In an October 2025 YouTube livestream, OpenAI leadership revealed ambitious plans to create autonomous AI researchers by 2028, with AI research assistants arriving as early as September 2026. Here's everything we know about their timeline and what it means for the future of artificial intelligence.
What is OpenAI's AI Research Automation Goal?
OpenAI's Chief Scientist Jakub Pachocki —recently named to Time's 100 Most Influential People in AI list—revealed the company's primary objective: developing AI systems capable of conducting independent scientific research. This goes far beyond chatbots and AI assistants—OpenAI aims to automate the research process itself.
"As a research organization that is working on automating research, naturally we are thinking about how does this impact our own work," Pachocki explained during their October 2024 presentation. (7:16)
OpenAI's AI Research Timeline: Key Milestones
September 2026: AI Research Assistants Launch Target
OpenAI expects to develop AI research interns by September 2026—less than a year away. These won't be simple AI tools but systems capable of tackling substantial research problems independently.
Sam Altman OpenAI's CEO, stated: "We think it is plausible that by September of next year we have sort of an intern level AI research assistant." (14:37)
Key capabilities expected by September 2026:
- Meaningful acceleration of human researchers
- Ability to deploy significant computational resources
- Handling of substantive research problems
March 2028: Fully Automated AI Researchers Target
The ultimate milestone arrives in March 2028—exactly five years after GPT-4's launch. By this date, OpenAI aims to create fully automated AI researchers capable of autonomously managing entire research projects.
"We have like a legitimate AI researcher and this is the core thrust of our research program," Altman emphasized about the 2028 goal. (14:54)
Why AI Research Automation Matters for Scientific Discovery
OpenAI believes automated AI research represents the most significant long-term impact of AI development—surpassing even economic transformation.
Accelerating Scientific Breakthroughs
Pachocki outlined the potential: "The potential to accelerate scientific discovery, to accelerate the development of new technology—we believe that this will be perhaps the most significant long-term impact of AI development." (4:58 - 5:21)
The vision includes:
- 2026: AI making small discoveries
- 2028: AI achieving medium to large discoveries
- 2030+: Exponential compound effect on scientific progress
Altman illustrated the transformative potential: "If you can do these 200 years of compounding discoveries... not in 200 years but in 20 years or in two years... think about what could be possible." (28:45)
How OpenAI Measures AI Research Capabilities
OpenAI tracks progress toward automated research by measuring the time horizon of tasks their AI models can complete:
- Current AI models (2025): Can perform tasks requiring approximately 5 hours of human work
- Target capability: Extending this time horizon through test-time compute scaling
"The current generation of models is at right now is about five hours," Pachocki noted, referencing performance in competitions like the International Olympiad in Informatics. (5:40)
Test-Time Compute: The Technology Behind AI Researchers
The breakthrough enabling automated research is test-time compute (also called in-context compute)—essentially how long AI models spend "thinking" about problems.
Pachocki explained: "This is roughly how much time the model spends thinking, right? And if you look at how much time the model's currently spent thinking about problems and if you think about how much compute, how much time you would like to spend on problems that really matter such as scientific breakthroughs, you should be okay using entire data centers." (6:17 - 6:36)
For critical research problems, OpenAI envisions dedicating entire data centers not for training, but for allowing AI to think deeply about individual challenges.
The Path to Superintelligence Through AI Research
Pachocki addressed the broader implications: "We believe that it is possible that deep learning systems are less than a decade away from superintelligence—systems that are smarter than all of us on a large number of critical axes." (4:16 - 4:39)
This positions automated AI research as a critical waypoint toward artificial general intelligence (AGI) and eventually superintelligence, with AI researchers helping build progressively more capable systems.
Will OpenAI Meet Their AI Research Timeline?
Both Altman and Pachocki acknowledged significant uncertainty around their predictions:
"We may be totally wrong. We have set goals and missed them miserably before," Altman admitted. (14:18) "But with the picture we see, we think it is plausible." (14:37)
Pachocki added: "These particular dates we absolutely may be quite wrong about them, but this is how we currently think, this is currently how we plan and organize." (6:57 - 7:16)
Realistic Assessment of September 2026 Goal
Altman stated: "By a year from now, certainly with this September of 2026 goal, we have a realistic shot at a tremendously important step forward in capability." (37:27)
OpenAI's Strategic Focus on Research Automation
Automated AI research isn't just one project—it's the organizing principle for OpenAI's entire operation.
"Something that we organize our entire research program around is the potential to accelerate scientific discovery," Pachocki stated. (4:58)
This includes:
- $1.4 trillion in infrastructure commitments for 30+ gigawatts of compute
- Corporate restructuring around AGI development
- OpenAI Foundation's $25 billion commitment to AI-assisted disease research
What Automated AI Research Means for the Future
If OpenAI achieves its goals, we could see:
- Accelerated drug discovery and medical breakthroughs
- Faster materials science and clean energy solutions
- Rapid advancement in fundamental physics and mathematics
- Compounding effect as AI discoveries enable more AI discoveries
As Altman concluded: "I think in some number of years we'll look back at these years and we'll say this was kind of the transition period when AGI happened." (27:48 - 28:06)
Key Takeaways: OpenAI's AI Research Automation Timeline
- September 2026: Target for AI research assistant capabilities (intern-level)
- March 2028: Goal for fully automated AI researchers
- Technology: Test-time compute scaling enables extended thinking time
- Impact: Could compress centuries of scientific progress into years
- Uncertainty: OpenAI acknowledges dates may shift significantly
- Superintelligence: Possibly less than a decade away according to OpenAI
OpenAI's unprecedented transparency about these internal goals signals confidence in their AI research trajectory and suggests the world should prepare for rapid transformation in how scientific discovery happens.
Based on OpenAI's October 2025 Youtube presentation featuring Sam Altman, Chief Scientist Jakub Pachocki, and Wojciech Zaremba discussing the company's restructuring and AI research automation plans.
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