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How to Hire – and When to Fire – a Chief AI Officer




Generative AI is quickly becoming part of corporate agendas worldwide. Nevertheless, most organizations are still struggling to get their GenAI operations up and running.

A recent Accenture survey revealed that only 27% of executives are in a position to scale such capabilities. Indeed, more than 70% are still at square one, trying to determine how to best leverage them. As a result of this current lag in AI readiness, a new corporate role has emerged: the Chief AI Officer (CAIO).

However, the ins and outs of GenAI as a business solution will eventually catch on, much like the Internet did; companies and their employees will adapt to new technologies, best practices will be established, and regulations will be set in place.

While CAIOs are indeed essential in facilitating and resolving critical AI deployment over the next few years or so, the role will eventually grow redundant. Given the inevitable maturation of GenAI, this latest C-suite position is all but temporary.

Popularity Contest

Many mid to large-sized companies have found themselves unprepared to scale GenAI technologies. 11% have responded by appointing a CAIO while another 21% (and growing) are actively seeking one out.

Top tier media including BloombergBusiness Insider, and Forbes have covered the rise of this new position – the New York Times even went as far as declaring it the “hottest job” in corporate America. Still, the actual responsibilities of a CAIO remain quite ambiguous. Job descriptions often include vague language like “You’ll be in charge of integrating AI strategies, deploying AI, and mitigating AI risks.”

Top 3 Considerations

In reality, the responsibilities of a Chief AI Officer can be divided into three main considerations – the first of which pertains to the kinds of AI solutions currently available.

GenAI tools are improving every week; it’s crucial for the AI executive to have their finger on the pulse of the current offerings and prices in the AI marketplace. Additionally, knowing which AI solutions offer a steady product development cycle is critical information when contracting an AI vendor. A CAIO must also supervise the deployment of any such solution across the entire organization.

Second, CAIOs need to determine the AI solutions that are most relevant for each department. Every department has its own unique tasks and objectives, and therefore will require different AI tools. Thus, a CAIO needs to foster open communication with department heads to best assess the most cumbersome, time consuming, and error-prone challenges facing each department, as well as the active AI tools which can best streamline those tasks.

Moreover, it’s the CAIO’s responsibility to ensure employees are proficient in using these AI tools. According to a recent report, only 35% of workers say their employers provide the necessary tools for AI adoption – even fewer receive usage guidance (29%) or requisite training (22%). To this end, CAIOs must bolster the adoption rate of AI amongst employees as well as the company-wide impact these solutions yield – such as cost savings, time-to-market, revenue, and net promotor scores.

The third consideration concerns awareness of AI regulations. A vendor’s solution can be the gold standard, offer competitive pricing, and align perfectly with a company’s objectives – only to be rendered undeployable in the face of newly established regulations. AI regulation is in its infancy, and GenAI technologies will surely be impacted by emerging rules. For this reason, it is critical that CAIOs stay abreast of AI regulations and take current trends into account throughout the process of choosing the right AI solutions.

When to Let Go

While CAIOs are key for companies looking to overcome hurdles and expedite AI integration into office workflows, their services won’t be necessary forever. Once core integrations have been established – CIOs and CISOs should be able to take the reins, curtailing the continued need for a CAIO.

But at what point does a company know when this point has arrived? It's important for companies, while remaining flexible as the technology continues to evolve, to establish benchmarks and milestones from the get-go in order to measure the progress of their newly appointed CAIO—and determine if the point has come to begin phasing them out.

Measuring Progress

Setting up clear benchmarks and milestones from the beginning ensures that the CAIO’s contributions are measurable and aligned with the company’s strategic goals. For instance, these could include achieving a specific level of AI integration across departments, demonstrable improvements in operational efficiency, compliance with new AI regulations, or significant advancements in employee AI proficiency. Each milestone should be specific and quantifiable, such as reducing operational costs by a certain percentage or achieving a set rate of AI adoption across various business units.

With these milestones in place, not only can a company gauge the progress of AI integration, but also strategically plan for the future without depending solely on the CAIO. This foresight is critical as it provides both the CAIO and the company with a clear view of the role's trajectory and potential sunset.

Planning for the Transition

With established benchmarks and milestones, it’s also crucial to have a transition process ready when those targets are met. This process involves a structured handover where the CAIO collaborates closely with the CIO and CISO to ensure a seamless transfer of duties. Essential elements of a successful transition include:

  • Knowledge Transfer: The CAIO should ensure that all AI-related strategies, projects, and operational knowledge are thoroughly documented and shared with the CIO and CISO.
  • Advisory Role: Transitioning from a direct management role to an advisory role can help maintain continuity and stability. The CAIO can support the CIO and CISO by providing insights and guidance on AI-related matters as they take over the reins.
  • Monitoring and Adjustments: Post-transition, it’s important to monitor the outcomes and make adjustments as needed. This ensures that the integration of AI continues to meet the strategic goals without the CAIO’s direct involvement.

By planning for the eventual transition of the CAIO’s responsibilities to other C-suite executives, companies can ensure that their investment in AI governance and integration delivers sustained value over the long term. This strategic foresight not only optimizes the contributions of the CAIO but also enhances the overall resilience and adaptability of the organization in the face of evolving AI technologies.

The Clock is Ticking

The competitive implications of emerging AI technologies can’t be ignored. For companies struggling to get a grip on GenAI, hiring an executive dedicated to extracting value from the red-hot tech is a practical, strategically sound move – as long as their role is clearly defined and aligned with a company’s mission and objectives.

However, as was the case for Chief Metaverse Officers or Chief Digital Officer positions, the role of the CAIO is on track to become redundant within the corporate hierarchy. Companies must therefore be ready to undo the role of a CAIO once initial adoption and company-wide integrations are complete by establishing measurable benchmarks and milestones and equipping themselves with a clear, transparent transition plan.

For those looking to hire – or be hired as – Chief AI Officers, the time is now.

Tomer Zuker is VP Marketing at D-ID, the leading platform for the generation of Digital Humans. A strategic marketing expert with extensive experience in global growth and go-to-market strategies, he has led marketing initiatives at tech giants like AWS, Microsoft, and IBM. Tomer is also co-founder of the vibrant “Linkers” marketing community on LinkedIn and co-hosts the Market Trip podcast.