Types of AI and their use in science

The paper examines how AI is contributing to the research process itself and provides some contextualized examples that illustrate applications of the techniques described. The paper aims to inform the rich debate within the science and science policy community by clarifying some of the concepts and techniques encompassed within the term ‘AI’.

Key takeaways

• Artificial intelligence (AI) is reshaping the scientific enterprise beyond computational assistance: AI is contributing to hypothesis generation and extending traditional methods of theory and experimentation.
• AI is not a monolithic technology, but encompasses a constellation of paradigms, each defined by distinct approaches to learning, inference or knowledge generation with different applications in the scientific context.
• A multitude of different AI techniques address descriptive, predictive, generative and optimization challenges within science.
• AI has found applications in research on medicine, climate science, genomics, social science and more.
• The reliance of AI on data means that computer science, mathematics and statistics intersect with social issues, including ethical questions and integrity of research.

Types of AI and their use in science

September 2025

DOI: 10.24948/2025.09

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This work was carried out with the aid of a grant from the International Development Research Centre (IDRC), Ottawa, Canada. The views expressed herein do not necessarily represent those of IDRC or its Board of Governors.