Is AI Creating or Destroying Jobs?

Is AI Creating or Destroying Jobs in 2026?

It’s no secret that AI has been taking a prominent seat in how we work, do business, create digital material, and even interact with other people. This begs the question, “Is AI creating or destroying jobs?” If something becomes so inundated in how we expedite processes or automate tasks, it’s natural to wonder if it will eventually take the place of human jobs. However, today’s experts see that AI is doing both: while it’s making some jobs obsolete, it’s creating opportunities in other places.

AI Is Doing Both

According to today’s experts, AI is currently doing both: it is clearly creating new jobs and tasks while also restructuring and in some cases eliminating others, with the balance depending on time horizon, occupation, and policy choices. A fair answer has to acknowledge that net effects are positive in some areas and negative in others, and that distribution – who gains, who loses, and who can adapt – is the core issue.

Is AI Creating or Replacing Jobs? What Recruiters Need to Tell Leaders in 2026

For talent leaders and recruiters, the real AI question isn’t “Will robots take all the jobs?” It’s “Where is work actually changing, and how do we hire and reskill fast enough?” The latest LinkedIn, OECD, and IMF data give a clear, evidence‑based way to answer that question. Let’s dive into what the experts are saying about AI’s role in creating or destroying jobs in 2026.

What LinkedIn’s 2026 Data Really Says

LinkedIn’s 2026 Global Labor Market insights show that employers created around 1.3 million new AI‑related roles worldwide in just two years, including AI engineers, data‑center roles, data annotators, and other “new‑collar” technical jobs. In parallel, LinkedIn reports a 70% year‑over‑year increase in U.S. roles that require AI literacy, alongside surging AI‑related learning and posting activity on the platform, which signals rapid skills rotation rather than simple job loss.

Yet overall hiring is still about 20% below pre‑pandemic levels, driven more by macro factors like higher interest rates and post‑pandemic rebalancing than by AI itself. AI exposure is broad: LinkedIn notes that AI is now embedded in “nearly every job function,” meaning most jobs are changing in content and skill requirements instead of disappearing outright.

For recruiters, the implication is direct: demand is shifting toward AI‑literate talent and hybrid roles faster than headcount is shrinking.

How Other Authorities See the Risk

Major labor‑market institutions echo this “transform, not just replace” story. The OECD estimates that around 27% of jobs in member countries are at high risk of automation, based on the share of tasks that are easily automatable, yet many workers already using AI report less monotony and better conditions. The IMF finds that about 40% of global employment is exposed to AI, with roughly 60% of jobs in advanced economies affected in some way; exposure here means tasks may change, be augmented, or be automated, not that all these jobs vanish.

Both institutions stress that AI can raise productivity and incomes overall, but it is likely to increase inequality unless governments and firms invest in upskilling, retraining, and safety nets. For employers, that translates into a simple tension: AI is an accelerator for value creation and a risk amplifier for talent gaps at the same time.

AI: Job Creator or Destroyer?

When asking if AI is creating or destroying jobs, there are four key aspects to look at to get the bigger picture: Time Horizon, Types of Work, Who Benefits, and Policies.

1. Time horizon

Short term (now through the late 2020s): Evidence from LinkedIn, the OECD, and the IMF points to more augmentation and new role creation at the AI frontier, plus churn and re‑bundling of responsibilities, rather than mass unemployment.

Medium/long term: As AI models improve and get cheaper, a larger share of routine cognitive tasks becomes automatable, which raises risks for mid‑skill and some high‑skill jobs unless organizations and policymakers move aggressively on adaptation.

2. Types of Work

Growing roles: High‑skill, AI‑building and AI‑complementary roles—machine learning specialists, data professionals, AI product roles, and advanced technical trades supporting AI infrastructure—are expanding quickly.

Most exposed to displacement: Routine, process‑driven cognitive work such as standard reporting, basic coding, some back‑office operations, and certain entry‑level professional tasks faces the most direct automation pressure.

Changing but hard to fully automate: Jobs in healthcare, skilled trades, and in‑person services tend to be structurally harder to replace due to physical, social, and regulatory constraints, even as AI reshapes documentation, diagnostics, and scheduling tasks around them.

3. Who Benefits

Likely winners: Workers who can already use AI—or can access training to learn it—often better‑educated employees in advanced economies, stand to gain productivity and, often, higher earnings.

At‑risk groups: Lower‑wage and older workers, and those in regions or firms that under‑invest in upskilling, are more likely to experience AI as job loss, role shrinkage, or downward mobility.

4. Policies

With reskilling and internal mobility: AI can flip from a net job destroyer in particular functions to a net creator across the business by driving productivity‑led growth and opening new roles in AI operations, data quality, workflow design, and higher‑touch customer work.

Without them: Automation amplifies churn and inequality: more people clustered in a small number of high‑productivity, high‑pay roles, and more workers pushed into precarious or underemployed positions.

A practical illustration for HR and TA: a support‑center agent might lose ticket‑triage work to an AI assistant, but with training they can move into higher‑touch customer success, complex escalation handling, or internal AI‑ops and prompt‑optimization roles. Without those pathways, the same automation shows up on the P&L as headcount reduction.

The Big Picture

AI isn’t simply creating or destroying jobs; it’s redrawing the map of work. In the 2024–2026 data, AI is clearly generating new roles and fresh skills demand. LinkedIn tracks over 1.3 million new AI‑related jobs and roughly 70% annual growth in AI‑literate roles in the U.S., even as it reshapes or automates more routine tasks.

At the same time, institutions like the OECD and IMF estimate that roughly a quarter to two‑fifths of jobs globally are significantly exposed to AI‑driven change, a signal that what people do inside their jobs is shifting long before those jobs disappear altogether.

That’s why the real question for employers isn’t just “net jobs up or down,” but “who is ready to transition, who is protected, and how intentionally are we designing training, internal mobility, and safety nets so AI becomes a job‑enhancer instead of a job‑destroyer?” This lens allows everyone to determine for themselves whether AI feels like an opportunity or a disruption for their workforce.