OpenAI Targets Fully Autonomous AI Researcher by 2028
OpenAI’s deep learning models are rapidly progressing, showing remarkable improvements in solving complex tasks. The organization is aiming to develop an intern-level AI research assistant by 2026 and a fully autonomous AI researcher by 2028. This marks a significant milestone in its broader mission to advance artificial intelligence.
The shift to a public benefit corporation supports these goals by allowing greater flexibility in raising capital and scaling innovation. Moving away from a non-profit framework enables the company to pursue larger research ambitions and attract the resources needed to accelerate progress.
Building Systems for Independent Discovery
The planned AI researcher is envisioned as a system capable of autonomously managing large-scale research projects. Such a model would independently design experiments, analyze data, and generate new insights without constant human supervision.
OpenAI is focusing on two core strategies to achieve this: continuous algorithmic innovation and scaling “test time compute” – the period during which models process and reason through complex problems. Current systems already perform at high human-competitive levels in advanced problem-solving tasks, such as mathematical challenges. By extending the computational horizon, these models could soon tackle more demanding scientific and technological questions.
In some cases, it may be worthwhile to dedicate massive computing infrastructure even entire data centers to a single complex research problem. This approach could dramatically increase accuracy, creativity, and the depth of AI-driven scientific breakthroughs.
Infrastructure and Responsible Growth
The restructuring also establishes a sustainable framework to support the company’s aggressive research timeline while maintaining responsible AI development. The non-profit foundation will hold a significant stake in the for-profit entity and guide long-term research priorities. It has also allocated substantial funding to initiatives focused on medical research, AI safety, and ethical innovation.
Additionally, the for-profit division’s ability to attract greater investment will help scale the infrastructure required for such ambitious goals. Plans include building 30 gigawatts of computing capacity an investment estimated at $1.4 trillion over the next several years. This massive expansion aims to push AI toward unprecedented levels of autonomy and capability by the end of the decade.
