2025: The Year AI Came of Age—And the Questions Ahead for 2026
From Leon Hadar
As 2025 draws to a close, artificial intelligence has unmistakably transitioned from experimental technology to essential infrastructure. This was the year AI moved from boardroom curiosity to balance sheet necessity, reshaping how we work, create, and compete on the global stage.
The numbers tell a compelling story. Forty-four percent of U.S. businesses now pay for AI tools, up dramatically from just 5% in 2023, while average AI contracts reached $530,000. More striking still: AI-first startups grew 1.5 times faster than their peers. These aren't pilot projects anymore—they're core operations.
The technical achievements were equally remarkable. AI system performance surged across major benchmarks, with scores rising by 18.8, 48.9, and 67.3 percentage points on MMMU, GPQA, and SWE-bench respectively in just one year. Perhaps most significantly, language model agents outperformed humans in programming tasks in some settings, signaling AI's evolution from assistant to autonomous actor.
Yet 2025 also exposed the growing pains of rapid adoption. The geopolitical race intensified, with the U.S. producing 40 notable AI models compared to China's 15 and Europe's three, though Chinese models rapidly closed the quality gap, with performance differences shrinking from double digits to near parity. Meanwhile, AI-related incidents rose sharply, while standardized safety evaluations remained rare among major developers.
The regulatory landscape fragmented dramatically. In the U.S., the Trump administration's January executive order reversed the Biden-era approach, prioritizing innovation over oversight. Thirty-eight states enacted approximately 100 AI-related measures in 2025, creating a patchwork that has businesses scrambling for compliance. Texas, California, Colorado, and Illinois all have comprehensive AI laws taking effect throughout 2026, covering everything from hiring discrimination to frontier-model safety.
Looking toward 2026, several critical questions loom large. Can we bridge the gap between recognizing AI risks and taking meaningful action? Will the ongoing federal-state regulatory tension resolve into coherent governance, or will fragmentation stifle the innovation both sides claim to protect? And as enterprises push beyond content generation into AI reasoning for their own data, how will we ensure transparency and accountability in systems making increasingly autonomous decisions?
The infrastructure challenge cannot be ignored. Multi-gigawatt data centers backed by sovereign funds signal a new wave of compute infrastructure, with power supply emerging as the new constraint. The question isn't just whether we can build AI systems smart enough to transform industries—it's whether we can power them sustainably and govern them responsibly.
2025 proved AI's commercial viability beyond doubt. The challenge for 2026 is ensuring that velocity doesn't outpace wisdom. As AI systems grow more capable and autonomous, our frameworks for oversight, accountability, and international cooperation must mature just as rapidly. The technology has come of age. Now our governance must catch up.