The widespread adoption of artificial intelligence and generative AI has many organizations wondering if a chief AI officer is needed. Gartner has found that each time there is a disruption, or new era of technology, another C-suite role is not necessarily warranted. This is the case with the role of the CAIO.

Though it is not necessary for organizations to implement a CAIO, they should have a dedicated role for enabled, empowered and enforced execution of a business strategy infused with AI. Rather than focusing on creating a new job title, or role, organizations should be focusing on the value of AI.

Why organizations should have a head of AI rather than a CAIO

A seat at the C-suite level takes years to build up to, embrace and justify. Not to mention, there have been times where a hasty C-suite role has been created. This was seen with the creation of roles such as the chief digital officer. Successful C-suite leader roles that are now mainstream, such as chief information security officers and chief information officers, involved over a decade of evolution.

C-suite members take direction from their board of directors, and most boards do not currently want to expand the C-suite. However, they do want a responsible leader when it comes to their organizations’ AI orchestration. Because of this, many organizations have already appointed a head of AI already within the business — such as the CIO, someone who reports to the CIO, chief technology officer, chief data and analytics officer or the chief of strategy office — who is responsible for the implementation and expansion of AI-focused plans and projects.

The reality is that organizations are still debating where the responsibility for AI and gen AI initiative lies. Organizations’ CIOs have become the de facto head of AI. In fact, Gartner has found that 51% of CEOs expect their CIO or tech leader to unlock the value of gen AI to the business.

Organizations must have a business strategy infused with AI

Given the speed of AI updates and changes, it is imperative that organizations operate in a dynamic, iterative, risk-adjusted, repeatable approach to better focus on the value that AI can bring to their organization. The key is a synergistic multidisciplinary approach to measurement, AI-ready data strategy, security, risk governance and talent shifts.

The C-suite must ensure empowered, enforced and enabled organizational constructs to drive success. This entails several critical success factors:

• Aligned business strategy: The impact of AI and gen AI is proportional to organizations’ willingness to rethink and recalibrate their business. The head of AI should build a value story tied to the organization’s business strategy. This should be a narrative that illustrates progress toward business outcomes.
• Orchestration: Orchestration involves harnessing the people, processes, technology, data and trust as one seamless powerful, collective force to deliver and sustain many concurrent AI and gen AI initiatives. The learning curve of AI and gen AI is incompressible and consequences can often be outside the wall of the organization. Additionally, there are limited years of experience when it comes to the talent arena of AI and gen AI. Because of this, orchestration, alignment and effective communication is critical.
• Multidisciplinary governance: AI leaders must facilitate governance across increasingly interconnected, fast-changing terrains to support business outcomes. Aligning different governance domains helps organizations identify gaps, overlaps, conflicts and synergies among different governance efforts. Decisions regarding assets, behaviors and risks in one area of the business increasingly impact other parts.

Technology-oriented decisions about AI and gen AI are not just a technology decision, they are a simultaneous business, technology, economic and ethical decision.

An example of an area that traverses both business and technology is data and analytics. The D&A function is a combination of data (the “fuel” for a select number of AI and gen AI initiatives) and analytics that proves the key ingredients for data-driven decision-making enablement. This accentuates the challenge of high-value, high-impact areas that demand a blend of business, functional and technology depth.

Gartner has found that 96% of organizations’ data is not AI-ready. This demonstrates a dire demand for rigor and discipline in the areas of strategy, leadership, organization and talent to deliver business results.

Establishing an aligned business strategy, orchestration and multidisciplinary governance is not a onetime task. It requires multidisciplinary teams to iteratively revisit each item, dynamically adjusting using a risk-adjusted repeatable approach.

Focus on the value of AI

Given these insights, the focus of AI should be a synergistic multidisciplinary approach to shapeshifting organizations’ future. AI and gen AI are unlike other technology disruptions. The level of ubiquity coupled with the capacity and capabilities are so extensive and complex that it is difficult to scope efforts as well as capture the risks and unintended consequences.

The reality is that AI and gen AI are extensions of an enterprise technology roadmap and toolbox of options to solve business problems. However, AI and gen AI are much more powerful than other tools; they transcend the arena of technology as entire products, services and business models and can be built in a way that at times has not been fully understood and tested. Despite this, they are fundamentally focused on addressing business problems and demands and delivering value.

AI should no longer be treated as just a technology. It is now in a place where it shapes society and impacts what it means to be human. Therefore, organizations must extend existing governance practices with AI-specific considerations.

This is where an existing leader in the company is so key to the growth of AI and gen AI in the company. They must focus on a business strategy that is infused with AI rather than an AI technology roadmap masquerading as a strategy. There will be many concurrent AI and gen AI initiatives that require functional, technical, security, D&A and many other organizational resources. All of them need to be orchestrated together for success.

Frances Karamouzis is a distinguished VP analyst in Gartner Inc.’s Research and Advisory Group focusing on artificial intelligence, as well as the business and IT services that drive outcomes. Gartner analysts will provide additional analysis on AI strategy and leadership at Gartner Data & Analytics Summit, taking place March 11-13, in Orlando, Florida.

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