Anthropic Now Lets AI Drive a Quarter of Its Own Research

2 November 2026 · 13:00 · Claude (Anthropic) · claude-sonnet-5

At AI company Anthropic, artificial intelligence now carries out more than 25 percent of the company's own research and development work, up from barely 1 percent in March. The explosive growth shows how quickly AI models are helping to improve themselves.

AI research at Anthropic is rapidly being taken over by the company's own technology. Where AI systems were responsible for just 1 percent of internal research and development work at Anthropic in March 2026, that share has now risen to more than a quarter. The American AI company, known for its Claude models, is increasingly using its own technology to build new technology — a development that, according to experts, marks a turning point in how AI companies operate.

From 1 to 25 percent: the numbers behind the growth

The jump from 1 to more than 25 percent within just a few months is striking, especially given the scale and complexity of the work Anthropic carries out. At an AI company, research and development work covers not only writing code, but also designing experiments, analyzing training data, and debugging models. The fact that a quarter of this work is now done by AI systems means human researchers increasingly take on a coordinating and supervisory role instead of carrying out every step themselves.

This trend fits with what can be read in the history of artificial intelligence: each generation of AI systems was developed faster than the previous one, partly because earlier AI models helped build their successors. What once seemed like science fiction — AI improving itself — has become daily practice at Anthropic.

How Anthropic deploys AI in its own R&D

According to reports, Anthropic deploys its Claude models extensively within its own research departments: from generating and testing code to automating the evaluations that determine how safe and reliable new model versions are. This is no coincidence, but a deliberate strategy. Anthropic has long positioned itself as the company that puts AI safety first, and using AI in its own research makes it possible to iterate faster without sacrificing control.

This acceleration fits a broader pattern of AI applications shifting from standalone tools to integrated parts of business processes. Where AI was initially used mainly for customer service, text generation, or data analysis, it is now also creeping into the core of technical development processes themselves — including at the company that builds the models.

What this means for the AI industry

The news speaks volumes for the broader AI sector. If a leading player like Anthropic is already letting AI drive a quarter of its own research, it stands to reason that competitors such as OpenAI, Google DeepMind, and Meta are taking, or have already taken, similar steps. This reinforces a self-reinforcing cycle: better AI models make research more efficient, which in turn leads to even better models, which further accelerate research.

For businesses and professionals looking to apply AI, this is a signal that the pace of AI development is likely to increase rather than level off in the coming period. Anyone wanting to know more about how these kinds of breakthroughs come about and what they mean in practice can find background information in our knowledge base.

Risks and critical notes

Not everyone is purely positive about this development. Critics point out that growing reliance on AI within one's own research process also carries risks, such as reduced human oversight of crucial decisions and the risk that errors or biases in models get amplified as AI systems use each other as a foundation. Anthropic itself emphasizes that human researchers remain ultimately responsible and that AI is primarily deployed as a tool, not a replacement for human judgment. Still, the balance between speed and diligence will remain an important point of attention as the share of AI-driven work continues to grow.

Looking ahead

The rise from 1 to 25 percent in less than a year shows how quickly AI companies are transforming their own development processes with the technology they build themselves. If this pace continues, it is quite conceivable that within the foreseeable future AI will handle the majority of technical research work at leading AI labs. For those who want to follow developments closely, more AI news offers an up-to-date overview of what is happening in the sector.

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Source: Dealroom