
A new Okta analysis tracking enterprise AI tool adoption from June 2022 to June 2026 reveals that Anthropic leads in growth rate, while Microsoft 365 holds the largest user base. Over half of companies now use multiple AI platforms in parallel, indicating that enterprises are mixing and matching tools rather than betting on a single vendor—a trend that reflects the maturation of enterprise AI adoption beyond early pilots.
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Okta's analysis of enterprise AI tool usage—tracked across over 2 million accounts from June 2022 to June 2026—shows Anthropic ranked #1 in growth rate (indexed at 100), followed by OpenAI (66.9), Google Workspace (59.8), GitHub (56.6), and Cursor (42.4). For the largest account counts, Microsoft 365 ranked #1, with Google Workspace in second place.
Why it matters
More than half (57%) of companies now use two or more AI platforms simultaneously, signaling a shift toward a "mix-and-match" approach rather than reliance on a single vendor. This fragmentation means enterprises are actively building portfolios of AI tools tailored to specific workloads, a pattern that could reshape how software budgets are allocated across different AI providers.
What to watch
Anthropic's growth has accelerated notably since January 2026, when it began adding enterprise accounts. Over the same period, OpenAI and Cursor growth has slowed, suggesting a shift in which vendors enterprises are adopting for new deployments.
The identity and access management (IAM) platform Okta released findings from an analysis of enterprise AI tool adoption patterns covering a 4-year window from June 2022 to June 2026. The research tracked access data from more than 2 million enterprise accounts to identify which AI tools are gaining adoption and at what rate. The findings, disclosed on July 21, 2026, were reported in the publication Publickey and shared with ITmedia NEWS.
When indexed with Anthropic set at 100 as the baseline, the growth-rate rankings show Anthropic in first place, followed by OpenAI at 66.9, Google Workspace at 59.8, GitHub at 56.6, and Cursor at 42.4. Over the 4-year span, Anthropic's trajectory has been significantly steeper than its peers, though the analysis notes that some tools saw their growth curves flatten in recent months. The graph depicting these trends shows that the gap between the top performer (Anthropic) and others has widened substantially. Okta also observed that in the second half of 2025 and into January 2026, Anthropic's enterprise account growth accelerated markedly, at the same time OpenAI and Cursor growth slowed.
The research found that enterprises are increasingly adopting a multi-platform approach. More than 57% of companies now use two or more AI platforms concurrently, assembling tool portfolios that match different workloads. The tools tracked span a broad range: specialized code and software development tools, workplace and communication software, creative platforms, enterprise productivity suites, cloud and DevOps AI, cybersecurity and infrastructure AI, and enterprise-specific solutions. The diversity of the market reflects the fact that no single vendor has captured the full breadth of enterprise AI demand; instead, companies are selecting best-of-breed tools for specific functions and managing them together.
Okta's analysis reveals a fundamental shift in how enterprises adopt AI tools. Rather than consolidating around a single vendor, companies are now mixing multiple platforms—a behavior that has emerged in just four years of widespread enterprise AI availability. Anthropic's exceptionally strong growth rate (indexed at 100 versus OpenAI's 66.9) reflects both the vendor's recent acceleration in enterprise account acquisition starting in January 2026 and the broader diversification trend. The plateauing of growth among earlier entrants like OpenAI and Cursor over the same recent period suggests that enterprises have moved past the "evaluate the leader" phase into active portfolio building. This multi-platform approach (adopted by over 57% of companies) reflects a pragmatic enterprise posture: rather than assuming one AI tool solves all use cases, companies are selecting specialized tools for narrow workloads—code generation, writing, security, cloud infrastructure, and creative tasks—and managing them as a unified ecosystem.
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