AI Cuts Entry-Level Tech Jobs by Over 50% Since 2019, Driving Talent Shift and Salary Gains in 2025

The rapid advancement of artificial intelligence is reshaping the technology sector’s employment landscape, particularly for new graduates entering the workforce. Recent reports indicate that job openings for entry-level positions in tech have plummeted by over 50% compared to pre-pandemic levels, a trend that underscores broader disruptions in how companies hire and deploy talent. This contraction not only challenges the career prospects of recent university leavers but also signals potential long-term shifts in skill requirements and economic productivity across industries.

The Scale of the Decline in Entry-Level Tech Jobs

As of mid-2025, the tech industry is grappling with a stark reduction in opportunities for new graduates. Data from various industry analyses reveal that entry-level job postings have been halved since 2019, driven largely by the integration of AI tools that automate routine tasks traditionally assigned to junior staff. This isn’t merely a cyclical downturn; it’s a structural change where firms are leveraging generative AI to handle data analysis, coding, and administrative functions that once formed the bedrock of starter roles.

Consider the broader context: the unemployment rate among recent college graduates has surged, with some estimates placing it at around 12.4% in early 2025, significantly higher than the general population. In tech specifically, this figure is exacerbated by AI’s ability to replace human input in areas like software development and basic research. For instance, AI-powered code assistants and automated hiring systems have streamlined processes, reducing the need for large cohorts of inexperienced hires. This shift is evident in major tech hubs, where companies are prioritising experienced professionals who can oversee AI implementations rather than training newcomers.

Key Drivers Behind the Trend

Several factors are converging to fuel this contraction. First, the proliferation of AI technologies has enabled cost efficiencies that make entry-level positions redundant. Tools capable of generating reports, summarising research, and even creating presentations are now commonplace, allowing mid-level employees to absorb workloads that previously required teams of juniors. A report from the World Economic Forum, published in April 2025, highlights how AI is “reshaping the career ladder” by putting entry-level roles at risk while expanding global talent pools for specialised skills.

Second, economic pressures post-2023 tech layoffs have compounded the issue. Over 800,000 private-sector jobs were cut in the US alone by mid-2025, with AI cited as a contributing factor in more than 10,000 of those in the tech sector. Companies like Microsoft, IBM, and Google have publicly acknowledged using AI to automate routine tasks, leading to workforce reductions and a sharper focus on roles that demand advanced expertise in AI ethics, machine learning operations, or prompt engineering.

Third, there’s a mismatch between graduate skills and market demands. While universities continue to produce record numbers of computer science degrees, the job market in 2025 favours candidates with hands-on experience in AI and machine learning. Surveys indicate that 95% of organisations value practical experience over formal qualifications, with 70% of cloud engineering roles filled through internal training rather than external hires. This has left many new graduates, even those with strong academic credentials, facing prolonged job searches—some applying to thousands of positions without success.

Implications for the Broader Economy and Investors

This erosion of entry-level opportunities carries profound implications for economic growth and talent development. On one hand, it risks creating a “lost generation” of professionals, where delayed career starts could lead to skill atrophy and reduced innovation in the long term. Analyst forecasts suggest that without intervention, youth unemployment in tech could rise by an additional 15–20% by 2030, based on models from institutions like Nexford University, which predict AI will displace jobs but create new ones in emerging fields.

From an investor perspective, this trend illuminates opportunities in companies at the forefront of AI adoption. Firms investing heavily in automation technologies are likely to see margin improvements, with productivity gains estimated at 10x for roles enhanced by AI. However, there’s a countervailing risk: a talent shortage in specialised areas. Reports note that 68% of organisations are understaffed in AI and machine learning operations, potentially driving up salaries for experienced talent—a median of $262,000 in total compensation for entry-level AI engineers, compared to $215,000 for general tech roles.

Sentiment among investors, as gauged by credible sources like Fortune in August 2025, leans cautious. While AI-driven efficiencies boost short-term profitability, there’s growing concern over societal backlash and regulatory scrutiny. For example, the “AI job apocalypse” narrative, echoed in outlets like The New York Times in May 2025, has prompted calls for policies to support reskilling, which could influence tech valuations if governments impose hiring mandates or AI taxes.

Emerging Opportunities Amid the Disruption

Yet, it’s not all gloom. AI is simultaneously creating niches for new graduates adaptable to the change. Projections indicate a 21% increase in technical hiring for AI-related roles in 2025, rising to 23% in 2026. Fields like AI ethics, data governance, and human-AI collaboration are expanding, with global demand for AI talent expected to reach 97 million jobs by the end of 2025, far outstripping the current supply of under 10,000 experts.

• Reskilling Initiatives: Companies are ramping up internal programmes, with 70% of roles in high-demand areas filled via upskilling existing staff or targeted training for graduates.
• Premium Compensation: AI/ML engineers command a 20% pay premium, highlighting a bifurcated market where specialised skills yield high returns.
• Global Shifts: While entry-level jobs dwindle in traditional tech, opportunities in emerging markets and AI startups are growing, with startup hiring down only 11% compared to 25% in Big Tech.

Investor models, such as those from the World Economic Forum, forecast that while 75% of roles face automation risks, the remaining 25% could see efficiency gains that propel sector growth. This duality suggests a selective investment approach: favour firms with robust AI strategies that also invest in human capital development to mitigate talent gaps.

Looking Ahead: Strategies for Mitigation

To navigate this landscape, stakeholders must adapt. Educational institutions should integrate AI literacy into curricula, preparing graduates for a market where degrees alone no longer guarantee employment. Governments could incentivise apprenticeships or subsidies for AI training, addressing the projected gap between talent supply and demand.

For investors, the key is diversification. While tech giants benefit from AI efficiencies, smaller innovators in edtech and reskilling platforms may offer upside as they capitalise on the need for continuous learning. Analyst-led forecasts from sources like WebProNews in August 2025 predict a 20% drop in overall job postings but a surge in new roles, creating a net positive for adaptable economies.

In summary, the halving of tech job openings for new graduates marks a pivotal moment in the AI era. It challenges conventional career paths but opens doors to innovation and specialisation. As the sector evolves, those who embrace AI as an enhancer rather than a replacer will thrive, ensuring the next generation of talent isn’t reduced but redefined.

References

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