Rise of the Chief AI Officer in Private and Public Sectors

Published Date : 06/11/2024 

Nextgov/FCW interviewed leading industry technologists about how the private sector is employing executives in charge of the emerging technology of artificial intelligence. 

In 2012, the Harvard Business Review famously declared the role of data scientist ‘the sexiest job of the 21st Century.’ Fast forward to 2024, and a similar claim can be made for the role of the chief artificial intelligence officer (CAIO), especially in the realm of technology jobs. Over the past 24 months, companies ranging from Amazon to Zendesk, and as diverse as Hinge and Tractor Supply Company, have hired or designated positions to oversee their AI efforts. Dozens of federal agencies have also followed suit, naming CAIOs in response to President Joe Biden’s executive order in October 2023. The Departments of Veterans Affairs, State, and Energy, among others, have installed CAIOs to oversee AI efforts and balance risk and innovation.

The CAIO role originated in the private sector, giving companies, particularly those in tech, a head start in defining and shaping the position. According to a survey by Foundry, one in four enterprise companies either have an AI chief or are actively seeking candidates to fill the role. But how are industry leaders deploying AI chiefs, and what advice do they have for their public sector counterparts? Nextgov/FCW sat down with several experts to find out.

A Successful Chief AI Officer Needs to Understand the Business

Jared Coyle, Head of AI for SAP North America, emphasized that many organizations immediately seek to hire data scientists to fill the CAIO role. However, hiring highly skilled PhDs to architect sophisticated algorithms does not guarantee business success. “The truth is, what you actually need are people who understand the business and business process experts,” Coyle stated. He highlighted the importance of algorithms that the sales divisions can effectively utilize to drive value and return for the organization.

Many organizations and federal agencies have opted to promote from within, leveraging internal talent. For instance, Accenture Federal Services promoted Denise Zheng to be its first chief AI officer in April, after she had served as the company’s global generative AI and ecosystem lead. “You need people in these roles who know how to operate within the organization,” Zheng explained. “It isn’t just about the number of academic articles they’ve published on AI and machine learning.”

Many CAIOs wear multiple hats, often serving in dual roles such as chief information officer (CIO) or chief data officer (CDO). Zheng, for example, also leads Accenture Federal Services’ Federal Data and AI practice. She believes this dual role can be advantageous. “Being dual-hatted enables them to be more effective in the early stage. They are a known quantity in the organization, have established relationships, and understand the existing data and analytic capabilities.”

While attracting and retaining top talent is crucial, institutional knowledge and the ability to get things done are equally important. Amy Jones, U.S. Public Sector AI lead at EY, noted that hiring external talent who don’t understand how the government works can present challenges. Government budgets and priorities differ significantly from the private sector, being mission-driven rather than profit-driven.

Establish and Drive Governance

Karen Dahut, CEO of Google Public Sector, stressed the importance of establishing appropriate governance at the leadership level. Many organizations are federated and enable a variety of platforms and technologies. “What they need is someone to drive governance, technology selection, and the approach, while allowing the organization to flourish,” Dahut said. “But someone has to drive the governance and policy.”

Dahut recommended that CAIOs report directly to senior leadership, rather than another C-suite peer like the CIO. “The CAIO and the CIO have different fundamental risks and opportunities,” she explained. “A CIO focuses on providing broad-based technology at a reasonable cost and ensuring security, while a CAIO is all about experimenting with new technologies to achieve the mission. Therefore, a CAIO should report to leadership to drive mission transformation through technology.”

Jared Coyle echoed the need for both internal and external governance. “You would think that the necessary buy-in at the leadership level would be automatic, but it’s crucial to ensure actual buy-in,” he said.

Balance AI Innovation and Risk

Amy Jones used a racing analogy to describe the CAIO’s role in balancing AI innovation and risk. The guardrails and gutters on the side of the road represent compliance and security, while the road itself symbolizes the CIO-developed infrastructure. The CAIO is like the driver, responsible for keeping the car moving as fast as possible while staying on the road. “The AI chief’s role is to remove friction between innovation and risk,” Jones said. One significant challenge is transitioning AI projects from the sandbox to the enterprise, a task made even more complex in government settings due to additional security requirements and standards.

Denise Zheng emphasized the importance of safe experimentation. “If you get new budget money, the most critical step is to create a safe and secure sandbox for experimentation,” she advised. “You need a controlled environment to experiment with models, test them, build them, and deploy them into applications. Otherwise, you’ll be waiting for vendors to develop solutions that may or may not fit your needs.”

Conclusion

The role of the Chief Artificial Intelligence Officer is evolving rapidly, driven by the increasing importance of AI in both the private and public sectors. Successful CAIOs are those who understand the business, drive governance, and balance innovation with risk. As more organizations adopt this role, the lessons learned from industry leaders will be crucial in shaping the future of AI leadership. 

Frequently Asked Questions (FAQS):

Q: Why is the role of a Chief Artificial Intelligence Officer important?

A: The CAIO role is crucial for overseeing and driving AI initiatives within an organization, ensuring that AI technologies are aligned with business goals and that risks are managed effectively.

Q: What skills are necessary for a successful CAIO?

A: A successful CAIO needs a deep understanding of the business, strong leadership skills, and the ability to balance innovation with risk. They should also have a solid grasp of AI technologies and governance.

Q: How can organizations ensure the right governance for AI initiatives?

A: Organizations should establish clear governance structures, with the CAIO reporting directly to senior leadership. This ensures that AI efforts are aligned with the organization's mission and that there is proper oversight.

Q: What are the main challenges faced by CAIOs in the public sector?

A: CAIOs in the public sector face challenges such as navigating complex budgets, understanding government operations, and balancing security requirements with innovation.

Q: Why is experimentation important in the role of a CAIO?

A: Experimentation allows CAIOs to test and refine AI models in a safe and controlled environment. This helps in identifying the most effective solutions and mitigating risks before full-scale deployment. 

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