1. Introduction
Traditional sociology relies on observation, interviews, surveys, and qualitative/quantitative analysis to understand social phenomena. The explosion of AI—especially large language models (LLMs) and machine learning—is fundamentally changing the way social data is collected, processed, and interpreted (Alvero et al., 2026; Joyce et al., 2021).
AI is not only a supportive tool but also a new object of study, leading to the emergence of the sub-discipline “Sociology of AI.” This article focuses on analyzing three main aspects: (1) impacts on research and methodology; (2) changes in career and education; and (3) ethical issues along with future prospects.
2. Impacts on Sociological Research: Automation and Scale Expansion
AI offers significant advantages in processing big data. AI tools can analyze millions of social media posts, detect sentiment trends, predict social behaviors, or simulate research subjects without the need for large-scale real-world surveys.
- Support for writing and qualitative analysis: A survey of 433 authors of sociology papers shows that about one-third of researchers use AI weekly, primarily for drafting, summarizing, editing, and translating. AI helps save considerable time on repetitive tasks, allowing sociologists to focus more on deep theoretical interpretation (Alvero et al., 2026).
- Simulation and social experiments: LLMs can create “virtual subjects” to test initial hypotheses before experimenting with real humans, reducing costs and increasing the feasibility of research.
- Multimodal integration: AI supports text coding, image analysis, or predicting cultural trends from historical data.
However, AI has not completely replaced the creativity and social sensitivity of human researchers. Many sociologists remain concerned about the accuracy, bias, and lack of transparency in AI outputs (the “black box” problem) (Alvero et al., 2026; Ruzzeddu, 2025).
3. Changes in Education, Training, and Professional Roles
AI is reshaping sociology curricula. Students need to learn basic programming skills, AI data analysis, and “AI literacy” (critical understanding of AI). Many universities have introduced courses on “AI and Society” to equip students with critical thinking about inequality and the future of work.
Regarding careers:
- Partial automation: According to Anthropic’s research (2025), approximately 18% of sociology-related tasks can be automated and 40% can be augmented by AI. Repetitive tasks such as quantitative data analysis will decrease, but work requiring social interpretation, policy, and human interaction remains essential (Bouchrika, 2026).
- New opportunities: Sociology opens up positions in “AI policy,” AI ethics, research on behavior within AI systems, and consulting to reduce inequality caused by AI. Many organizations are seeking sociologists to assess the social impact of technology (Joyce et al., 2021; Othersociologist, 2025).
AI helps sociologists shift from “data collectors” to “interpreters of social meaning” and “policy designers.”
4. Ethical Issues and Social Inequality
AI is not neutral; it often reproduces existing social biases (gender, race, class). Algorithms used in recruitment, medical diagnosis, or crime prediction risk deepening inequality if the training data is biased (Joyce et al., 2021; Tai, 2020).
Sociology plays a pivotal role:
- Criticizing how AI turns social data into “objective data” while ignoring contexts of power and inequality.
- Proposing ethical frameworks: transparency, accountability, privacy protection, and bias mitigation.
- Promoting leadership of minority groups and indigenous peoples in AI policy (Othersociologist, 2025).
Without the involvement of sociology, AI risks becoming a tool that reinforces the existing social order rather than promoting justice.
5. Future Prospects: Toward Symbiosis Between AI and Sociology
The future of the sociology profession lies in the integration of “Sociology of AI” (studying AI as a social phenomenon) and “Sociology with AI” (using AI as a tool). These two directions need to be more closely integrated to avoid “toolification” of AI or missing opportunities (Airoldi, 2025; Davis & Sloane, 2026).
Sociologists will take a leading role in:
- Designing human-centered AI oriented toward social sustainability (SDGs).
- Training new generations capable of combining critical social thinking with advanced technology.
- Monitoring and adjusting global AI policies.
6. Conclusion
AI is not a threat but a powerful catalyst for the sociology profession, provided that researchers proactively adapt and maintain their central position in shaping technology. The sociology profession under the impact of AI will become more interdisciplinary, more practical, and more applicable, while preserving its core mission: understanding and improving human society.
For the sociology profession to develop sustainably in the AI era, research institutes and universities need to invest in digital skills training, promote interdisciplinary research, and build clear ethical frameworks. Sociology will not only “survive” but also lead the future of AI—a future that is more equitable and humane.
References
1. Alvero, A. J., et al. (2026). Generative AI in Sociological Research: State of the Discipline. Sociological Science, 13, 45-62.
2. Bouchrika, I. (2026). AI, Automation, and the Future of Sociology Degree Careers. Research.com.
3. Davis, J. L., & Sloane, M. (2026). AI's Sociological Era. Social Science Computer Review.
4. Joyce, K., et al. (2021). The Future of Artificial Intelligence Requires the Guidance of Sociology. Drexel University.
5. Othersociologist. (2025). Sociology of Artificial Intelligence.
6. Ruzzeddu, M. (2025). Understanding Artificial Intelligence: the role of Sociology. RTSA.
7. Tai, M. C. T. (2020). The impact of artificial intelligence on human society and bioethics. Tzu Chi Medical Journal.
Author: Nguyen Duy Hai