PwC: Global Workforce Hopes and Fears Survey 2026
Source: PwC, Global Workforce Hopes and Fears Survey 2026: Unlock the workforce advantage, 29 September 2026
Key takeaways
The workforce is splitting into distinct groups with very different experiences of AI and change. PwC identifies four cohorts: front-runners, the engine room, AI insurgents and the indispensables. The 56% engine room remains central to organisational delivery but has less access to AI, learning and opportunity.
AI adoption is already widespread. 64% of workers used AI at work during the past year, up ten percentage points year on year. Daily GenAI use increased from 14% to 22%.
AI adoption is highly uneven. 51% of front-runners use GenAI daily compared with just 11% of the core workforce, and the majority of the engine room say they have never used AI.
The workforce divide is also a trust divide. Trust in management fell seven percentage points year on year. Only 33% of engine room workers trust top management compared with 75% of front-runners.
Adoption alone does not produce AI value. PwC finds that 20% of companies capture 74% of AI driven returns. Leading organisations are more likely to redesign workflows, provide role based learning and create incentives for experimentation.
The most AI fit companies achieve 7.2 times higher AI driven performance than the rest. The differentiator is not simply access to tools, but how organisations redesign roles, workflows, incentives and human AI collaboration around them.
Learning is becoming part of the job, but access to development is deteriorating. 88% of workers applied new skills during the past year and 64% had to learn new tools or technology, yet positive ratings of learning and development access fell from 59% to 51%.
The learning gap is particularly wide across workforce cohorts. Fewer than 40% of engine room workers say they have access to learning and development resources compared with almost 80% of front-runners.
Managers are struggling with the same pace of change they are expected to help employees navigate. 31% of senior executives and 24% of managers say they find change difficult to manage.
PwC’s recommendation is reinvention rather than optimisation. Organisations need to redesign work, workforce systems and management practices so that capability and confidence can keep pace with technology and business model change.
Executive summary
PwC’s Global Workforce Hopes and Fears Survey 2026 examines how employees are experiencing AI, organisational change, skills development, financial pressure and leadership. The research draws on a global sample of nearly 50,000 workers and reveals a workforce increasingly divided by access to AI, development opportunities and confidence about the future.
PwC identifies four distinct workforce cohorts. At one end are front-runners, representing 14% of workers. They combine strong AI advantage with skills that are in high demand and are generally optimistic, adaptable and confident about their prospects. At the other end is the engine room, representing 56% of the workforce. This group remains essential to everyday delivery but has less access to meaningful AI use, learning and career opportunity and reports significantly lower trust in leadership.
Between the two sit AI insurgents, who show high AI usage and ambition, and the indispensables, whose specialist expertise remains difficult to replace but who have relatively limited hands-on AI experience.
The workforce divide is emerging at the same time as AI adoption accelerates. 64% of workers used AI at work during the past year and daily GenAI use increased from 14% to 22%. But adoption remains highly uneven: more than half of front-runners use GenAI daily compared with just 11% of the core workforce.
PwC argues that increasing adoption alone will not solve the problem. Its AI Performance Study finds that just 20% of companies capture 74% of AI driven returns. The leaders are much more likely to redesign workflows, provide role based learning and change incentives so that employees are encouraged to experiment with AI rather than simply use another tool inside the existing operating model.
The workforce is also dealing with broader organisational change. One in five workers says change is difficult to manage, while 27% identify fatigue and burnout as an important constraint on productivity. Managers and senior leaders themselves report significant difficulty coping with the pace of change.
At the same time, workers are learning rapidly. 88% say they applied new skills over the previous year and 64% had to learn new technologies or tools. Yet access to learning and development has weakened, with positive ratings falling from 59% to 51%.
PwC’s conclusion is that workforce transformation has become a business and economic imperative. The return on AI investment increasingly depends on whether organisations can redesign work, build capability, strengthen trust and give both workers and managers enough capacity and confidence to execute continuous change.
Key stats and quotable claims
64% of workers report using AI at work during the past 12 months.
AI usage increased by 10 percentage points year on year.
Daily GenAI use increased from 14% to 22%.
59% expect their use of AI tools at work to increase during the next 12 months.
51% of front-runners use GenAI daily.
Only 11% of the core workforce use GenAI daily.
14% of workers fall into PwC’s front-runner cohort.
56% make up the engine room.
75% of front-runners trust top management.
82% of front-runners trust their immediate manager.
Only 33% of engine room workers trust top management.
Only 40% trust their immediate manager.
Overall trust in management fell seven percentage points year on year.
85% of front-runners feel very confident about their job security.
29% of front-runners say they are very or extremely likely to change employer within the next year.
Only 34% of workers can pay their bills and still have money left over, down eight percentage points year on year.
62% say the cost of living had a moderate or major impact on them at work during the previous year.
Daily GenAI users report higher confidence in job security, with 68% feeling very or extremely confident.
Workers with AI skills command a 62% wage premium, according to PwC’s AI Jobs Barometer.
34% of daily GenAI users say AI helps them with some of the most difficult and complex parts of their job.
31% of daily AI users identify accuracy or quality concerns as their biggest barrier to AI use.
Just 20% of companies capture 74% of AI driven returns.
AI leaders are 1.9 times as likely to use incentives encouraging employees to experiment with AI.
They are 1.7 times as likely to provide ongoing role based AI learning.
They are 2.2 times as likely to redesign workflows around AI rather than simply add AI tools.
The most AI fit organisations achieve 7.2 times higher AI driven performance than the rest.
34% of workers affected by change say they experienced more change than in previous years.
20% say they find change difficult to manage.
18% do not understand the reasons for the change.
27% cite fatigue and burnout as a key limit on productivity.
57% identify economic volatility as a major threat to job security compared with 44% who cite AI taking on more tasks.
88% applied new skills in their job during the previous year.
64% had to learn new tools or technologies.
Only 51% rate their access to learning and development resources positively, down from 59%.
Fewer than 40% of engine room workers say they have access to development resources compared with almost 80% of front-runners.
31% of senior executives and 24% of managers say they find change difficult to manage.
Overall summary
PwC’s central finding is that there is no longer one common workforce experience.
A relatively small group of workers is moving quickly with AI, developing skills, building confidence and becoming more valuable in the labour market. These front-runners are optimistic about change, trust their leaders and expect continued career progression. Many are also willing to leave if their organisations fail to keep pace with their expectations.
The majority of workers experience the transition differently. PwC’s engine room continues to serve customers and operate the business, but these employees have much less exposure to AI, learning and innovation. They report lower confidence about job security and weaker trust in management while also facing greater financial pressure.
The danger is that AI adoption reinforces rather than closes this divide. Employees already benefiting from AI gain greater productivity, stronger skills and potentially higher labour market value. Workers with less access can fall further behind unless organisations deliberately create opportunities for them to learn and apply new technology.
PwC therefore argues that organisations need to stop treating their workforce as a single group. Different cohorts require different combinations of learning, rewards, career opportunities, trust building and access to AI.
The same principle applies to AI itself. More adoption does not automatically produce more value. The organisations generating the strongest AI returns combine adoption with workflow redesign, role based learning, incentives for experimentation and deliberate changes to how work gets done.
Workforce transformation and AI transformation therefore become part of the same business problem. Technology investment increasingly pays off when organisations redesign the work around it and give employees enough capability, capacity and confidence to operate successfully in the new model.
Deep dive
The dynamic: a workforce moving at different speeds
PwC’s Global Workforce Hopes and Fears Survey 2026 reveals a stark divergence in a fast-changing workplace. On one side, an optimistic minority group of AI-enabled front-runners who are motivated, adaptive, and ready to advance—within or beyond their organisations. On the other, an anxious majority group of core workers who worry about their jobs and finances, feel shut out of growth and learning, and distrust their leaders.
This diverging workforce presents employers with a complicated challenge. Front-runner workers are proving to be more agile and adaptive than their organisations, many of which continue to reward caution over innovation. Nearly a third of these confident, can-do workers say they are very likely to change employers in the next 12 months.
The core workforce, though—the engine room of delivery—feels unsettled by change, left behind in the AI race, unsupported to upskill, and poorly led by their managers. They are experiencing a crisis of trust. Across PwC’s global sample of nearly 50,000 workers, trust in management has fallen by seven percentage points year-on-year.
The research suggests that, even as organisations invest heavily into AI, leaders aren’t doing enough to help workers and managers navigate change, build new skills, and translate technology into innovation and value. PwC’s Global CEO Survey finds that most CEOs say their companies aren’t yet seeing a financial return from investments in AI.
Injecting AI into legacy operating models isn’t enough. To unlock sustained advantage, organisations need to rewire work. That makes workforce transformation a business and economic imperative. The return on technology investment increasingly depends on whether organisations can redesign work, build capabilities, and translate new technology into productivity, innovation, and growth.
PwC therefore identifies three actions for leaders: make tough choices to engage a divided workforce, rewire work to translate AI into value, and empower workers and managers to embrace change and build new skills.
Four workforce cohorts emerge
PwC assessed workers’ “AI advantage”—the extent to which AI has boosted the quality of their work, their creativity and skills, and their value to their employer. The research also assessed respondents’ perception of the market demand for their skills and experience and how difficult it would be for employers to develop or acquire workers with those capabilities.
This analysis sorts workers into four distinct cohorts. Front-runners, representing 14% of the workforce, combine strong AI advantage and high-demand capabilities. The engine room, representing 56%, brings dependable delivery but feels increasingly squeezed. Between the two sit AI insurgents, who bring ambition and energy, and the indispensables, who bring valued, field-specific expertise but relatively low engagement with AI.
The four cohort model matters because exposure to AI is only one dimension of the workforce transition. The value of a person’s skills, their confidence, ability to adapt, access to learning and relationship with the organisation also shape how they experience change.
Front-runners are embracing change
Front-runners are embracing change with enthusiasm. Three-quarters of this cohort say recent changes make them optimistic about their organisation’s future, and 85% say they are ready to adapt to new ways of working. They are highly motivated. Nine in ten say they look forward to work and are willing to go above and beyond what’s required in their role.
Unlike the average worker, front-runners report a high degree of trust in their leaders—75% trust top management, and 82% trust their immediate manager.
Front-runners are nearly twice as likely as the global average to work in an organisation that rewards effective AI use. They over-index on being rewarded for challenging existing ways of working and learning new skills. They are more likely to work in organisations that reward innovation rather than minimising risk or avoiding mistakes.
This gives front-runners the confidence to reach higher. Two-thirds say they are very likely to ask for a promotion or pay rise over the next 12 months. 85% feel very confident about their job security. At the same time, 29% say they are very or extremely likely to change employer in the next year.
This creates an important retention problem. The workers benefiting most from AI and change may also have the strongest outside options if their organisation cannot provide sufficient growth, autonomy or opportunity.
The engine room is experiencing a very different transition
The contrast with the larger engine room cohort is telling. This majority of workers is key to organisational delivery, but has limited access to learning, innovation and meaningful AI use.
They are the least likely of the four cohorts to say they feel ready to adapt, while only half feel confident about their job security. Their experience contributes to a striking overall finding: twice as many workers believe their bargaining power has fallen over the past three years as believe it has increased.
Engine room workers are also stretched financially. Only a third believe they are fairly paid, and even fewer say they can pay their bills and have something left over at the end of the month.
Across the wider workforce, only 34% can now pay their bills and have money left over, an eight percentage point decline from the previous year. Almost two-thirds of workers, 62%, say the cost of living has had a moderate or major impact on them at work over the past year.
Despite these pressures, most engine room employees remain motivated. Two-thirds say they take pride in their work and are willing to go above and beyond. But they feel let down by leadership.
Only 33% trust top management and only 40% trust their immediate manager. These low scores from the majority of the workforce are pulling down overall trust, with less than half of the global workforce now trusting top management.
The organisation therefore faces a difficult combination: the employees most essential to current delivery can remain motivated while simultaneously losing trust in the people leading the transformation.
AI insurgents and indispensables
Not all workers fall neatly into the front-runner or engine room groups.
PwC identifies AI insurgents as tomorrow’s talent. They report the highest weekly AI usage of any cohort and combine ambition with energy.
The indispensables have skills that are difficult to replace and say they are ready to adapt to new ways of working, but have relatively little hands-on AI experience.
Trust among both groups sits somewhere between the high-trust front-runners and low-trust engine room. PwC argues that leadership decisions will influence whether these workers move towards greater confidence and growth or greater fear and disengagement.
The middle cohorts are therefore strategically important. They represent groups where targeted access, development and leadership can materially change the trajectory of workforce readiness.
Engaging a divided workforce
Leaders will have to make some tough choices. These could include rewarding experimentation rather than just expecting workers to avoid mistakes, changing performance measures that reinforce old ways of working, and giving managers more licence to redesign work. Leaders will also need to protect time for learning rather than adding it on top of daily tasks.
Organisations must understand the drivers of each worker cohort rather than applying one employee value proposition or development model to the entire workforce. Preference analytics can provide clearer insight into what workers value and help organisations redesign employee experiences around roles, skills development, mechanisms for building trust, performance metrics and rewards.
To engage and excite front-runner talent, employers can put them at the centre of redesigning AI-enabled work and invite them to help shape the rewired organisation, giving them autonomy, opportunities for innovation and clear routes to progression.
For the squeezed majority in the engine room, organisations need to make learning and reskilling available without increasing workloads. The principle is important because asking employees to develop new capability while maintaining exactly the same workload can turn learning itself into another source of strain.
Other cohorts require different interventions. AI insurgents may need recognition and opportunities to apply their emerging capabilities, while indispensables may benefit from greater exposure to AI so that their valuable existing expertise can be combined with new tools.
Capturing ROI from AI
AI adoption is on the rise. Nearly two in three workers, 64%, report using AI at work in the past 12 months, a ten-point increase year-on-year. The proportion of the workforce using GenAI daily has increased from 14% to 22% in the same timeframe.
The trend is likely to continue. 59% of workers expect their use of AI tools in their job to increase over the next 12 months, and workers already using AI frequently report feeling energised and empowered by the technology.
But again, adoption is uneven.
Among the front-runner cohort, more than half use GenAI daily, at 51%, compared with just 11% of the core workforce. In fact, the majority of the core workforce say they have never used AI.
These disparities are deepening the workforce divide because AI adoption is associated with a more positive employee experience. Daily GenAI users report significantly higher confidence in their job security than other workers, with 68% feeling very or extremely confident.
PwC’s AI Jobs Barometer also finds that workers with AI skills now command a 62% wage premium, up from 57% in 2025.
The implication is that uneven adoption may compound over time. Workers receiving greater exposure to AI can build more experience, become more productive and increase the market value of their capabilities, while people without equivalent access risk falling progressively further behind.
AI is moving into more difficult parts of the job
Daily users of GenAI are increasingly applying the technology to more sophisticated work.
Of daily users, 34% say AI helps them perform some of the most complex and difficult parts of their job better, compared with 29% of AI users overall.
Higher adoption does not mean blind trust. The more workers understand AI, the more discerning they become about where and how to use it.
Daily GenAI users are familiar with the current pitfalls and fallibilities of AI and are correspondingly alert to its limits. Nearly a third, 31%, say their biggest barrier to AI use is concern about accuracy or quality, six percentage points above the global average.
Greater AI fluency therefore appears to create more critical usage rather than indiscriminate trust. Experience allows workers to understand where AI is valuable and where human judgement or verification remains necessary.
Rewire work to translate AI into value
Organisations need to translate workers’ enthusiastic embrace of AI into value not just by driving adoption, but by rewiring work itself.
PwC’s AI Performance Study finds that just 20% of companies capture 74% of AI-driven returns.
These leading firms are 1.9 times as likely to create performance incentives that encourage employees to experiment with and use AI in their work, 1.7 times as likely to provide ongoing, role-based AI learning, and 2.2 times as likely to redesign workflows to incorporate AI rather than simply adding AI tools.
The prize is significant. The most AI-fit companies achieve 7.2 times higher AI-driven performance than all others.
The energy and empowerment reported by AI-fluent workers is therefore an opportunity, but it needs an operating model around it. Organisations that drive relevant adoption alongside a culture of innovation and experimentation stand to multiply the benefit.
AI adoption creates the greatest value not when organisations simply deploy more tools, agents or pilots, but when they redesign work, roles and operating models around uniquely human contribution and trusted human AI collaboration.
Among cohorts that lag behind in AI use, organisations can support greater adoption and impact where roles allow for it. Established employees with valuable domain expertise may be able to combine that expertise with AI to create new sources of value.
Companies that treat AI as a series of isolated tools may find it considerably harder to turn usage and cost into sustainable value.
Reinvention, not optimisation
As organisations navigate major change, workers and managers are often struggling to keep up.
Among workers affected by change, 34% strongly or moderately agree that they experienced more change in the last year than in previous years. One in five workers say they find it difficult to manage change, and 18% do not understand the reasons for the change.
At the same time, fatigue and burnout remain a significant workforce challenge, cited by 27% of workers as a key limit to productivity.
When workers consider threats to job security, economic volatility currently worries them more than AI. 57% cite economic volatility compared with 44% who cite AI taking on more tasks. Gen Z reports greater anxiety across these measures than other generations.
The workforce transformation problem therefore extends beyond whether employees accept AI. People are processing technological change alongside economic uncertainty, workload pressure and repeated organisational change.
Front-runners are moving quickly, but even they feel the strain
A cohort lens reveals a more complicated picture.
Front-runners are experiencing change at a greater pace than other workers. Two-thirds of these AI-enabled, high-demand workers say they have experienced faster change than in previous years. Most say they have applied new skills, learnt new tools, increased their workload, and seen their daily responsibilities and team structures change.
This group remains motivated and optimistic, but almost half say they find it difficult to manage change.
That is an important warning. Even workers benefiting most from AI can reach the limits of their capacity to absorb continuous change.
High readiness should therefore not be interpreted as unlimited capacity.
The core workforce risks being left behind
The engine room cohort has experienced far less change.
Only a quarter of these workers have experienced increased change, learnt new skills or applied new tools during the previous year.
They may therefore see change happening elsewhere in the organisation without feeling that they are participating in it.
Only 20% say recent changes make them optimistic about the organisation’s future.
This creates a different transformation risk. Front-runners can become overwhelmed by the speed of change, while the core workforce can become disengaged because the change appears to be passing them by.
Organisations need to manage both problems simultaneously.
Learning is now part of the job
Learning is increasingly embedded in everyday work.
Almost all workers, 88%, say they have applied new skills in their job over the previous year, with 40% saying they did so to a large or very large extent.
Nearly two-thirds of workers, 64%, had to learn new tools and technology for their role to at least a moderate extent. 36% say this occurred to a large or very large extent.
AI-enabled workers have upskilled fastest. PwC’s AI Jobs Barometer finds that the skills employers seek in occupations most exposed to AI are changing more than twice as quickly as those in the least exposed occupations.
The workforce is therefore already adapting. The larger problem is whether organisations are providing the infrastructure and opportunity employees need to keep doing so.
Access to development is falling
Despite workers applying new skills at a rapid pace, they rate their access to learning and development resources at only 51%, down from 59% the previous year.
Only 49% say they understand the future skills required, while 61% believe they personally have the capacity to develop new skills.
The cohort divide is again significant. Fewer than 40% of engine room workers say they have access to learning and development resources compared with nearly 80% of front-runners.
This suggests that willingness and capability to learn may be stronger than the organisational systems supporting that learning.
If the people already ahead continue receiving significantly greater access to development than the core workforce, the capability gap can widen further.
Managers are stretched as well
Leaders and managers, who must guide the workforce through change and rebuild trust and confidence, are finding their own roles difficult.
31% of senior executives and 24% of managers say they find change difficult to manage.
Managers also face a particular set of pressures as they try to engage teams and prevent fragmentation. Confidence in their own job security is down six percentage points year on year even while there has been relatively little change among more junior roles.
This matters because managers sit at the interface between enterprise transformation and employee experience.
They are expected to explain the change, support development, redesign work, maintain performance and sustain trust while simultaneously adapting their own roles.
A transformation model that assumes managers have unlimited capacity to absorb and translate change therefore risks creating another bottleneck.
Reinvention requires workforce capacity and confidence
As the business landscape shifts quickly, PwC argues that staying competitive requires reinvention rather than just optimisation.
Organisations must rethink how they create, capture and deliver value by developing new revenue streams, redefining customer experiences and creating new digital products and services.
But a reinvention strategy is only as executable as the workforce behind it.
As organisations pursue new sources of growth and develop AI-enabled business models, workforce capacity, capabilities and confidence can become either an accelerator of strategy or a constraint on it.
Managers need to navigate complex change for themselves as well as for the people on their teams. Helping managers build resilience can strengthen their ability to overcome obstacles, adapt and lead more effectively.
Reinvention succeeds when organisations move at pace while ensuring the workforce has enough capacity and confidence to match that pace. Workers and managers need to understand how change affects their roles, have access to the skills required to adapt and trust leadership to navigate uncertainty.
The workforce advantage
The reality of a diverging workforce heightens the challenge for leaders.
Most front-runner workers are using AI every day, learning new skills and backing themselves to grow, lead and prosper. If their organisations do not keep pace with them, they may move to more innovative or rewarding workplaces.
At the same time, leaders need to address the deep mistrust and strain experienced by the majority of the workforce who continue to serve customers and run operations.
These workers need space to learn, meaningful support from managers and a credible belief that they have a place in the organisation’s future.
The workforce advantage therefore does not come from concentrating investment exclusively on the people already ahead.
It comes from creating an organisation capable of moving the broader workforce with the technology.
Conclusion
PwC’s research shows that workforce transformation is becoming inseparable from AI transformation.
The technology is already spreading quickly. Nearly two-thirds of workers use AI and daily GenAI adoption is rising rapidly. But access and benefit are distributed very unevenly.
A small cohort is moving quickly, gaining confidence, skills and market value. The much larger engine room continues to deliver the business but has less access to AI, learning and opportunity and considerably less trust in leadership.
Closing that gap requires more than expanding access to technology.
Organisations need to redesign workflows, rethink incentives, make role based learning available inside the flow of work, give managers enough capacity to lead the transition and make different workforce interventions for different employee cohorts.
The strongest AI performers provide evidence for that approach. They do not simply deploy more tools. They are more likely to redesign the work around the technology.
The result is a broader definition of workforce advantage: an organisation in which technology, skills, roles, management and employee confidence can change together rather than at different speeds.
Key takeaways
AI adoption has already reached the majority of the workforce, but the benefits remain highly uneven. The challenge is shifting from getting employees to use AI towards ensuring that the broader workforce can participate in the value it creates.
The 56% engine room deserves particular attention because this group remains fundamental to everyday delivery while reporting the weakest access to learning, lower AI usage and far lower trust in leadership.
The front-runners present a different challenge. They are optimistic, AI enabled and increasingly valuable, but they are also more willing to leave. Retaining them requires autonomy, continued development and meaningful involvement in redesigning future work.
Learning needs to become part of work rather than an additional burden placed on top of existing workloads. Employees are already developing skills quickly, but organisational access to development is moving in the opposite direction.
Managers need support as much as employees. They are being asked to translate large scale change into everyday work while many are struggling with the pace themselves.
Most importantly, PwC’s AI performance evidence suggests that workflow redesign, role based learning and incentives for experimentation matter more than adoption alone.
The workforce advantage therefore comes from the organisation’s ability to rewire work, spread capability beyond a small group of AI front-runners and give people enough confidence, trust and opportunity to move with the transformation.
