Chip Capacity Constraints Put a Governor on AI Spending Growth (www.nextplatform.com)

Recent reports indicate that chip capacity constraints, particularly in DRAM and HBM memory, are poised to stall the rapid growth in AI spending. As memory manufacturers operate at full capacity and struggle to expand, forecasts suggest that increases in AI spending will be more modest moving forward. Gartner’s analysis shows an uptick in spending for AI data center infrastructure and software, particularly in servers and network components, but the increase is largely attributed to opportunistic pricing rather than genuine capacity expansion. Additionally, while AI’s share of total IT spending surged dramatically between 2024 and 2025, the growth of non-AI IT budgets is declining, indicating a shift in industry focus. This slowdown in chip availability is significant for the AI/ML community as it points to potential limitations in scaling AI technologies amid escalating demands. Companies may face higher costs and constrained growth, affecting their ability to innovate and deploy AI solutions rapidly. Furthermore, as the AI sector starts to represent a majority of IT budgets, the sustainability of investments will hinge on demonstrable gains in efficiency, productivity, and economic returns from AI implementations. How the market reacts to these constraints and the economic climate will shape the future trajectory of AI spending and development in the coming years.