A study released this week indicates leading private sector tech companies’ investments in artificial intelligence may not ensure “long-term national competitiveness” within the United States.

Conducted by the Center for Security and Emerging Technology, the study maps the research agendas of Apple, Amazon, Facebook, Google, IBM and Microsoft across 60 AI areas, including robotics and grasping to optimization.

The study indicates “consideration differentiation” in prioritized AI research areas among the companies that could negatively impact the United States’ status against near-peer nation-state rivals.

“None of the leading companies examined in this analysis appear to be prioritizing work on problem areas within machine learning that will offset the broader structural challenges the United States faces in deploying and benefitting from the technology when competing against authoritarian regimes,” the study states.

The study indicates problem areas include federated learning, simulation learning, interpretability, few-shot learning and machine learning fairness—all subfields of AI. The study’s findings are based on numerous research papers published by universities since 2010 and other open-source information, according to its authors. The study encourages U.S. policymakers to “take into account the state of play of corporate investments’ in AI in formulating national AI policy, and suggests the U.S. government position itself as “gap filler” by addressing certain machine learning areas .

“To the extent that national interests and private sector agendas converge, the U.S. government may only need to encourage existing research activity,” the study states. “To the extent that these interests diverge, U.S. government strategy may need to intervene more extensively in order to ensure national competitiveness in underinvested areas.”

The Biden administration has indicated it aims to increase investments in science, research and development of up to 2% of U.S. gross domestic product.