The number of chief artificial intelligence officers (CAIOs) has nearly tripled in the past 5 years, as reported by LinkedIn. Companies in various sectors are recognizing the importance of integrating artificial intelligence (AI) into their core strategies at the executive level to stay competitive. These AI leaders are tasked with creating a roadmap for AI adoption and oversight within organizations and government entities.
In light of a recent executive order from the Biden administration and the rapid increase in AI adoption across industries, the Office of Management and Budget (OMB) has issued a memo outlining how federal agencies can leverage the opportunities presented by AI while managing associated risks.
Many federal agencies are now appointing CAIOs to supervise AI usage, promote responsible AI innovation, and address potential risks, including those posed by generative AI (gen AI), while considering the impact on the public. However, how will these CAIOs strike a balance between regulatory compliance and fostering innovation? How will they build trust?
Three IBM leaders share their perspectives on the significant opportunities and challenges that new CAIOs may encounter in their initial 90 days:
1. “Consider safety, inclusivity, trustworthiness, and governance from the beginning.”
—Kush Varshney, IBM Fellow
During your first 90 days as a chief AI officer, it’s crucial to prioritize safety, inclusivity, trustworthiness, and governance right from the start rather than treating them as afterthoughts. While embracing the optimism of a technologist, don’t disregard the caution and critical perspective of a social change agent. Remember that AI’s presence doesn’t absolve your agency of its existing responsibilities to the people. When defining the problem, analyzing the data, and evaluating solutions, consider the most vulnerable individuals.
Rather than just focusing on equitable resource distribution, redefine fairness to address the needs of the most disadvantaged. Shift your perspective on accountability from mere regulatory compliance to technology stewardship. Embrace transparency as a proactive measure, seeking public input before making decisions. Treat AI like infrastructure, understanding that choices made today can have far-reaching consequences for future generations. Implement a multi-model platform approach after piloting and innovating with a portfolio of projects.
2. “Create trustworthy AI development.”
—Christina Montgomery, IBM Vice President and Chief Privacy and Trust Officer
To drive efficiency, innovation, and trust, all CAIOs should establish an AI governance program that addresses ethical, social, and technical concerns related to creating trustworthy AI solutions.
Within the first 90 days, conduct an organizational maturity assessment to understand your agency’s current status. Review frameworks and assessment tools to identify strengths and weaknesses that could impact AI implementation and risk management. Define agency-wide ethics and values regarding AI creation and usage to guide decision-making on risk factors like data privacy, bias, transparency, accountability, and safety.
Implement trust and transparency principles, along with an “Ethics by Design” playbook, to operationalize ethical principles. Establish accountability and oversight mechanisms to ensure responsible and ethical AI usage, including monitoring, auditing, and compliance processes. Adapt existing governance structures to support AI initiatives, leveraging existing programs like third-party risk management, procurement, and privacy.
Prepare for the December 1, 2024 deadline to incorporate minimum risk management practices for impactful AI or pause usage until compliance is achieved. Utilize automated tools and seek assistance from trusted partners like IBM to implement strategies for responsible AI solutions.
3. “Establish an enterprise-wide approach.”
—Terry Halvorsen, IBM Vice President, Federal Client Development
IBM has collaborated with U.S. federal agencies for over a decade to advance AI technology and drive operational improvements. AI has facilitated efficiency gains in agencies like the IRS, VA, and Navy, but it also poses risks that must be managed through robust governance.
Newly appointed CAIOs should adopt an enterprise-wide approach to data and governance to mitigate risks, simplify implementation, and capitalize on AI opportunities. Engage stakeholders from various agency departments and industry partners to develop a comprehensive strategy. Measure results and learn from both internal and external AI initiatives.
Embrace a use-case-driven approach to AI, focusing on desired outcomes and selecting AI technologies accordingly. Begin with a clear vision of the end goal to guide AI implementation and governance.
CAIOs leading by example
The establishment of the CAIO role sets a precedent for responsible AI adoption in all sectors. IBM offers tools and strategies to assist agencies in adopting AI in an ethical and efficient manner, supporting new CAIOs in developing responsible AI solutions within their organizations.
If you’re seeking guidance on your AI journey, schedule an AI strategy briefing with IBM.
Was this article helpful?
YesNo
