Anthropic unseats OpenAI in the enterprise as AI model spending spikes

Anthropic’s Claude models surpassed OpenAI’s GPT suite in business adoption last month for the first time, according to an analysis by Ramp. The fintech platform provider began tracking generative AI model payments made by more than 50,000 businesses in January 2023.

Claude adoption permeated more than one-third of the companies using Ramp’s platform in April, as longtime leader OpenAI fell nearly three percentage points from the previous month to 32%. In the last year, Anthropic quadrupled its user base while OpenAI remained relatively flat.

Ramp Lead Economic Ara Kharazian cautioned against crowning Anthropic the definitive leader in business adoption. However, the model maker has gained ground on a chief competitor in a rapidly growing market.

“The truth is, we have never seen a software industry as dynamic, where newcomers can disrupt market leaders in a matter of months, and where the pace of development overrides the typical forces of vendor stickiness,” Kharazian wrote in a May 13 blog post.

Global AI spending across all categories is on a tear, according to the latest Gartner forecast published Tuesday. The analyst firm expects the market to balloon to $2.59 trillion this year, growing nearly 50% year over year.

Vendor and hyperscaler capital investments in hardware and infrastructure to support AI workloads comprise the largest market segment, accounting for nearly $1.5 trillion of projected spending. AI models occupy a more modest niche. Nonetheless, Gartner nonetheless expects AI model spending to more than double this year to almost $33 billion as enterprises expand their use of generative and agentic AI tools embedded in existing software applications.

“Model consumption will increase through multistep processes and integration into broad suites of tools as enterprises recognize the potential value of agentic automation,” the firm said in the report.

The AI model spending category is limited to LLMs and domain specific models and does not include applications that use “a model in the background,” Gartner Distinguished VP Analyst John-David Lovelock told Channel Dive via email. The spending spike is largely tied to model providers charging more for their products, he added.

Anthropic and OpenAI cut their teeth building LLMs but have recently pivoted to AI enablement.

OpenAI created a standalone consulting firm earlier this month after plunging into IT services by purchasing an ownership stake in Thrive Holdings last year. 

Anthropic launched a partner program in March and has continued laying groundwork for business adoption. Earlier this month, the company unveiled the Claude for Small Business AI suite and on Tuesday inked an alliance with KPMG that will deploy Claude Cowork in the professional services firm’s client delivery platform. Anthropic and PwC announced a similar partnership on May 13.

Both Anthropic and OpenAI recently made waves in the cybersecurity industry with the release of models designed to root out software vulnerabilities.

The two companies are currently fortifying themselves to weather industry consolidation, which has historically been the trend in software.

“AI technologies are revolutionary, but the fundamental market dynamics shaping the market are not,” Lovelock said. “As the foundational GenAI model race continues, GenAI markets will consolidate. There simply isn’t sufficient revenue for several redundant LLM ecosystems.”

Next year, Gartner projects AI to accrue roughly another trillion dollars in spending and approach $3.5 trillion. Growth in the AI model segment will slow slightly, growing roughly 80% year over year to nearly $60 billion.

Even that level of spending will only support a handful of contenders, according to Lovelock.

“Costs to train and operate LLMs will only become more extreme as efficiencies and technological improvements are offset by greater model scale and higher energy demand,” said Lovelock. “Even large, diversified companies will have difficulty convincing shareholders to support continued investment in races when their projected market share will not support the required return on investment.”