As of May 2025, artificial intelligence (AI) has solidified its role as a transformative force across industries, with science being a key beneficiary. This article explores the current state of AI in 2025, focusing on its applications in scientific research, and offers predictions for what we can expect by the end of the year.
AI in Science: The Current Landscape
AI has become a cornerstone in scientific research, driving breakthroughs in biology, physics, and environmental science. One notable advancement is in biology, where AI systems are being used to tackle complex problems like protein folding. Tools like AlphaFold have evolved, enabling researchers to predict molecular interactions with unprecedented accuracy, which has accelerated drug discovery. For instance, pharmaceutical companies are leveraging AI to identify potential drug candidates faster, potentially saving years in development timelines.
In environmental science, AI is being used to address global challenges. AI models can now predict climate-related disasters by analyzing vast datasets on weather patterns and historical climate changes. This capability allows scientists to optimize energy usage and develop sustainable solutions, such as more efficient renewable energy grids. Additionally, AI’s role in scientific discovery extends to automating research processes. Systems like Sakana’s AI Scientist can autonomously conduct experiments, analyze data, and even draft research papers, streamlining the scientific method.
However, the integration of AI in science isn’t without challenges. Many benchmarks used to evaluate AI systems, such as those for general knowledge and reasoning, have become saturated—meaning AI systems are scoring so high that these tests are no longer useful for measuring progress. This has prompted researchers to develop new benchmarks like MMMU and GPQA, which are designed to push AI capabilities further.
Broader Trends in AI
Beyond science, AI’s evolution in 2025 is marked by several key trends. Multimodal AI models, such as OpenAI’s Sora for video generation, have expanded AI’s capabilities beyond text to include audio, images, and video. This has opened new avenues for scientific visualization and data interpretation. Additionally, autonomous AI agents, like Microsoft’s Copilot, are automating complex tasks, from lab workflows to data analysis, freeing up researchers for more creative endeavors.
The global AI race is heating up, with the U.S. leading in the number of notable AI models released (40 in 2024, compared to China’s 15). However, Chinese models are closing the quality gap, with performance differences on benchmarks like MMLU shrinking to just 1.7% by early 2025. This competition is driving innovation but also raising concerns about responsible AI use, especially as incidents related to AI misuse rise.
What’s Coming by the End of 2025
Looking ahead to the end of 2025, several developments are on the horizon. First, we can expect further advancements in agentic AI—systems that can autonomously plan, reason, and execute tasks. These agents will likely become more integrated into scientific research, potentially acting as “virtual scientists” that handle entire research projects with minimal human oversight. This could lead to a surge in research output, particularly in fields like biology and materials science.
Second, the focus on responsible AI will intensify. With new benchmarks like HELM Safety and AIR-Bench gaining traction, researchers will prioritize improving AI’s factuality and safety, especially in scientific applications where accuracy is critical. Companies may also face pressure to adopt more systematic AI governance practices, driven by regulatory changes like the EU’s AI Act and increasing scrutiny in the U.S.
Finally, AI’s role in education and workforce development will expand, impacting how science is taught and practiced. Initiatives like the U.S. Department of State’s AI education programs will likely lead to more AI-literate researchers, fostering a new generation of scientists who can seamlessly integrate AI into their work.
Conclusion
In 2025, AI is already a game-changer in science, accelerating discoveries and tackling global challenges. By the end of the year, we can anticipate even more autonomous AI systems, a stronger emphasis on responsible AI, and broader access to AI education. As these trends unfold, AI will continue to redefine the boundaries of scientific exploration, promising a future where human and machine collaboration drives unprecedented innovation.
