A new playbook offers guidance for AI leadership

A new playbook sheds light on the role chief artificial intelligence officers will play in the coming years for public sector firms looking to safely and effectively incorporate AI and machine learning into their operation flows. 

In a white paper authored by the International Data Corporation and sponsored by Google Cloud, IDC analysts Adelaide O’Brien and Ruthbea Yesner highlighted four actions as particularly vital for advancing AI responsibly in government sectors: assessing AI maturity; addressing risk, governance and compliance needs; developing an AI-ready workforce; and investing in innovation to scale AI use cases. 

“AI is one of the most powerful technologies of today, and an AI-fueled agency will require significant pivots in strategy, governance, talent management, and technology,” the authors write. “CAIOs play a vital role in structuring and guiding the innovative use of AI to meet the agency’s mission.”

The ethos of the report lines up with previous Biden administration guidance on responsible AI management, namely President Joe Biden’s landmark AI executive order and the Office of Management and Budget’s memorandum on responsible AI environments. 

Given that the role of the CAIO is new across public and private sectors alike, the white paper surveyed agencies to understand how some of the four key areas highlighted in the report are faring in the early stages of AI policy and tech adoption. 

Researchers found, for example, that 39% of surveyed agencies with a “higher AI maturity” prioritize delivering generative AI projects and focusing on responsible innovation. 

On the workforce side, authors note that 36% of agencies are facing a drought of in-house expertise that would enable their internal workforce to be equipped with sufficient skills to deploy and monitor AI systems. 

“This is the time to leverage outside expertise,” the authors write. “Sixty-nine percent of agencies involve a trusted partner, such as a system integrator, cloud provider, IT consultant,

and/or GenAI model vendor, from the beginning to shape their road map of AI use cases.”

The report also surveys agencies about the major motivators and most common use cases for deploying AI technology internally. Strengthening cybersecurity posture was a notable leader, with 62% of respondents citing this as a motive for incorporating AI into their operations. And 52% listed “boosting innovation” as a key motivator, with economic growth being the third most common use case, coming in at 41%. 

Findings in the report also noted that an individual agency’s current AI “maturity” level impacts the types of use cases it is embarking on. Agencies with high levels of AI maturity are beginning to deploy generative AI in public services and benefits arenas, while agencies with lower levels of AI maturity are using generative AI in less public-facing operations, like cybersecurity and administrative tasks.

Based on these results, the playbook advises that CAIOs focus on applying AI to near-term impact areas to jumpstart internal operations. 

“CAIOs should target more immediate use cases with clearly identifiable pain points and measurable mission impact,” the authors state. “These early victories can pave the way for tackling more ambitious and complex challenges, creating a virtuous cycle of AI-driven innovation.”