The notion that artificial intelligence will trigger mass layoffs remains contested. The evidence instead points to a redistribution of functions: managers today oversee nearly twice as many employees as just a few years ago, while routine tasks are increasingly delegated to algorithms. This is less about direct job replacement than about gradual shifts in organizational structures and methods of supervision.
Even so, in everyday professions it is the automation of repetitive functions that is most visible. Translation, proofreading, stenography, and legal support have already been partially transferred to AI systems, raising questions about the role of these professions in the near future.
Artificial intelligence has become a force reshaping society. Generative systems such as ChatGPT are now part of daily life: anyone with a smartphone can interact with AI. Yet as adoption grows, so does the list of professions under threat: algorithms are capable of taking on tasks that can be formalized and repeated in similar patterns.
Among the first to be affected are jobs built on routine functions.
Translation. Communication across languages inevitably runs into barriers. While English is taught as a second language in many countries, in practice most people prefer their mother tongue. Services such as Google Translate and DeepL now provide real-time translation in more than 200 languages, enabling people to converse freely and expanding opportunities in education and business. A human translator is usually limited to a handful of languages, whereas AI removes such constraints and makes communication far simpler.
Court transcription. Courtrooms have traditionally relied on stenographers, typing every word of proceedings on a special machine. The job demands immense speed and flawless accuracy. Today AI can perform these functions: systems can transcribe hearings, and multiple algorithms working in parallel deliver the required precision at a fraction of the cost. In the future, the role of court reporters may evolve into overseeing the accuracy and completeness of artificial stenographers.
Text editing. In newspapers and publishing houses, copy editors polish texts, eliminating errors. Machines handle this with ease: trained on grammar and equipped with vast dictionaries, they can refine even a rough draft into acceptable form. AI performs corrections instantly, so instead of an entire department, a single IT specialist can oversee the flow of materials.
Legal support. Junior lawyers are typically assigned repetitive tasks: searching case law, drafting briefs, processing expert testimony. Because such documents follow predictable patterns, AI can quickly take over their preparation. This reduces the need for entry-level associates and cuts costs for clients. At the same time, demand is emerging for a new generation of paralegals—professionals with AI skills who will supervise the process.
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Yet before assuming that algorithms will fully replace humans, it is worth considering the complexity of these professions. A machine can translate text or record a court hearing, but it cannot grasp tone, emotion, or context—all of which alter meaning. Moreover, such roles often serve as entry points in a career: editors frequently begin with proofreading, and lawyers with junior associate work.
AI will continue to penetrate new fields and reshape the very nature of work. Like outsourcing production abroad in search of cheap labor, replacing people with machines brings immediate savings but may entail long-term costs. Blindly cutting staff for short-term gain risks dismantling systems that train future professionals.
Rather than seeing AI solely as a threat, it should be regarded as an opportunity. An industry is already emerging to train people in working with new systems. The challenge is how to extend access more broadly and equip society with the skills needed to participate in this new economy.
Any change is painful. Every job displaced by AI creates space for others. But simply replacing people with machines for the sake of savings today may lead to a shortage of human capital tomorrow. Pennies saved now risk turning into dollars lost later.
Sheldon H. Jacobson, professor of computer science at the Grainger College of Engineering, University of Illinois Urbana-Champaign, applies risk analysis methods to public policy.