What the Ramp AI Index shows about business AI spending
The Ramp AI Index tracks how real US businesses spend on AI tools through Ramp's corporate card network. Unlike survey data, it reflects actual purchases made by real organizations. The June 2026 edition of the Ramp index reported that Anthropic overtook OpenAI in share of US business AI spending in May 2026, the first time that had happened. The shift was not a narrow margin or a single-month anomaly. Anthropic's share had been climbing steadily as OpenAI's share softened. The Ramp report also noted that 43% of Anthropic's current business customers had previously spent with a different primary AI vendor. That figure describes something specific: the switching cost for AI vendors is near zero, and businesses are acting on it. DeepSeek entered the Ramp data at roughly 0.1% share in early 2026 and reached the top of the trending vendor list by the June report. The growth rate is notable less because of where DeepSeek landed than because of how quickly it moved from negligible to significant in real business spending. The Ramp data does not tell you which vendor to use. It tells you that the vendor landscape is shifting, businesses are switching, and optimizing too deeply for any single vendor is a risk that was not obvious when one vendor was dominant.
Why vendor switching costs are near zero in AI
AI vendor switching costs are structurally different from most enterprise software categories. In most software categories, switching costs are high: data migrations, retraining, integration rebuilds, contract penalties, lost institutional knowledge about workflows. These costs create stickiness even when a competitor offers better value. AI vendor switching has most of those costs removed by default. The major frontier models accept natural language prompts. The model API formats are similar enough that switching a model call from one provider to another is often a few lines of code, not a multi-month migration. Data does not live inside the vendor. Outputs are text, images, or code, all portable. The knowledge about how to write effective prompts transfers across providers. The main switching cost is prompt tuning: system prompts and few-shot examples that work well with one model may need adjustment on another. For a business that has built one or two specific AI workflows, that is hours of work, not months. This structural difference matters for how businesses should build. A purchasing decision that assumes high switching costs should be revisited when switching costs are actually low.
What vendor fragmentation means for how you buy AI
When one vendor is dominant and the market is stable, the right approach is to go deep: build integrations, train your team on that vendor's tools, and optimize your workflows for their specific strengths. When the market is fragmenting and switching costs are near zero, going deep on a single vendor without a portability plan is a different kind of risk. The risk is not that any specific vendor will disappear tomorrow. Anthropic and OpenAI are both well-capitalized and widely deployed. The risk is that the vendor advantage you optimize for today may not be the relevant advantage in twelve months. Model quality, pricing, capability, and enterprise features are all changing rapidly across every vendor. The vendor that offers the best performance for your specific workflow today may not offer it next year. If your workflows are built in ways that make switching painful, you absorb that cost at exactly the wrong moment. The practical implication for buying decisions: treat AI vendors the way you treat API providers for commodity services, not the way you treat an ERP system or a core business database. Keep the integration layer thin enough to swap. Avoid building AI-specific workflows that only function with one vendor's proprietary features when a portable alternative exists. Review your AI spend annually, not only at contract renewal.
What the DeepSeek rise illustrates
DeepSeek's move from 0.1% of measured business AI spending to the top of the Ramp trending vendor list in a few months represents something worth understanding beyond the market share number. DeepSeek's R1 model demonstrated that open-weight models could match frontier closed-model performance in specific benchmarks at a fraction of the API cost. The practical business implication is that some AI use cases that previously required a premium API may now be addressable with a lower-cost or self-hosted model. For business owners, the DeepSeek story is not primarily about DeepSeek specifically. It is about the category it represents: capable, lower-cost alternatives to frontier APIs that perform well on common business tasks. Whether those alternatives are DeepSeek, Mistral, Meta's Llama models, or the next open model that reaches deployment quality, the pattern is the same: what cost a specific amount to run six months ago may cost significantly less to run today on an alternative. This means that AI cost optimization is not only about reducing usage. It is also about periodically evaluating whether the model you are paying for is still the right cost-quality tradeoff for each specific workflow.
What business owners should not read into this
The AI vendor fragmentation story can be misread in two directions. The first misread is that vendor selection is now trivial and all models are interchangeable. They are not. Different frontier models have genuine performance differences across task types. A model that performs well for customer-facing summarization may perform less well on technical code review. Vendor selection still requires matching model capabilities to workflow requirements. Portability means having a plan to switch, not choosing carelessly. The second misread is that switching vendors frequently is a productive activity. It is not. Changing vendors without a specific performance, cost, or capability reason introduces disruption without benefit. The goal is not to rotate vendors regularly. The goal is to build so that a well-reasoned switch does not cost you three months of integration work. Vendor portability is a design choice, not an operational habit. You make the investment once in how you build. The optionality that creates is available when you actually need it.
The Atlacis view
Most of the businesses we work with selected their primary AI vendor two to three years ago, often without a deliberate decision process. OpenAI was first, most familiar, and the path of least resistance. That was a reasonable approach when the market had one dominant player and model quality gaps were large. The market has changed enough that the assumption underlying that original choice deserves a review. Not because you should switch, but because the decision to stay should be a decision, not a default. A useful AI vendor review covers four questions: which vendor are you currently spending on and what are you getting for that spend; which workflows are tightly coupled to that vendor's specific features and which are loosely coupled; what would a switch to the current best alternative cost in integration time and prompt rework; and whether the answer to that cost question is acceptable given how quickly the vendor landscape is moving. For most businesses, this review takes less than a day. The result is either confirmation that your current vendor is the right choice, or identification of a workflow that deserves a closer look. Either outcome is more useful than the status quo.
The short version
- In May 2026, Anthropic overtook OpenAI in US business AI spending for the first time, according to the Ramp AI Index, which tracks actual corporate card purchases.
- 43% of Anthropic's current business customers had previously spent with a different primary AI vendor, reflecting near-zero switching costs in practice.
- DeepSeek grew from roughly 0.1% of measured business AI spending to the top of the fastest-growing vendor list in the same period.
- AI vendor switching costs are structurally lower than most enterprise software: API calls are portable, prompts transfer across providers, and no data lives inside the vendor.
- The right response to vendor fragmentation is portability by design: thin integration layers, workflows that avoid proprietary features when portable alternatives exist, and annual spend reviews.
- A productive vendor review answers four questions: what you are spending and getting, which workflows are tightly vs. loosely coupled, what a switch would cost, and whether that cost is acceptable given market velocity.