Society & Ethics

Intelligence doesn’t come cheap as AI drives up costs for the NSA, hospitals, and insurers

· September 25, 2026
Intelligence doesn’t come cheap as AI drives up costs for the NSA, hospitals, and insurers

The business move

The NSA is sinking billions into testing advanced AI models, mainly on the computing power needed to run them. Lawmakers now predict AI oversight alone could cost tens of billions annually, a sharp rise from the Congressional Budget Office’s previous $20 million estimate. Meanwhile, in U.S. healthcare, AI-assisted billing codes have inflated costs by nearly $1 billion over two years, showing the technology’s wide financial impact beyond just government agencies.

Why it matters

The explosion in AI-related expenses exposes a major challenge for public and private sectors: intelligence at scale is expensive. For the NSA, this means budgeting for vast computing infrastructure and long-term oversight costs, not just the upfront tech development. In health care, AI’s ability to create more complex billing codes drives up insurer payouts and patient expenses. These realities force operators, funders, and policy makers to rethink assumptions about AI’s cost-effectiveness and the real price of smart automation.

Who gains and who gets squeezed

Cloud providers, hardware vendors, and AI service firms stand to gain as demand for high-powered computing grows. The NSA and other agencies must allocate larger budgets, potentially tightening resources for other priorities. Health insurers face higher claims linked to AI-assisted billing, which can also press patients with increased medical bills. Smaller hospitals or agencies without AI budgets risk falling behind or losing competitiveness in adopting AI solutions.

What to watch next

Watch lawmakers as they finalize AI oversight spending rules and budgets; their decisions will determine operational limits for intelligence agencies. In healthcare, monitor how regulators respond to the cost inflation from AI-driven billing codes. Operators in both sectors should assess infrastructure investments cautiously and prepare for rising AI-related costs that may compress margins or slow deployments.

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