Does your organization have a chief AI officer (CAIO), or does it need one? I have strong opinions on this matter, believing that most organizations should rely on existing C-level executives to lead AI strategy and collaborate on initiatives.

One of the running jokes at the weekly Coffee With Digital Trailblazers is the number of new C-level titles that gain traction. We recall the debates on when organizations need chief digital officers and whether the ‘I’ in CIO should stand for information, integration, or innovation.

Why adding a chief AI officer may be a mistake

Last week, I wrote about the disastrous ROI problem with genAI and shared findings from three prominent research papers. According to the AWS Study Generative AI Adoption Index, “Organizations are rapidly consolidating AI leadership, with 60% already having appointed CAIOs and another 26% planning appointments by 2026.”

I was shocked by this revelation, especially since this same report stated that just 14% of organizations have a change management strategy. While organizations are shedding middle management, they are opting to add to their executive ranks.

Organizations may be repeating mistakes they’ve made in the past. Many added data, product, digital, and other officers to “partner with CIOs,” aiming to address strategic alignment and implementation challenges. Some CIOs in larger enterprises added these C-level roles as direct reports, which can work when there’s a healthy balance of alignment and diversity of thought. In general, adding more chiefs tends to magnify the alignment questions and can create chaos when C-level leaders disagree on implementation practices.

Now, if you are a CAIO, your first responsibility is to develop relationships with the other C-level leaders and debate responsibilities and strategy. And if your organization doesn’t have one, it’s up to the CIO, CISO, and other C-level leaders to do the same thing.

What CIOs need to lead AI in their organizations      

I’m opinionated and believe that most organizations shouldn’t need CAIOs. Here’s what’s needed:

• CIOs must step up in delivering business value from AI and lead the evolution of genAI in digital transformation strategy.
• Chief data officers should increase the scope of data governance to include AI governance.
• CISOs must partner with legal, risk management, and privacy officers to define guardrails and policies for using LLMs and avoiding rogue AI agents.
• All three leaders must have a comprehensive understanding of the end-to-end business, from sales to operations, including an understanding of the underlying workflows, data, experiences, and transformation opportunities.  
• All three roles must understand the regulations, compliance, brand risks, and employee concerns relating to AI and data security.

Like most digital transformation initiatives, delivering customer experiences and the future of work using AI requires a significant change management effort. So rather than adding a CAIO to the mix, my strong recommendation is that existing C-level leaders need to up their collaboration game and develop a people-first implementation plan.

CIOs must adapt to added AI responsibilities

I asked some experts for their opinions about the CAIO role.

“The question isn’t whether organizations need dedicated CAIOs, but whether existing leadership can adapt quickly enough,” says Bruno Kurtic, co-founder and CEO of Bedrock Data. “CIOs are naturally positioned to lead AI initiatives, given their oversight of enterprise infrastructure and data flows that AI depends on.”

So I agree with Kurtic, but this can be a steep challenge for CIOs. I used to joke that CIOs knew more about the servers running the databases than the underlying data models and pipelines. CIOs who fail to learn about AI capabilities and where to prioritize implementations may find that AI is the end of IT as they know it.

CIOs must also up their collaboration and relationship-building skills with other C-level leaders.   

“Successful AI implementation requires security leaders as strategic partners, not afterthoughts,” adds Kurtic. “CIOs bring operational understanding, while security leaders ensure governance frameworks keep pace with AI deployment. This partnership becomes even more important as AI touches every business function, from data classification to risk management. The most effective approach combines CIO execution authority with security leadership’s risk perspective.”

Arguments for why and when organizations need CAIOs

Alas, I was overruled by several experts who weighed in on the debate and believe CAIOs are important new roles. Here is their rationale.

1. CAIOs should own an AI-first strategy from CX to EX

“As AI becomes an intrinsic business enabler, leadership must evolve beyond siloed tech functions,” says Varun Goswami, head of product and AI of Newgen. “The chief AI officer symbolizes a mindset shift where AI is deeply embedded into product, process, and platform thinking. With evolving business priorities, a clear AI charter is important that integrates AI with the existing ecosystem.”

2. AI requires evolving implementation practices

Alejandro Ruperti, senior product manager of AI at Kandji, says, “In larger enterprises, leadership tends to be more structured. I think of it as a pyramid: at the top, a CAIO works closely with the CEO to set strategy and direction. In the middle, CDOs and VPs of engineering translate that strategy into systems and roadmaps. And at the base, AI leads execution on the ground. This layered approach is critical. Without role separation and clear ownership, large organizations can struggle to scale AI initiatives effectively.”

3. CAIOs guide scaling AI capabilities and governance

“As AI shifts from content generation to autonomous decision-making, enterprises need leaders who can ensure systems behave safely, securely, and transparently in production,” says Manoj Saxena, founder and CEO of Trustwise. “Emerging roles like chief AI officers and chief trust officers are becoming critical, particularly in regulated industries such as banking, healthcare, and insurance. Unlike traditional CIOs and CDOs who focus on infrastructure and scale, these leaders bring cross-disciplinary fluency to turn AI policies into operational guardrails across departments. They bridge the gap by “speaking AI” to tech teams, compliance to legal teams, and business value to boards.”

Is the trend to CAIO different?

These are all good points, and I agree with them, except to say that top CIOs will step up and lead the organization through these challenges.

Let’s shuffle the drivers:

• Say I replaced “AI” with “tech” or “cloud” in these three points. There would be little argument that “CIO owns a cloud-first strategy from CX to EX” or CIOs guide technology scaling and governance.
• Replace AI with data, and this became the heart of the debate of CIO versus a CDO (data), with the best balance, IMHO, is when the CDO (data) reports to the CIO.
• Replace AI with digital, and this drove the debate in some organizations about whether they needed a chief digital officer, rather than the CIO leading a product management-based IT organization.

I am certain that there will be ongoing debate about whether CAIOs are needed, who they should report to, and how C-level leaders define their AI-related responsibilities. Just remember that it takes a village to drive transformation. To deliver business value, the C-level leaders involved will need to focus on leading change.

 At StarCIO, we deliver center of excellence programs that focus on developing leaders and implementing transformational best practices tailored to the organization’s goals, culture, and staffing needs. Our approach encompasses a combination of leadership, learning, and advisory programs that guide teams in developing standards, cultural principles, AI innovations, and excellence with technology platforms. Contact StarCIO to learn more about our programs.