Consolidating tech executives: Is there too many chiefs?

• The addition of new titles like chief AI officer as companies deploy generative artificial intelligence could further complicate the already confusing landscape.
• Recent studies indicate that workers are uncertain about which resources to rely on for data, technology, and problem resolution.
• Nearly a third of technology executives surveyed admit to not fully understanding their responsibilities as leaders, despite being leaders themselves.

As businesses adopt generative AI, they are also introducing new C-suite positions such as chief AI officer. However, adding a new title to the organizational chart may only complicate an already confusing situation.

A recent study by Thoughtworks, which involved an MIT expert, found that 87% of people in organizations are somewhat confused about where to turn for data and tech services and issues. The study also revealed that most organizations with tech and data leaders had multiple executive roles in these areas, including chief information, technology, data, information security, digital, analytics, and AI officers. Additionally, nearly a third of respondents reported not fully understanding their own roles in relation to other technology executives.

John Spens, the director of data and AI for the Americas at tech consultancy Thoughtworks, which collaborated on the study with IT experts from MIT, Babson College, and the University of Arkansas, explains that the confusion surrounding generative AI makes sense due to its wide-ranging impact on technology organizations. He compares the technology to a hockey stick, affecting various aspects such as data, software engineering, and client interaction. As a result, it is unsurprising that individuals are unsure about where it belongs and who is responsible for it, he says.

Spens, a data practitioner with over 30 years of experience, is familiar with the confusion surrounding technology executive acronyms, as CIOs were popular in the 1980s, followed by CTOs in the 1990s, and other acronyms emerging in their wake.

As technology continues to play a larger role in business, the responsibility for addressing related issues is shifting to leaders, according to Spens. He believes that the AI renaissance has only intensified this need.

Supertech superstars

Spens believes that businesses should take seriously the issue of confusion about who to report to in the tech leadership space, despite his expectation of it.

As AI technology continues to be integrated into organizations, discussions about ownership of its various components may lead to a broader discussion about a company's overall structure.

According to Spens, identifying supertech leaders, who combine at least two traditional tech titles into one, is crucial. These leaders are heavily business-oriented with a technical underpinning. They act as an opinionated interpreter between the business and technical ends of the spectrum, advocating for both sides of the organization and generating enthusiasm at the executive and team levels. They also encourage the technologists to work together more effectively and achieve the desired business outcomes.

According to Keith Ferrazzi, founder of Ferrazzi Greenlight and author of books such as "Never Eat Alone" and "Never Lead Alone," the issue of confusion regarding who to report to on the tech side can be attributed to a lack of coordination.

"According to Ferrazzi, teaming is not about organizational charts or titles. It's about aligning our work around key performance indicators, initiatives, and the work itself. This is everyone's responsibility."

To be productive, whether it's related to AI or any other initiative, it's essential for anyone with a stake in the project to take responsibility for collaborating, coordinating, and managing across departments, according to Ferrazzi. He believes that defining roles in an organizational chart can lead to failure.

Ferrazzi is discussing the agile business methodology, which McKinsey & Company defines as a way of working that adapts to change rather than resisting it. The framework was first introduced in 2001 with the publication of the "Manifesto for Agile Software Development," which emphasizes values such as flexibility and collaboration.

Spens believes in agile too. He stated, "Although a little bureaucracy can make people feel comfortable and secure about their roles, it's essential to minimize it as much as possible to foster collaboration and achieve exceptional results."

In his new book "Never Lead Alone," Ferrazzi explores the idea of "teamship," which involves teams working together as leaders rather than traditional hierarchies. By doing so, Ferrazzi has found that up to 30 percent of a leader's time can be freed up, potentially reducing the need for more tech executive labels.

Ferrazzi has advised companies such as Unilever and Lincoln Financial Group, as well as national governments like Bhutan, on how to implement this approach. According to him, key elements of successful organizations include decision governance, which involves determining who will drive the process, who will be consulted, who will be informed, and who will make the final decision.

DACI is a framework used by Amazon to clarify roles and decision-making responsibilities, which eliminates confusion and maximizes efficient collaboration.

A solution to organizational confusion — for now

Businesses are confusing their employees with too many tech executive labels, and new roles like CAIO are threatening to further ambiguate roles. However, agile, consolidated architectures can help resolve this issue. Ferrazzi calls these individuals "teamship ambassadors," while Spens refers to them as evangelists. Regardless of the title, Spens advises not to become too comfortable in your newfound functionality.

"Spens stated, "You never have the ideal model, and you should never assume you've solved the problem. Instead, always think, 'I've solved the problem now.' As businesses expand and technology advances, a reset may be necessary. With AI's rapid evolution, Spens emphasized, "Don't become complacent. Expect the next change to disrupt your perfect model.""