers to as evangelists, can help propel the new way of doing things. Whatever you call it, Spens says not to get too comfortable in your newfound functionality.

"You never have the perfect model," said Spens. "You should never think, 'Okay, I've solved the problem.' You should think, 'I've solved the problem now.'" As businesses continue to grow, and as technologies continue to evolve, a reset may be in order. With AI's quickly evolving nature, Spens added, "Don't rest on your laurels. Expect that next change to come along that's going to put a kibosh on your beautiful model."