Artificial intelligence is reshaping the global workforce at an unprecedented speed—but the emotional response to this change varies widely across demographics.
A September 23 report from Deutsche Bank highlights a striking paradox: younger employees, most familiar with digital technology, are the most anxious about AI potentially replacing their jobs, while older workers, often considered less tech-savvy, appear unusually calm.
Based on a survey of 10,000 employees across major economies in the U.S. and Europe, the report exposes generational, geographic, and trust gaps emerging in the AI era.
1. Young Workers Fear for Their Jobs: The Generational AI Gap
The survey reveals significant age-based differences in AI-induced job anxiety.
According to dbDataInsights’ research conducted from June to August, 24% of employees aged 18–34 report being “very concerned” (rating 8–10/10) about the possibility of losing their job to AI within the next two years.
In contrast, only 10% of workers aged 55+ express the same level of worry.
This anxiety is supported by recent academic findings:
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Stanford University reports that employment rates for young graduates (22–25) in AI-affected roles like software engineering and customer service have dropped 6% compared to late 2022 peaks.
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Harvard University’s analysis of U.S. resumes and hiring data indicates that junior positions are declining sharply in AI-adopting companies, while senior positions are seeing growth.
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U.S. Census Bureau data shows that recent college graduates have an unemployment rate of 4.8%, surpassing the overall workforce rate of 4.0%.
Together, these figures depict a harsh reality: AI’s impact begins at the bottom of the job pyramid, hitting entry-level positions first.
2. Geography Matters: AI Adoption and Anxiety Diverge Globally
Age isn’t the only factor—location also shapes AI perception and adoption.
The report finds that Americans are generally more anxious about AI job displacement than Europeans. Within the next two years, 21% of U.S. respondents report being very worried, compared with 17% in Europe. This may reflect faster AI adoption and higher social awareness in the U.S. market.
Practical adoption also varies:
| Scenario | U.S. | U.K. | Germany | France & Italy | Spain |
|---|---|---|---|---|---|
| Workplace AI adoption | 56% | 52% | 41% | 41% avg | – |
| Home AI adoption | 59% | – | – | – | 68% |
These gaps suggest that while individual AI experimentation is happening worldwide, corporate integration, governance, and policy support are progressing faster in the U.S. and parts of Europe (like the U.K.), which could translate into future productivity advantages.
3. The AI Skills Gap: Employees Are Underprepared
Employees recognize the urgency of upskilling for AI, but corporate and societal preparation lags far behind.
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54% of U.S. employees and 52% of European employees want AI-related training at work.
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Yet only about one-third of U.S. workers and one-quarter of European workers have received any form of AI training.
In the absence of formal training, many employees are taking matters into their own hands:
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~33% of Americans and >25% of Europeans are learning AI through online videos.
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~25% read articles and tutorials.
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However, half of respondents have not undertaken any self-education in the past 3–6 months.
4. Trust Deficit: The Final Barrier to Large-Scale AI Adoption
While AI is gaining traction in areas like personal assistants (61% adoption in the U.S., 50% in Europe) and content creation, trust remains a critical barrier for deeper adoption in high-stakes domains.
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High-risk domains: 40% of respondents do not trust AI to manage personal finances, and 37% do not trust AI for medical diagnoses.
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Core functionality: 29% doubt AI decision-making fairness, and 29% question the accuracy of AI-provided information.
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Common applications: Even customer service, one of AI’s most established uses, faces 27% distrust among users.
The report notes that despite improvements in AI accuracy, LLMs’ probabilistic nature, hallucinations, and bias continue to erode trust. Until reliable trust frameworks are established, AI commercialization in industries like finance and healthcare will remain challenging.
Key Takeaways for Global Employers and Employees
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Generational divide: Younger workers are the most vulnerable and anxious about AI, particularly in entry-level roles.
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Geographic differences: U.S. and select European markets adopt AI faster, potentially creating productivity gaps.
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Skills gap: Employees need urgent AI training, but corporate provision is insufficient.
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Trust matters: Building confidence in AI is crucial before expanding into high-stakes areas.
For organizations, the lesson is clear: strategic AI adoption requires addressing both skills and trust, while employees should actively seek AI upskilling opportunities to future-proof their careers.
