AI’s Impact on Jobs

AI is set to profoundly impact how people’s work is organized, but not in the way AI marketing presents:

Writers and graphic designers are already experiencing falls in job opportunities, as employers choose AI text and image generation instead 1.

Typists, travel consultants, customer service representatives, and other administrative workers are most likely to lose their jobs to AI 2.

New jobs such as quality controllers, prompt engineers, and linguistics experts are proposed as alternatives, 3 but without public and private sector investment in re-training, transition into these new jobs will be difficult 4.

The impact of AI on jobs and the idea of “work” is a complex issue linked to other social and economic changes. Here, we summarize a selection of research on this topic.

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More work, until it takes over

Despite all the promises that automation would make us work less, in reality we are working more 5.

Using generative AI reduces people’s critical thinking skills 6. Work expands and workers take on tasks outside their roles, AI blurs boundaries between work and non-work. Tasks slip into breaks and evenings reducing time for rest 5.

AI management systems spy on workers; assigning them work and scoring their performance. 2 People are being treated like machines, by machines, and can’t challenge the AI’s decisions, while also absorbing responsibilities that might previously have required additional staff 7.

The productivity surge promised by AI marketing gives way to lower-quality work, turnover, and other problems, which in turn lead to cognitive fatigue, burnout, and weakened decision-making 5.

AI in Recruitment

AI is also being used to score Resumés, CVs, and applications in recruitment processes.

41% of companies were using AI in recruitment and human resources as of late 2023, according to an IBM survey of international IT professionals 8.

AI algorithms tend to favor people from social groups who are already over-represented in the workforce. Therefore, AI makes discrimination worse 9.

Amazon, for example, had to ditch an AI recruitment tool that was biased against women 10.

AI is neither Artificial nor Intelligent

Not Artificial

AI relies upon vast amounts of “data work” undertaken by humans to train AI models. This data work involves things such as filtering videos, labelling objects in images, and transcribing documents 11.

Not Intelligent

AI is not as autonomous or capable as it is portrayed in popular media.

A global study of 305 executives found that the need for rigorous oversight and intervention was widely acknowledged among those who have implemented AI in their organizations, with a quarter reviewing AI outputs daily or more often 12.

AI has made dangerous and fatal mistakes such as autonomous vehicles injuring and killing pedestrians, or an experimental healthcare chatbot suggesting a mock patient commit suicide 13 14 15.

To be caught, such mistakes rely on human intervention, however the implementation of oversight procedures has lagged behind the implementation of AI itself 16.

Poorly Paid and Precarious Data Work

AI models need massive databases of human knowledge to train them. These databases are put together by unpaid, or poorly paid and precariously employed data workers.

Data workers are often freelance, earning around only US$1 per hour or employed on contracts for less than a week. They live in constant fear of losing their jobs. Their employers force them to work over 9 hours per day and refuse to pay overtime, and they feel powerless in responding 17.

You also (probably) do data work for free. You know those “Are you a robot?” reCAPTCHA boxes that ask you to copy out words or identify images? They use your responses to teach AI for Google’s book digitization, image recognition, and driverless cars 11.

Thankfully, workers are uniting to challenge the platforms that exploit them

Worker Mobilizations around AI in Arts, Culture, and Media. From Hollywood writers and game performers in the US to voice actors in Brazil, cultural workers around the world are striking, protesting, running campaigns and mobilizing to contest the use of AI in the workplace. This tracker published by Creative Labour and Critical Futures aims to document strikes, protests, campaigns and mobilizations by workers in the arts, culture and media 18.

Data Workers Inquiry does worker-led research, identifying urgent issues, formulating their own questions, and telling their stories in zines, documentaries, comics, essays, podcasts, and animations 19.

Turkopticon is a worker-led organization supporting Amazon’s freelance data workers. They help workers resolve disputes with Amazon and clients, allow workers to review clients, and provide a space for general questions and concerns 20.

Fairwork conducts action research and produces AI Principles to evaluate the working conditions of data workers 21. This research is used to advocate for policy changes to improve protections for data workers 22.

African Tech Workers Rising is working to transform the data supply chain by ensuring that workers’ voices shape the new world of work. That includes a binding sector-wide agreement committing tech companies to living wages, safe jobs and the right to organize 23.

The Data Labelers Association (DLA) advocates for fair treatment, better conditions, and recognition for data labelers worldwide, while pushing for workers to be at the center of policy and regulatory formulation 24.

Savethe.ai/jobs is an initiative of the Just Sustainability Design Lab in Collaboration with Digilabour, Universtity of Toronto.

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References

  1. Kawakami, R., & Venkatagiri, S. (2024). The Impact of Generative AI on Artists. Proceedings of the 16th Conference on Creativity & Cognition, 79–82. https://doi.org/10.1145/3635636.3664263 ↩

  2. Gmyrek, P., Berg, J., & Bescond, D. (2023). Generative AI and jobs: A global analysis of potential effects on job quantity and quality (No. 96; Working Papers). International Labour Organization. https://www.ilo.org/sites/default/files/2024-07/WP96_web.pdf ↩ ↩2

  3. Daugherty, P., Ghosh, B., Narain, K., Guan, L., & Wilson, J. (2023). A new era of generative AI for everyone. Accenture. https://www.accenture.com/content/dam/accenture/final/accenture-com/document/Accenture-A-New-Era-of-Generative-AI-for-Everyone.pdf ↩

  4. Berg, J. (2024, October 9). Minimizing the negative effects of AI-induced technological unemployment. International Labour Organization. https://www.ilo.org/resource/article/minimizing-negative-effects-ai-induced-technological-unemployment ↩

  5. Ranganathan, A., & Ye, X. M. (2026, February 9). AI Doesn’t Reduce Work—It Intensifies It. Harvard Business Review. https://hbr.org/2026/02/ai-doesnt-reduce-work-it-intensifies-it ↩ ↩2 ↩3

  6. Lee, H.-P. (Hank), Sarkar, A., Tankelevitch, L., Drosos, I., Rintel, S., Banks, R., & Wilson, N. (2025, April). The impact of generative AI on critical thinking: Self-reported reductions in cognitive effort and confidence effects from a survey of knowledge workers. Proceedings of the ACM CHI Conference on Human Factors in Computing Systems. https://www.microsoft.com/en-us/research/publication/the-impact-of-generative-ai-on-critical-thinking-self-reported-reductions-in-cognitive-effort-and-confidence-effects-from-a-survey-of-knowledge-workers/ ↩

  7. Wood, Alex. 2021. “Algorithmic Management: Consequences for Work Organisation and Working Conditions.” JRC124874. EU JRC. https://joint-research-centre.ec.europa.eu/publications/algorithmic-management-consequences-work-organisation-and-working-conditions_en. ↩

  8. Morning Consult. (2023). IBM Global AI Adoption Index—Enterprise Report. IBM. https://filecache.mediaroom.com/mr5mr_ibmspgi/179414/download/IBM%20Global%20AI%20Adoption%20Index%20Report%20Dec.%202023.pdf ↩

  9. Cole, M., Cant, C., Ustek Spilda, F., & Graham, M. (2022). Politics by Automatic Means? A Critique of Artificial Intelligence Ethics at Work. Frontiers in Artificial Intelligence, 5. https://doi.org/10.3389/frai.2022.869114 ↩

  10. Dastin, J. (2018, October 11). Insight—Amazon scraps secret AI recruiting tool that showed bias against women. Reuters. https://www.reuters.com/article/world/insight-amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK0AG/ ↩

  11. Casilli, A. A. (2025). Waiting for Robots: The Hired Hands of Automation (S. Brown, Trans.). University of Chicago Press. https://press.uchicago.edu/ucp/books/book/chicago/W/bo239039613.html ↩ ↩2

  12. AI Momentum, Maturity and Models for Success. (2018). https://www.sas.com/content/dam/SAS/documents/marketing-whitepapers-ebooks/third-party-whitepapers/en/ai-momentum-maturity-success-models-109926.pdf ↩

  13. Roy, A. (2024, January 26). How GM’s Cruise robotaxi tech failures led it to drag pedestrian 20 feet. Reuters. https://www.reuters.com/business/autos-transportation/how-gms-cruise-robotaxi-tech-failures-led-it-drag-pedestrian-20-feet-2024-01-26/ ↩

  14. Uber’s self-driving operator charged over fatal crash. (2020, September 16). BBC. https://www.bbc.com/news/technology-54175359 ↩

  15. Daws, R. (2020, October 28). Medical chatbot using OpenAI’s GPT-3 told a fake patient to kill themselves. AI News. https://www.artificialintelligence-news.com/news/medical-chatbot-openai-gpt3-patient-kill-themselves/ ↩

  16. Fuentes, O. V. (Director). (2024). Life of a Latin American Data Worker [Video recording]. https://data-workers.org/oskarina/ ↩

  17. Shitawa, W. (2024). Click Captives. The Unseen Struggle of Data Workers. In M. Miceli, A. Dinika, L. Sachenbacher, C. Salim Wagner, & K. Kauffman (Eds.), The Data Workers‘ Inquiry. https://data-workers.org/wilington/ ↩

  18. Creative Labour and Critical Futures. (n.d.). Worker Mobilizations around AI in Arts, Culture, and Media. https://creativelabourcriticalfutures.ca/resource-files/tracker-ai-mobilization-clcf.html ↩

  19. Data Workers Inquiry. (2026, March 5). Data Workers’ inquiry - Data Workers’ inquiry. Data Workers’ Inquiry. https://data-workers.org/ ↩

  20. Irani, L., & Silberman, S. (n.d.). Turkopticon. Turkopticon. Retrieved March 11, 2025, from https://turkopticon.net/ ↩

  21. Fairwork. (n.d.). About. Fairwork. Retrieved March 11, 2025, from https://fair.work/en/fw/principles/ai-principles/ ↩

  22. Fairwork Philippines, Riguer-Teodosio, G., Cainglet, J., Labudahon, G., & Kuttler, T. (2025, February 22). Fair and sustainable work futures for platform workers in the Philippines. Fairwork. https://fair.work/en/fw/blog/fair-and-sustainable-work-futures-for-platform-workers-in-the-philippines/ ↩

  23. UNI Global Union. (2025, March 27). African tech workers rising. https://uniglobalunion.org/about/sectors/ict-related-services/african-tech-workers-rising/ ↩

  24. Data Labelers Association (DLA) - Empowering the human workforce behind AI. (n.d.). https://datalabelers.org/ ↩