Federal agencies are facing an onslaught of artificial intelligence requirements, a new government watchdog report detailed, with callouts coming from executive orders, federal laws, advisory guidance and other sources.

As of July, there were nearly 100 different objectives related to the emerging technology that might be considered government-wide standards, according to the Government Accountability Office. 

“AI technologies can drive economic growth and support scientific advancements that improve the conditions of our world,” the GAO said in its correspondence to Congress. “It also holds substantial promise for improving the operations of government agencies. However, AI technologies also pose risks that can negatively impact individuals, groups, organizations, communities, society, and the environment.”

The goal of the report, the watchdog said, was to understand the various AI requirements facing the government and which bodies hold responsibility related to the technology. 

The review included current requirements for federal agencies, like creating inventories of AI use cases and updating AI use policies. It also examined broader efforts, like the National AI Initiative, which focuses on goals like increasing research and development of the technology and investing in computing resources. 

“Federal agencies’ efforts to implement AI have been guided by a variety of legislative and executive actions, as well as federal guidance,” GAO continued. “Congress has enacted legislation, and the President has issued EOs, to assist agencies in implementing AI in the federal government.”

The office reviewed new artificial intelligence initiatives created by the current and former administrations, stretching from the first Trump administration’s executive order on artificial intelligence and the signing of the AI Training Act to more recent guidance from the Office of Management and Budget.

Overall, GAO found that 10 different bodies had a stake in reviewing the U.S. government’s AI efforts, and that federal laws, executive orders, and guidance had produced 94 different expectations related to the technology, including reviews related to risk mitigation, investment strategies, and usage policies. 

The GAO sent a draft of the report to OMB, the Office of Science and Technology Policy, the Commerce Department, the General Services Administration and the National Science Foundation. OSTP, Commerce and NSF responded with technical comments, while GSA declined to provide comments and OMB did not respond to GAO’s request for comments on its findings.

The IBM Institute for Business Value study shows that generative AI is live in customer care for 69% of telecoms. Meanwhile, agentic AI—capable of autonomous decision-making—is being used by 44% of CSPs. These technologies are enabling real-time insights, personalized experiences and operational efficiency across the board.

Momentum is building in areas such as network automation, edge intelligence and service assurance, but leading CSPs are already pushing further. 

For example, Bharti Airtel, a leading CSP in India, has deployed an AI-powered anti-SPAM network that flags over 8 billion spam calls and 1 billion spam SMS messages. It identifies nearly 1 million spammers daily. The company also launched an AI-driven RAN energy management solution, expected to save USD 12 million annually while reducing its carbon footprint.

Meanwhile, China Mobile has introduced over 24 AI products. One of them, Lingxi—an intelligent customer assistant—handles 90% of first-line inquiries and has boosted customer satisfaction by 10% in pilot regions. The company also uses AI-powered predictive analytics to reduce network repair times by 30% and AI-based energy management to dynamically optimize power usage across its RAN infrastructure.

As AI becomes embedded in critical infrastructure, telecom providers are turning to performance dashboards to bring transparency and accountability to AI-driven initiatives. These tools help shift AI from a black box to a visible engine for business value—tracking model drift, triggering retraining and alerting teams when KPIs fall below thresholds. Governance dashboards also support regulatory compliance by offering transparency logs for audit purposes.

To ensure sustained impact, continuous monitoring and agile feedback loops are essential. But measuring the right things matters equally. Focusing solely on cost can obscure gains in customer experience or business growth.

That insight is why leading telecom adopters track a balanced set of KPIs—most often cost savings, customer satisfaction, AI-driven revenue growth and operating margin. Over the past year, CSPs have reported real, measurable improvements across these high-priority performance areas.

By anchoring AI initiatives in business outcomes and operational KPIs, CSPs can ensure that innovation translates into growth, efficiency and long-term competitive advantage.

“Artificial astronauts” could fly as actual crew members on human missions to Mars, and elsewhere in space.

These rugged, space-rated artificial humans offer great advantages, advocates say. For example, they would not require the large amounts of consumables needed to support humans. They could also perform spacewalks without a life-support system.