Gartner forecasts more AI-created jobs than losses by 2030, alongside hiring delays

More jobs overall would not mean an easier hiring market, especially for people starting their careers. Gartner’s newly reported workforce forecast expects AI to create 10.6 million jobs and eliminate 8.9 million by 2030, excluding China and India. Separately, it anticipates 5 million deferred jobs, with entry-level positions particularly exposed.

The projected net gain of 1.7 million jobs represents an eventual reversal, not Gartner’s assessment of the current balance. For 2026, the firm estimates that AI accounted for 2.2 million jobs lost against 1.6 million gained. John Lovelock, Gartner’s distinguished vice president analyst and chief forecaster, expects that relationship to turn around as organizations achieve greater success with AI deployments.

A job delayed is not counted as a job lost

Gartner treats hiring deferrals as a separate category from eliminated positions. These are jobs that would otherwise have been created, but where employers use AI as a reason to restrain hiring. Lovelock said companies initially held open positions while waiting to understand the effects of their AI projects. That makes a pause in recruitment a distinct part of the employment forecast.

Entry-level positions are expected to bear the greatest effect of those delays. Lovelock told Computerworld that many deferred positions would be filled after 12 to 24 months, though some would turn into job losses. He also expects the mix of employees in most industries and positions to tilt toward more senior staff. The forecast therefore distinguishes between a role disappearing and an applicant waiting longer for an opening.

Technology gains; government faces cuts

The technology industry is expected to record the largest net employment gain, with 1.9 million jobs created and 400,000 lost by 2030. Gartner does not identify the specific roles that will benefit, but expects some new work to involve implementing, maintaining and expanding AI systems. Its outlook is not simply that existing technology jobs survive: supporting AI itself is expected to require additional work.

Services industries, including financial services, are forecast to see substantial creation and losses. Gartner now expects a positive balance there, reversing its 2025 prediction that losses would exceed gains. Lovelock linked the revised outlook to growing demand for data- and system-oriented skills, alongside the sector’s ability to improve employee productivity and increase employment.

Government faces the opposite outlook: Gartner expects it to have the largest net job loss of any industry. Lovelock’s explanation is that governments lack the same revenue-growth incentive as businesses and are more likely to focus on efficiency and staff reductions. Those different incentives underpin sharply different employment expectations within the same forecast.

Changing tasks does not mean eliminating whole jobs

Gartner expects more than 20% of workers to see their jobs evolve by 2030, changing their tasks, methods or responsibilities. It forecasts high AI exposure for 70% of technologists. Exposure is not the same as redundancy: Lovelock told CIO Dive that an AI project can affect tasks spread across many jobs without taking over every task in any one role.

His expectation is that employers will need existing staff to develop new skills, rather than turn everyone into a prompt engineer. Most people, he said, will use AI supplied by their organization. For IT leaders, the responsibility extends beyond adapting their own teams: they will also have to help manage reskilling and changes to work across the wider business.