Will AI create or take away more job opportunities?

Will AI create more jobs or cut them? I'll pull the latest forecasts on AI's net impact on employment.

The short answer is: Both — but most major global forecasts predict AI will create more jobs than it destroys in aggregate by 2030-2035, while causing painful displacement for specific occupations, skills and entry-level workers in the short term.

The numbers look different because "exposure" to AI, "displacement" and "new jobs created" mean different things.

1. What the major forecasts say — net positive, but disruptive

A key nuance from the IMF:

> Roughly half of those exposed jobs may benefit from AI through higher productivity, while for the other half AI could take over key tasks and reduce demand for labor

And from economists synthesizing all forecasts:

> All the major forecasts (WEF, McKinsey) say that overall impact is positive, but the balance masks the disruption in that the jobs lost and the jobs created have very different characteristics and are done by different workers

McKinsey also estimates that in its base case, about 11 million workers, roughly 7% of the workforce, would need to leave their occupations entirely.

2. Jobs AI is most likely to take away or shrink

The consensus across ILO, Brookings, OECD and WEF studies is that routine, predictable, rules-based and screen-based tasks are most exposed.

> Among traditional careers, data entry clerks, document processors, typists and routine administrative officers are probably the most immediately vulnerable

This includes:

The ILO estimates around one in four jobs globally has some exposure to generative AI, but says transformation is more likely than outright replacement.

3. Jobs AI is already creating

Between 2024 and 2026, AI has already created around 1.3 million net new jobs globally, including roles like AI Engineers, Machine Learning Researchers, MLOps Engineers, Data Annotators, AI Product Managers, Prompt Engineers, and Forward-Deployed Engineers.

Other new growth areas:

The broader WEF pattern is:

4. Why the aggregate "net gain" can feel like a net loss

> Employment levels for entry-level software developers and customer service representatives dropped after 2022 and especially after 2024, while employment for more seasoned workers remained stable

Researchers call young workers "canaries in the coal mine" because junior-level positions include the type of research, writing, and analysis that current AI can perform competently.

5. So, will AI create or take away more?

Historical pattern has been similar: automation destroys tasks, not necessarily entire occupations forever, and creates new tasks (AI trainers, auditors, ethicists, human-machine teaming managers) — but transition requires retraining. The WEF estimates 39% of core job skills will change by 2030, with AI and big data literacy as the fastest-growing demand.

> AI will eliminate or drastically reduce certain tasks and even entire roles. That part is real. However, the idea that AI will lead to net job destruction on a massive scale misunderstands how technology has always worked throughout history

Practical takeaway: If your work is repetitive, rule-based, and digital, risk is high — prioritize AI/data literacy, prompt and tool fluency, and human strengths AI struggles with (judgment, creativity, social skills, complex problem-solving). If you can use AI to augment your work, forecasts suggest you are more likely to be in the half that benefits than the half that gets displaced.