Artificial Intelligence Adoption and Sectoral Transformation

The rapid advancement of artificial intelligence (AI) has profound implications for lawmakers, policymakers, and private sector leaders. In this report, the authors present the AI Capabilities Framework, which serves as a tool for understanding existing AI applications, anticipating future developments, and emphasizing the need for systematic evaluation of the potential policy challenges, opportunities, and uncertainties surrounding AI adoption. The report focuses on AI’s transformative potential across four specific sectors: financial services, climate and energy, health care, and transportation.

Key insights include identifying sector-specific risks and challenges, along with suggested policy responses to mitigate these issues while balancing potential benefits. The framework aids in identifying and responding to AI-related risks beyond the four selected sectors by offering a structured approach to align policy solutions with AI’s evolving capabilities. Additionally, the authors suggest integrating additional frameworks, such as the Comprehensive Mapping Protocol for Anticipating and Adapting to Systemic Shocks (COMPASS) approach and other RAND Strategic Rethink efforts, to enhance the understanding and management of systemic AI risks.

Key Findings

• AI in health care is primarily operating at lower levels of the AI Capabilities Framework.
• The health care sector faces a complex transformation through AI, and this change will have implications that extend far beyond patient outcomes to workforce dynamics and health equity.
• Most deployments of AI in the financial services sector operate at lower capability levels, although some systems are beginning to demonstrate the characteristics of higher capabilities, especially in the trading and investment, risk management, and customer service domains.
• The financial sector’s adoption of AI promises significant benefits but could also pose new forms of systemic risk that differ markedly from those associated with traditional algorithmic trading, raising concerns about market stability and oversight.
• AI adoption in the climate and energy sector is currently positioned at lower capability levels, but existing applications are starting to explore the potential for sustained autonomous operations.
• AI presents pivotal opportunities for addressing climate change and energy challenges and is being used to improve the efficiency of energy systems, reduce energy costs, and increase the reliability of services. However, this sector also faces issues of model accuracy and bias, emissions growth, and competition for resources.
• The transportation sector has achieved lower-level AI capabilities and has made some advancements toward higher-level capabilities, such as sustained, autonomous operation.
• AI technologies are revolutionizing how transportation systems are conceived, designed, and managed, affecting everything from personal vehicles to public transit and logistics networks.

This is part of the Social and Economic Policy Rethink Initiative, a RAND effort to transform the approach to solving social and economic policy problems.

Topics

• Artificial Intelligence
• Banking and Financial Services
• Energy and Environment
• Health Care Technology
• Transportation Technology