ZDNET’s key takeaways
- Programming is AI’s killer app.
- The highest enterprise AI, particularly for programming, is Anthropic.
- Open-source AI is lagging behind its proprietary opponents.
Should you had been to ask J. Random Consumer on the road what the most well-liked enterprise AI Giant Language Mannequin (LLM) is, I wager you they’d say OpenAI‘s ChatGPT. As of mid-2025, nonetheless, Anthropic is the leading enterprise LLM provider, with 32% of enterprise utilization, in line with Menlo Ventures, an early-stage enterprise capital agency.
Earlier than you get too excited, although, take into account that Menlo Ventures is a serious Anthropic investor. The agency has backed the corporate by way of a number of important funding rounds, together with main their Sequence D spherical and collaborating of their $3.5 billion Sequence E, which valued Anthropic at $61.5 billion.
Additionally: What happened when Anthropic’s Claude AI ran a small shop for a month (spoiler: it got weird)
In different phrases, Menlo Ventures has billions of causes to reward Anthropic. That stated, others additionally view Anthropic as the highest enterprise AI firm. As AI Journal put it, “Anthropic has established itself as the premier enterprise AI company by way of its Claude household of LLMs, attaining exceptional 1,000% year-over-year development to achieve $3 billion in annual recurring income.” Even by hyper-aggressive AI requirements, that is actual development.
Behind Anthropic, you will discover OpenAI, which now has 25%; Google with 20%; and Meta Llama with 9%. All the way in which within the again, with a mere 1% you will discover DeepSeek, adopted by the remainder of the pack. Menlo Ventures credit Anthropic’s speedy ascent to the robust efficiency of its Claude Sonnet and Claude Opus fashions.
(Disclosure: Ziff Davis, ZDNET’s father or mother firm, filed an April 2025 lawsuit towards OpenAI, alleging it infringed Ziff Davis copyrights in coaching and working its AI techniques.)
These numbers mirror the proportion of manufacturing AI use, not spending. They had been derived from a survey of 150 technical decision-makers at enterprises and startups constructing AI functions in the summertime of 2025.
What’s behind Anthropic’s success?
Three various factors are driving Anthropic’s rise. The primary is what Menlo Ventures calls “AI’s first killer app”: Code technology. Whereas AI-created code quality remains questionable, however, extra builders are utilizing AI programming instruments than ever, and Claude has develop into programmers’ best choice with 42% of the market share. That is double OpenAI’s 21% share.
There are concrete examples of Anthropic growth packages gaining recognition. For example, in only one 12 months, Claude helped remodel GitHub Copilot right into a $1.9-billion ecosystem. Claude Sonnet 3.5‘s 2024 launch confirmed how LLM breakthroughs could make attainable completely new classes corresponding to AI IDEs, Cursor and Windsurf; vibe app builders, Lovable, Bolt, and Replit; and enterprise coding brokers, Claude Code and All Palms.
One more reason Anthropic is profitable is its use of reinforcement learning with verifiable rewards (RLVR) to coach its LLMs. Behind that sophisticated title lies a easy idea: You present clear, binary suggestions (1 for proper, 0 for incorrect) on the mannequin’s output. This works properly for programming AI instruments, the place the code both works or would not.
Anthropic has additionally led the way in which to LLMs that take step-by-step approaches to fixing issues and use exterior instruments to drag in knowledge to ship higher solutions. Briefly, Anthropic has been a pacesetter in creating AI agents. In addition to serving to individuals and programmers, this method can assist LLMs iteratively enhance their responses and combine instruments like search, calculators, coding environments, and different sources through the Model Context Protocol (MCP). This new open-source protocol allows LLMs and AI brokers to seamlessly join with the huge, ever-changing panorama of real-world knowledge, instruments, and providers.
Additionally: 7 strategic insights business and IT leaders need for AI transformation in 2025
That is vital as a result of Menlo Ventures additionally discovered that it is not value that drives corporations to alter LLMs, it is efficiency. “This creates an surprising market dynamic: At the same time as particular person fashions drop 10x in value, builders do not seize financial savings through the use of older fashions; they only transfer en masse to the best-performing one.”
This dynamic could change as soon as LLMs begin to mature and fashions start to achieve comparable efficiency ranges. For now, although, as LLMs enhance massively from one launch to a different, corporations are keen to pay for the latest and quickest.
AI within the enterprise
The research additionally discovered that corporations are steadily shifting from constructing and coaching fashions to inference, that’s, with fashions really working in manufacturing. Startups are main the way in which, with 74% of builders now stating that the majority of their workloads are in manufacturing. Giant enterprises aren’t far behind, with 49% reporting that the majority or almost all of their computer systems are in manufacturing. Briefly, enterprises are actually utilizing AI, not merely constructing AI.
Lastly, the researchers stated that open-source LLMs have declined to 13% of AI workloads at this time from 19% six months in the past. The market chief stays Llama, albeit that Llama isn’t really open source.
Additionally: How agentic AI is transforming the very foundations of business strategy
However, extra open-source LLMs have been showing. These embody new fashions from DeepSeek (V3, R1), Bytedance Seed (Doubao), Minimax (Textual content 1), Alibaba (Qwen 3), Moonshot AI (Kimi K2), and Z AI (GLM 4.5) within the final six months.
They’re simply not used a lot. That is as a result of, regardless of their benefits, “larger customization, potential price financial savings, and the flexibility to deploy inside personal cloud or on-premises environments,” their efficiency has continued to “path frontier, closed-source fashions.” Add in that lots of the best-performing open-source LLMs to this point are from Chinese language corporations that Western companies are cautious of, and open-source LLMs seem like stalling out.
Additionally: Anthropic tripled its revenue in 5 months – and this is why
So what does all this result in?
“Predicting the way forward for AI is usually a idiot’s errand. The market adjustments by the week, with thrilling new mannequin launches, developments in basis mannequin capabilities, and plunging prices,” Menlo Ventures stated. Nonetheless, “situations are ripe for a brand new technology of tolerating AI companies to be constructed on high of at this time’s foundational constructing blocks.”
The query stays, nonetheless, “What is going to these foundational constructing blocks be?” OpenAI? Google, Meta? Anthropic? Keep tuned. We’re not but near having the ability to say which AI fashions will in the end find yourself on high.
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