The jobs that AI will change, the jobs it will replace, and the ones that will survive, according to Indeed

Debates over whether AI will replace skilled human professionals often cast the question as all‑or‑nothing: Either machines take over every job or humans remain indispensable.

But the latest AI at Work Report 2025 from the Indeed Hiring Lab offers a more nuanced picture. Instead of wholesale replacement, AI is likely to transform the nature of how skills are used — with human oversight, context, and judgment still playing crucial roles.

Indeed’s researchers assessed almost 2,900 common work skills to see how susceptible they are to transformation by generative artificial intelligence along two axes: problem‑solving capability and physical necessity.

The result? A classification into four tiers of transformation potential: minimal, assisted, hybrid, and full.

Rather than asking “will AI replace all human skills?”, we should consider which ones are most exposed to change.

According to the Indeed analysis, only a small fraction of skills (about 1 %) fall into the “full transformation” category, meaning AI could autonomously perform tasks using those skills. Many more will fall into “hybrid” or “assisted” categories, where humans still must validate, supervise, or step in on edge cases. Many roles remain shielded from immediate AI disruption. Yet even under ideal adoption scenarios, almost half of a job’s underlying skills could still undergo significant transformation.

Here is a breakdown of key dimensions and examples from the Indeed report, illustrating which kinds of human skills are most and least vulnerable to AI transformation.

Jobs that still demand human presence

Roles that require physical execution or deep interpersonal connection tend to resist transformation. The Indeed report classifies skills like patient care, employee relations, and network administration as falling into the minimal‑transformation category. In these areas, human performance is expected to stay largely unchanged, at least for now

Jobs that could get AI support but not replacement

Some roles allow AI to act in a support capacity, offering templates, basic research or prompts, without  taking over fully. These include environmental law, trading, and teaching. When it comes to AI-supported roles, the human remains the lead actor and must apply judgment beyond what AI suggests.

Hybrid jobs: work shared between humans and AI

In this category, AI handles much of the routine execution, while humans oversee, audit, and intervene in ambiguous or exceptional cases. Examples might include medical coding, travel planning, and proofreading.

Jobs entirely replaceable by AI are rare — but possible in specific niches

Only about 1 % of the analyzed skills are currently rated as fully replaceable by AI. They tend to be narrow, structured tasks (e.g. basic math operations, image classification, prompt engineering) which exist within broader processes

Software development jobs are among the most impacted

Technical skill sets are among those more vulnerable to AI replacement. The report notes that 82 % of skills mentioned in software development job postings fall under hybrid transformation. AI already handles many routine coding tasks, leaving human developers to supervise, refine, and resolve edge cases.

Core nursing jobs appear safe. But administrative tasks face disruption

Core nursing skills, such as direct patient care, are less likely to be replaced by AI. But peripheral tasks such as administrative paperwork, translation support, and documentation hold potential to become hybrid roles. Some 14 % of general admin tasks and 9 % of healthcare admin skills in nursing are considered replaceable with AI to some degree.

Change is possible, but not inevitable

Despite AI’s capabilities, actual adoption requires businesses to be ready. In its report, Indeed emphasizes that the skill classification reflects potential transformation, not guaranteed replacement. In both AI assisted and hybrid roles, the human touch is still needed for ambiguous cases, to interpret context, and to validate AI outputs. Overall, oversight skills, domain expertise, and the ability to reason beyond AI’s reach will remain essential.

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