PwC’s 2025 Global Workforce Hopes & Fears survey finds that employees who use generative artificial intelligence (GenAI) daily report substantially greater labor-market benefits than those who use it rarely or not at all. The survey was conducted between July 7 and August 18, 2025, and covers responses from 49,843 workers across 48 countries and 28 sectors.
Key figures and comparisons
- 92% of daily GenAI users reported productivity gains, compared with 58% of rare users.
- 58% of daily users reported improved job security, versus 36% of rare users.
- 52% of daily users reported pay benefits, compared with 32% among rare users.
- 69% of daily GenAI users are optimistic about their role’s prospects over the next 12 months, versus 51% of rare users and 44% of non-users.
While 54% of respondents used some form of AI at work in the past year, daily GenAI use remains low at 14% (up slightly from 12% in 2024). Even fewer—6%—use agentic AI (AI agents) daily.
Uneven access to training and development
Although companies are investing more in upskilling, PwC’s survey highlights unequal access to those resources:
- Only 51% of non-managerial employees feel they have the tools needed for learning and development;
- The figure is 66% for managers and 72% for senior leaders.
Among daily AI users, 75% report access to learning and development opportunities, compared with 59% of rare users. This suggests that workers already using AI are more likely to receive further support and thus widen their labor-market advantage.
Workplace culture and psychological safety
Overall, 54% of respondents say their team treats mistakes as learning opportunities, but sectoral differences are large: 65% in technology versus 47% in transport and logistics.
Psychological safety is a clear concern: 57% do not feel safe experimenting with new ideas or approaches at work, and 66% say failures are not treated as opportunities to learn or grow. Only 54% trust their manager, and 55% say they can communicate openly with them. PwC notes that psychological safety is directly linked to performance and innovation, making it foundational for organizational renewal.
Job satisfaction, overload and financial stress
- 70% of respondents feel satisfied with their job at least one day a week.
- 35% feel overloaded at least once a week; among Gen Z workers the figure is 42%.
- 55% of the global workforce report financial difficulties, up from 52% in 2024.
In the past year 43% received a pay rise and 17% were promoted. Intentions to seek pay rises and promotions have fallen—from 43% to 37% for pay rises, and from 35% to 32% for promotions.
Leadership alignment and engagement
Workers who strongly align with leadership goals are 78% more motivated than those who feel the least alignment. Understanding of organizational goals is not universal—64% overall say they understand their organization’s objectives, with lower rates among non-managers and Gen Z.
Hungary compared with the global average
PwC’s data show that AI usage in Hungary lags the global average (38% in Hungary vs. 54% globally). In Hungary 54% of respondents feel they lack the right tools to learn new skills, and 49% say they lack managerial support. PwC warns that such gaps in learning and leadership support slow technology adoption and can undermine long-term competitiveness. The report recommends shifting training strategies toward practical, on-the-job learning that gives workers tangible support for developing skills and applying AI tools effectively.
Conclusions
PwC’s 2025 survey indicates that daily use of generative AI confers clear advantages in productivity, pay and job security, but those advantages are amplified by unequal access to training and managerial support. Strengthening access to practical learning, extending leadership backing, and improving psychological safety are presented as essential steps for organizations that want to convert AI investments into sustained performance and innovation.
Methodology
PwC surveyed 49,843 workers between July 7 and August 18, 2025, across 48 countries and 28 sectors. The sample proportions reflect the gender and age distributions of working populations in the participating countries, making the findings broadly representative.
