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ChatGPT leads enterprise AI, but model diversity is surging

Yesterday

New Relic has published its first AI Unwrapped: 2025 AI Impact Report, presenting data from 85,000 businesses on enterprise-level adoption and usage trends in artificial intelligence models.

ChatGPT's leading role

The report reveals that developers are overwhelmingly favouring OpenAI's ChatGPT for general-purpose AI tasks. According to the findings, more than 86% of all large language model (LLM) tokens processed by New Relic customers involved ChatGPT models.

Nic Benders, Chief Technical Strategist at New Relic, stated,

"AI is rapidly moving from innovation labs and pilot programmes into the core of business operations. The data from our 2025 AI Impact Report shows that while ChatGPT is the undisputed dominant model, developers are also moving at the 'speed of AI,' and rapidly testing the waters with the latest models as soon as they come out. In tandem, we're seeing robust growth of our AI monitoring solution. This underscores that as AI is ingrained in their businesses, our customers are realising they need to ensure model reliability, accuracy, compliance, and cost efficiency."

The report highlights that enterprises have been quick to adopt OpenAI's latest releases. ChatGPT-4o and ChatGPT-4o mini emerged as the primary models in use, with developers making near-immediate transitions between versions as new capabilities and improvements are launched. Notably, there has been an observed pattern of rapid migration from ChatGPT-3.5 Turbo to ChatGPT-4.1 mini since April, indicating a strong developer focus on performance improvements and features, often taking precedence over operational cost savings.

Broadening model experimentation

The findings also suggest a trend toward greater experimentation, with developers trying a wider array of AI models across applications. While OpenAI remains dominant, Meta's Llama ranked second in terms of LLM tokens processed among New Relic customers. There was a 92% increase in the number of unique models used within AI applications in the first quarter of 2025, underlining growing interest in open-source, specialised, and task-specific solutions. This diversification, although occurring at a smaller scale compared to OpenAI models, points to a potentially evolving AI ecosystem.

Growth in AI monitoring

As the diversity of model adoption increases, the need for robust AI monitoring solutions has also grown. Enterprises continue to implement unified platforms to monitor and manage AI systems, with New Relic reporting a sustained 30% quarter-over-quarter growth in the use of its AI Monitoring solution since its introduction last year. This growth reflects a drive among businesses to address concerns such as reliability, accuracy, compliance, and cost as AI systems become more embedded in day-to-day operations.

Programming languages trends

The report notes that Python solidifies its status as the preferred programming language for AI applications, recording nearly 45% growth in adoption since the previous quarter. Node.js follows closely behind Python in terms of both volume of requests and adoption rates. Java, meanwhile, has experienced a significant 34% increase in use for AI applications, suggesting a rise in production-grade, Java-based LLM solutions within large enterprises.

Research methodology details

The AI Unwrapped: 2025 AI Impact Report's conclusions are drawn from aggregated and de-identified usage statistics from active New Relic customers. The data covers activity from April 2024 to April 2025, offering a representative view of current AI deployment and experimentation trends across a substantial commercial user base.

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