US Companies Boost AI Usage Despite Spending Decline

According to the Ramp AI Index, AI spending by over 70,000 US companies has decreased, while AI usage has increased by approximately 50% since July 2026. The report, released by economist Ara Kharazian, highlights a significant shift in the landscape, driven largely by competitive pricing between major players OpenAI and Anthropic. As of the last week of September, spending on Anthropic's tokens accounted for 51%, while OpenAI held 44.5% of the market. Open-source models, however, remain a minor component, constituting less than 5% of corporate spending.

The data reflects a record level of AI usage by the end of September, marking an unusual trend where companies are utilizing more AI capabilities while spending less. This pattern is not new but its persistence over several months is noteworthy, especially given the previous spending peak in July 2026.

The decreased spending amidst increased usage suggests a strategic shift among US companies, prioritizing cost efficiency and competitive pricing. With OpenAI and Anthropic dominating corporate spending, their pricing strategies have significant implications for smaller AI vendors and open-source alternatives, which struggle to capture market share.

This dynamic also highlights the growing dependency on proprietary AI models, raising concerns about national AI sovereignty and potential vulnerabilities in supply chains. The dominance of these two players could lead to a duopoly, influencing not just pricing but also innovation trajectories within the AI sector.

Looking forward, it's likely that OpenAI and Anthropic will continue to refine their pricing models to capture more market share. This could lead to further consolidation in the AI sector, with smaller companies either merging or exiting the market. By early 2027, expect regulatory scrutiny as policymakers assess the implications of such concentrated market power.

Additionally, companies may increasingly turn to hybrid models, combining proprietary and open-source solutions to balance cost and capability. This trend could spur further innovation in open-source AI, potentially increasing its market share by mid-2027.

The current spending dynamics may have broader implications for the AI supply chain. As companies seek more cost-effective solutions, demand for AI infrastructure and support services may increase, benefiting cloud service providers and AI consultancy firms.

Moreover, if the trend of decreased spending continues, it could lead to a reevaluation of AI investment strategies, impacting sectors reliant on AI for competitive advantage, such as finance and healthcare. These sectors may need to innovate more aggressively to maintain their edge.

In the broader context of AI sovereignty, the reliance on a few dominant players poses risks for national autonomy. Similar to the early 2020s' semiconductor shortages, this dependence could lead to strategic vulnerabilities. Unlike that case, however, the AI market is still evolving, offering opportunities for diversification and resilience building.

Overall, the shift in spending and usage patterns underscores the need for strategic foresight in AI policy and market dynamics. As competition intensifies, stakeholders must navigate these changes to leverage AI's full potential while mitigating associated risks.