Key Developments

New research from Stanford’s SIEPR Economic Summit reveals that AI’s impact on employment is no longer theoretical—it’s happening now. Entry-level software developer hiring for workers aged 22-26 has dropped 20%, while call center hiring is down 15%. This data represents actual market conditions, not future projections.

A separate Anthropic study by Brynjolfsson et al. found employment in AI-exposed occupations has fallen 6-16% among workers aged 22-25. Paradoxically, the most AI-exposed workers tend to be higher-skilled professionals—lawyers, financial analysts, and software developers—rather than warehouse workers, and they’re 16 percentage points more likely to be female with significantly higher average earnings.

Industry Context

The employment impact reflects a broader shift in AI deployment strategy. As one industry analyst noted, “2026 will be the year of agents as software expands from making humans more productive to automating work itself.” This transition is already visible in corporate actions—Block co-founder Jack Dorsey announced a 40% staff reduction, citing AI capabilities.

However, MIT Sloan researchers suggest this is just the beginning: “As frontier LLMs get more capable, their accuracy will continue to improve, while human accuracy will likely be unchanged. So it is quite possible that LLM accuracy surpasses human accuracy in 2026 for many enterprise tasks.”

Practical Implications

For European tech companies and workers, these trends signal several immediate concerns. New graduates entering AI-exposed fields face a significantly more challenging job market, particularly in software development and customer service roles. Companies should prepare for potential talent shortages in mid-level positions as entry-level hiring contracts.

The gender and education demographics of affected workers—predominantly female, highly educated professionals—suggests Ireland’s growing fintech and software sectors could see disproportionate impacts on their most skilled workforce segments.

Open Questions

Critically, the Peterson Institute for International Economics argues that “claims about harmful impacts on particular groups of workers are premature,” noting that evidence remains inconclusive. Citadel Securities researchers contend that AI adoption is still “slow and expensive” and would need to accelerate significantly to meaningfully displace workers at scale.

The key uncertainty is whether current deployment patterns will accelerate or whether implementation challenges will slow AI’s labour market impact, giving workers and policymakers more time to adapt.

Source: Stanford SIEPR Economic Summit