The chief artificial intelligence officer: A blueprint for state and local government?

Late last year the White House issued an Executive Order (EO) on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence. On page 52 of the 66-page document, the EO called for each federal agency to establish a permanent chief artificial intelligence (AI) officer. The EO specifies the primary responsibility, in coordination with other responsible officials, for coordinating their agency’s use of AI, promoting AI innovation in their agency, managing risks from their agency’s use of AI, and promoting the use of trustworthy artificial intelligence in the federal government. While this has no direct bearing on state and local government, it does serve as a blueprint for AI governance. What makes this position so remarkable is the fact that AI was hardly on anyone’s radar some five years ago. Prior to the EO, a few states had already assigned senior level people to manage and coordinate AI initiatives—and local governments were not far behind. Given the history of federal initiatives, what happens at the federal government often gets adopted by state and local governments in some form or fashion.

The role of the chief AI officer (CAIO) is designed to play an increasingly significant role in both the private and public sectors. The CAIO is responsible for overseeing the development and implementation of AI technologies across the federal government. While we can expect to see the further clarification of the roles and responsibilities of the CAIO in the coming months, one can easily create a listing of roles and responsibilities which would include:

1. Strategic leadership and vision
• Developing and leading the organization’s AI strategy to support its overall government’s goals.
• Ensuring the alignment of AI initiatives with the organization’s strategic objectives.
• Advocating for and communicating the value of AI investments to stakeholders at all levels, including elected leaders, public managers, employees and external business partners.

2. AI governance and ethics
• Establishing governance structures to oversee AI projects, ensuring they adhere to ethical standards and comply with relevant laws and regulations.
• Implementing frameworks for responsible AI use, including transparency, fairness, accountability and privacy.

3. Innovation and transformation
• Identifying opportunities for AI to create value, improve efficiency and drive innovation within the organization.
• Leading digital transformation initiatives, leveraging AI to enhance products, services and customer experiences.
• Monitors AI use across all lines of government businesses.

4. Collaboration and partnerships
• Fostering collaboration across departments (e.g., IT, operations, government branding, HR) to ensure AI projects meet business and operational needs.
• Building and maintaining relationships with external partners, vendors and the AI research community to stay ahead of technological advancements.

5. Talent management and development
• Attracting, retaining and developing AI talent, including data scientists, machine learning engineers and other specialists.
• Promoting an organizational culture that supports continuous learning and adaptation in the face of AI-driven change.

6. Data and technology management
• Overseeing the development and maintenance of the data infrastructure required to support AI initiatives.
• Ensuring the organization has the necessary technology and tools to develop, deploy and scale AI solutions effectively.
• Ensuring AI systems are well-maintained and protected against cyber threats.

7. Risk management and compliance
• Identifying and mitigating risks associated with AI, including technological, reputational and operational risks.
• Ensuring AI projects comply with data protection laws, intellectual property rights and industry-specific regulations.
• Ensuring AI disclosure is clearly stated on any AI-generated reports, publications and data.

8. Performance measurement and improvement
• Establishing metrics and KPIs to measure the effectiveness and impact of AI initiatives.
• Regularly reviewing and adjusting AI strategies based on performance data and changing business needs.

9. Training and development
• Make AI training available to all government employees to help them understand the appropriate use of the technology and the potential for misuse.
• Provide professional development access to external AI programs.
• Conduct AI best practice awards for AI adoption.
• Develop a culture of sharing best practices in the innovative use of AI.

10. Public outreach
• Keep the public and community interest groups appraised of AI use in government.
• Serve as the principal spokesperson on all AI-related issues.

As AI continues to evolve and its applications become more widespread, the role of the CAIO will expand and adapt in response to unfolding new challenges and opportunities. Ideally, the CAIO can and will play a critical role in ensuring that AI technologies are leveraged in a way that is strategic, ethical, and maximizes value for the organization. Regarding the issue of leadership, the question of reporting relationships and hierarchy needs to be determined. Who does the CAIO report to or through? Should it be the CIO or the chief administrative officer, or someone else? Regardless, hail to the newest chief!

Dr. Alan R. Shark is the executive director for the Public Technology Institute (PTI), a division of the nonprofit Fusion Learning Partners; and associate professor for the Schar School of Policy and Government, George Mason University, where he is also an affiliate faculty member at the Center for Advancing Human-Machine Partnership (CAHMP). Shark is a fellow of the National Academy of Public Administration and co-chair of the Standing Panel on Technology Leadership. Shark also hosts the bi-monthly podcast “Sharkbytes.net.” Shark acknowledges collaboration with generative AI in developing certain materials.