admin Payments data covering more than 50,000 businesses showed Anthropic’s Claude products used by 34.4 per cent of firms in April, ahead of OpenAI’s ChatGPT and related services at 32.3 per cent. Overall paid AI adoption among the surveyed businesses reached 50.6 per cent, underlining how quickly generative AI has moved into corporate budgets.
The lead is narrow, and the data reflects paid transactions captured through one business payments platform rather than the full enterprise market. Still, the change is significant because OpenAI’s ChatGPT set the pace for the consumer and workplace AI boom after its launch in late 2022. Claude’s move ahead in paid business usage suggests Anthropic has converted its reputation among developers, finance teams and professional services firms into broader commercial traction.
Anthropic’s advance has been driven largely by Claude Code, its agentic coding system designed to read codebases, modify files, run tests and support software development workflows. The product has appealed to engineering teams seeking direct productivity gains, but its use has also spread to non-technical staff using AI to prototype applications, analyse documents and automate internal processes.
The business AI contest is increasingly being decided by workplace integration rather than chatbot popularity. Companies are weighing model quality, cost, security controls, data-handling terms, latency and procurement simplicity. Claude has gained favour among firms that prioritise coding, document analysis and complex reasoning, while OpenAI retains a powerful position through ChatGPT’s consumer brand, developer platform and enterprise contracts.
OpenAI remains far from displaced. The company says more than 1 million business customers use its tools worldwide, including organisations paying for ChatGPT for Work and developers using its models directly. ChatGPT also retains a much larger consumer footprint than Claude, giving OpenAI a brand advantage that continues to support workplace adoption when employees bring familiar tools into companies.
OpenAI has responded by intensifying its corporate push. It has created a deployment-focused company backed by more than $4 billion in initial investment to help organisations build and implement AI systems. The unit includes the acquisition of Tomoro, an AI consulting firm with around 150 engineers and deployment specialists, and is backed through a partnership involving 19 firms led by TPG with Advent, Bain Capital and Brookfield as co-lead founding partners.
That move shows the enterprise AI market is entering a service-heavy phase. Large companies no longer want only access to powerful models; they want help redesigning workflows, connecting AI to internal systems and measuring returns. Anthropic has also moved in that direction through partnerships with major professional services groups and products aimed at making Claude easier to deploy across departments.
The April crossover also reflects a wider reordering of enterprise model spending. Anthropic has been gaining share in large language model APIs, while Google has strengthened its position through Gemini and cloud-linked AI services. OpenAI’s early lead has narrowed as businesses adopt multiple providers and select models by task rather than relying on a single vendor.
Coding has become the most important battleground. Software development offers clear performance metrics, frequent usage and fast feedback loops, making it easier for companies to justify paid AI subscriptions. Anthropic’s strength in coding benchmarks and developer workflows has helped it win early adopters, while OpenAI, Google and Microsoft are pushing competing tools through Copilot, Gemini and enterprise cloud platforms.
The shift also carries risks for Anthropic. A lead based on one month of payments data does not establish a durable moat. Corporate buyers can switch vendors quickly if rivals offer better pricing, stronger integrations or improved model performance. Token-based billing also remains a concern for finance chiefs trying to forecast AI costs as usage scales across thousands of employees.
