Which jobs are turning digital collar

A job turns digital collar when a growing share of its tasks can be done by AI systems and the person's work shifts toward setting those tasks, checking the output and owning the result. The best public data on where this is happening comes from the International Labour Organization's 2025 index of occupational exposure to generative AI. This page explains what it found and what exposure does and does not mean.

The short answer: clerical jobs are the most exposed, led by data entry clerks, typists and accounting and bookkeeping clerks. Some highly digital professional jobs, such as financial analysts and web and multimedia developers, have become more exposed since 2023. The ILO's main conclusion is that most jobs will be transformed rather than replaced, because most occupations still contain tasks that need people.

How the ILO measures exposure

The ILO scored thousands of individual work tasks from 0 (cannot be automated with generative AI) to 1 (could be done without a human operator), using AI models, a survey of 1,640 workers and rounds of review by international experts. It then grouped occupations into four gradients by the average score of their tasks and how much those scores vary (ILO Working Paper 140, 2025):

• Gradient 1: low exposure overall, with some highly exposed tasks.
• Gradient 2: moderate exposure, with a mix of exposed and unexposed tasks.
• Gradient 3: a significant share of tasks consistently exposed.
• Gradient 4: the highest exposure, consistent across most tasks in the job.

Exposure measures potential, not what has happened. A high score says a job's current tasks could largely be done with generative AI, not that the job will disappear.

The most exposed occupations

Thirteen occupations fall into gradient 4, most of them clerical. The table shows a selection from gradients 4 and 3 in the ILO's ranking (ILO Working Paper 140, Annex).

The common thread is work made of information tasks done at a screen: entering, formatting, checking, summarizing, translating and producing standard documents and code.

The digital jobs moving up

Between 2023 and 2025 the ILO raised its scores for several highly digitized occupations, including web and media developers, statistical and database specialists, and finance and software jobs. It links this to the fast growth in what AI models can do: working with images, audio and video, and gaining some agentic abilities to carry out multi-step tasks, work inside software and make decisions in context (ILO Working Paper 140).

The ILO adds that these jobs are closely tied to digital technology and many exist because of it, so they also have a strong capacity to take on new tasks built on AI tools. That is the digital collar shift in its clearest form.

How many people this affects

Globally, one in four workers is in an occupation with some exposure to generative AI, and 3.3% of global employment is in the highest exposure gradient. Exposure rises with country income: 34% of employment in high-income countries is exposed, compared with 11% in low-income countries. Women are more exposed than men, with 4.7% of female employment in the top gradient against 2.4% of male employment globally (ILO Working Paper 140).

What employers expect

The World Economic Forum's 2025 employer survey points the same way. Clerical and secretarial jobs such as cashiers, ticket clerks, administrative assistants and executive secretaries are expected to see the largest declines in absolute numbers by 2030, and postal clerks, bank tellers and data entry clerks are among the fastest-declining roles. Big data specialists, fintech engineers, AI and machine learning specialists and software developers are among the fastest-growing roles in percentage terms (WEF Future of Jobs Report 2025).

Transformed, not simply replaced

Because most occupations consist of tasks that still need human input, the ILO concludes that transformation of jobs is the most likely impact of generative AI. Its example from an earlier wave is the bank teller: when ATMs automated routine withdrawals, banks opened more branches and tellers moved toward more complex customer service and advice. The open question, the ILO notes, is how far policies help these jobs retrain and keep their existing workers rather than replace them.

If your job is on the list

• Sort your tasks. Separate the ones an AI system could draft from the ones that need your judgment, relationships or sign-off.
• Move toward checking and owning. The value shifts to knowing when an output is wrong and being accountable for what goes out.
• Use your domain knowledge. A bookkeeper who understands the accounts is far better placed to supervise AI-prepared reconciliations than someone who does not.
• Learn the tools on real work. Employers in the WEF survey rank AI and big data as the fastest-growing skills.