Gartner: Hiring Freeze Could Cost Firms 15% Premium by 2030

Businesses that halt entry-level hiring to deploy AI tools instead could face a 15% pay premium for early-career professionals by 2030. According to Gartner, 75% of organisations choosing AI over entry-level recruitment in 2026 will encounter these elevated costs within four years.

The warning comes from research presented at the Gartner Supply Chain Symposium in Orlando. Supply chain leaders are increasingly turning to AI to address workforce gaps and reduce operational costs across their organisations.

A Gartner survey conducted between July and October 2025 gathered responses from 509 supply chain leaders across multiple industries and sectors. The research found that 55% of respondents anticipate a decline in entry-level hiring due to agentic AI advancements.

Supply chains face ongoing disruption and workforce shortages. Many organisations view AI as a cost-effective solution to expensive hiring and training processes.

However, this approach could create longer-term problems for businesses. Organisations may find themselves without adequate talent pipelines and face employee dissatisfaction as career progression routes disappear.

Talent pipeline warnings

Simon Bailey, VP Analyst in Gartner's Supply Chain practice, presented the findings at the Orlando symposium. He outlined the potential consequences of replacing human workers with AI systems.

"Many organisations are attempting to manage uncertainty today by pausing entry-level hiring, but they will face talent shortages for themselves in the near future," says Simon Bailey, VP Analyst in Gartner's Supply Chain practice.

"AI is not a 'plug and play' replacement for people. Organisations that stop hiring and fail to develop early-career professionals, will soon face talent pipeline gaps, employee dissatisfaction and elevated hiring pay premiums, especially for AI-native talent."

Simon explained at the symposium that AI impact will extend beyond headcount reduction. The technology should support human-AI collaboration rather than wholesale replacement of workers.

Most survey respondents expect AI and agentic AI to drive supply chain performance over the next three years. This shows widespread adoption across industries and business sectors.

Companies that maintain early-career talent development alongside AI integration could see better outcomes. Senior staff would be freed to focus on strategic work and decision-making responsibilities.

Building talent pipelines alongside AI

Gartner advises that leaders  continue building talent pipelines while introducing AI capabilities. The research firm suggests four areas for action.

Organisations should audit supply chain processes and AI initiatives to understand talent impact. This could help redefine conversations around how AI creates new talent pathways.

Workflow and role redesign should ensure continuous learning and remove friction. Hands-on learning and team building can increase supply chain resilience and agility.

Talent pipelines require future-proofing through investments in learning, coaching, mentoring and AI simulations. These measures could protect supply chains and develop the emerging workforce.

Leaders should partner with chief human resources officers to strengthen employee value propositions and offset wage pressure. This includes targeting benefits such as work-life balance and flexible working arrangements.

Human and AI collaboration

The research suggests AI is better suited to augmenting than replacing human workers. Organisations adopting this approach may avoid the costs associated with talent shortages.

Supply chain leaders who halt entry-level recruitment risk creating skills gaps that become expensive to fill. The 15% premium represents the cost of neglecting workforce development during a period of technological change.

Gartner's analysis indicates that businesses maintaining balanced investment in both human talent and AI tools will achieve better long-term results. This approach allows organisations to benefit from automation while preserving institutional knowledge and career development structures.