Before artificial intelligence supercharges global productivity, governments must confront an unfortunate reality: the long-awaited economic windfall may be years away, yet the costs are coming due right now.
Listen to the optimists, and the AI-driven economic boom is just around the corner. The Penn-Wharton Budget Model projects AI will to GDP and productivity over the next decade. Goldman Sachs says it could add to productivity every year. By the mid-2030s, AI might, according to.
Moody’s Ratings says the global AI productivity boom will average 1.5% annually across 106 countries, per a Thursday research note. But when it comes to economic growth, governments may need to spend money now to generate more later. AI could deliver significant productivity benefits, yet nations will first have to navigate a complex, costly landscape as they build digital infrastructure and support disrupted workforces, Moody’s analysts warned.
The push to make AI adoption widespread will likely involve substantial upfront costs. For countries already facing tight public finances, AI’s capital expenses could end up “sharpening the policy trade-off between taking on higher near-term fiscal risk and delaying participation in AI-driven growth opportunities,” the analysts wrote.
A windfall, delayed
To be clear, AI adoption could bring meaningful fiscal advantages to governments, including stronger growth, higher corporate and wealth tax receipts, and more effective tax administration. AI-powered digitalization could also close compliance gaps, potentially adding up to 1.3% of GDP in revenue for countries with weak enforcement, Moody’s noted, citing IMF data.
But the note warned against treating AI as an “immediate fiscal windfall.” Before productivity gains fully materialize, governments face upfront costs that could strain budgets already burdened by post-pandemic debt. Explicit government spending on AI remains modest—often just a fraction of a percent of GDP—but a host of hidden costs could make the transition far harder for budgets to manage.
Consider the energy crunch: Global data-center power demand will, per the International Energy Agency, forcing upgrades to grids, water systems, and connectivity. China’s state grids are launching a 5 trillion yuan ($722 billion) expansion specifically for AI and data centers—equivalent to 4% of GDP, according to Moody’s. The Qatar Investment Authority has announced a $20 billion project (9% of the nation’s GDP) to develop AI data centers and computing infrastructure. And in Korea, while AI-related spending accounts for just 0.4% of GDP, the country’s newly established sovereign wealth fund is almost entirely focused on high-tech industries like AI and chips, with plans to deploy a 5.7% of GDP war chest over the next five years.
These debt-funded projects create “indirect but potentially material” exposure to fiscal risk, the analysts wrote. Beyond infrastructure, governments will need to plan for labor disruptions and related social support. The IMF estimates 40% of global jobs—and 60% in advanced economies—are, particularly high-skill roles, which could erode payroll taxes while spiking demand for reskilling and safety nets.
“Declines in labor-based tax receipts could offset or exceed other AI-related tax gains,” Moody’s noted, echoing from the IMF that fiscal policy include progressive taxation and social protections to mitigate AI-related budgetary impacts.
Uncertainty reigns
For the U.S., the stakes of this transition are uniquely high. As a leading hub for the global AI infrastructure boom, the U.S. is poised to capture a significant share of the projected $3 trillion in data-center-related investments over the next five years, per Moody’s. Yet this leadership comes with a steep price: massive demands on power grids and digital connectivity that require enormous spending before productivity gains ever hit the bottom line.
The Penn-Wharton model found in a preliminary analysis that AI could reduce deficits by. But the Congressional Budget Office framed AI and associated investment as wildcards in shaping the U.S. fiscal and economic outlook. While the CBO projects AI will boost total productivity by 1% over the next decade, its most recent conceded that this prediction was “highly uncertain.” If adoption is slow or costs are higher than expected, it would significantly alter GDP growth—and consequently, government revenue.