Artificial intelligence (AI) has the potential to raise the standard of living, expand economic opportunities, and make America more competitive globally, but an honest assessment of how AI is currently reshaping labor and the economy is needed, according to experts at the Special Competitive Studies Project (SCSP), a nonprofit and nonpartisan initiative focused on strengthening America's long-term competitiveness in AI. At the SCSP's annual AI+Expo, a Task Force on AI and the Future of Work unveiled preliminary findings that can serve as a foundation for further development and inform discussions. The Task Force, a joint effort between SCSP and Nvidia, identified ten aspects of AI's current and potential impact on work and the economy.
The first finding highlights that AI is distinct from most prior general-purpose technologies because it extends into certain types of cognitive work by impacting the foundational skills by which tasks are performed. This rapid advancement is reshaping how work is done across industries. Second, the transition is unpredictable: although AI has already shown the potential to simultaneously expand human work and eliminate or transform other jobs, disruption and complications are to be expected during transitions. Third, new data collection and analytics will be needed to assess changing skill sets and hiring patterns in the workforce now and in the future, restructuring how data is gathered and used.
Fourth, at the task level, workers need to understand how AI may automate or augment key tasks, and how roles may be reconfigured even without changes in job titles or employment levels. Fifth, for entry-level labor, the long-term impact remains unclear, but increased use of AI for these jobs may affect traditional talent pipelines and career advancement pathways in certain industries. Sixth, adoption of AI will vary across sectors and organizations based on incentives, workflows, and institutional constraints, meaning its use in certain areas is not inevitable and may not be consistent. Seventh, shifting skills will be required: training and roles with enduring value in an AI-driven economy include not only new digital and technical skills but also enduring human traits like critical thinking, leadership, and adaptability. Additionally, skilled labor is needed for constructing data centers and other facilities to support AI infrastructure.
Eighth, training shortfalls demand that education be reimagined from a front-loaded learning system to a more flexible model that uses AI as a training tool to hone foundational capabilities and adaptable domain-specific skills. Ninth, expanding access to AI can improve worker performance by deploying high-productivity tools widely, but outcomes depend on how AI is used, who benefits from increased productivity, and how quickly workers can adapt. Tenth, unifying national action is crucial: the speed, scale, and complexity of AI require coordination across government, industry, and educational institutions to manage the transition by aligning incentives and investing in workforce development. "The window for proactive intervention is open," the authors concluded. For more information, visit scsp.ai.
