National context shapes AI’s transformation of sociology
A new paper co-authored by Dr Fanqi Zeng argues that AI is transforming the field of sociology by enhancing tasks such as large-scale data analysis, literature reviews, and theoretical modelling.
However, the integration of AI within sociology has not been uniform across the world; instead, it has been shaped by each country’s academic traditions, institutions, and social contexts.
The study suggests that AI in sociology should be studied in three separate ways: as a resource for sociologists to use; as a transformative force changing society and thus something to be investigated; and as a form of symbolic engagement, reflected in how research communities publicly present their engagement with AI through seminars, conference agendas and faculty profiles.
Dr Zeng and co-author Dr Xiaoguang Fan compare AI use in China and the US by analysing information from leading sociology departments, faculty research profiles, and national sociological conferences – suggesting that AI has impacted sociology in each country in distinctive ways.
Firstly, the paper notes that the US adopted AI much earlier than China, meaning AI use within American sociology is becoming increasingly routine. However, Chinese AI use has accelerated rapidly since 2023, and has benefitted from learning from earlier developments – selectively incorporating the best technological developments while maintaining existing research traditions.
The analysis finds that in China, AI research is connected to machine learning, ‘intelligentisation’, governance, and broader societal transformation. Chinese AI research also tends to be more solution- and policy-oriented, which may partly reflect the influence of state-linked funding and institutional structures.
In contrast, AI research in the US focuses more heavily on algorithms and large language models (LLMs), alongside topics such as inequality, prediction, and the impact of AI on sociology itself.
The US therefore appears more focused on using AI as an academic research method and treating AI as an object of sociological inquiry, while Chinese sociology places greater emphasis on practical, societal, and policy applications.
The emergence of country-specific tools such as ChatGPT and DeepSeek could further shape how AI is incorporated into sociology in each country.
“It’s clear that AI won't create one universal form of sociology. Epistemological pluralism is expected to continue in the AI era as different sociological communities incorporate AI according to their own institutional structures, theoretical traditions, cultural contexts and societal roles.”
Despite this, the paper argues that these contrasts should not be seen as inherent differences between Chinese and American ways of thinking. Instead, they reflect the varying contexts in which sociological research takes place.
For example, Chinese funding priorities and policy structures may encourage research focused on governance and practical applications, while the US has a more diversified research environment that supports a wider range of academic and critical approaches to AI.
Importantly, the authors caution that the data only reveals what sociology departments and professional associations publicly present as AI-related research, which is not necessarily exactly how individual sociologists use AI behind the scenes.
“It leads us to the question: is AI simply becoming more visible in sociology, or is it actually changing how sociological knowledge is produced?”
Original Publication
Zeng, F., Fan, X. (2026). Bridging AI and sociology: a comparative analysis of AI integration in China and the US. Theor Soc 55, 76. https://doi.org/10.1007/s11186-026-09743-6
