Executives prioritising AI-driven headcount reductions are almost half as likely to invest in AI upskilling, raising questions over whether businesses risk cutting workforce capacity before building the capability needed to deliver AI productivity gains.
Executives turning to artificial intelligence to reduce headcount are investing significantly less in preparing their remaining workforce to use the technology effectively, new research reveals. Among the 27% of C-suite executives who identify cost savings through headcount reduction as a top AI investment goal, just 18% also prioritise AI upskilling, according to new research from Businessolver.
That compares with 35% of executives who do not prioritise AI-driven headcount reduction. The gap raises an important question for employers investing heavily in AI. Can businesses achieve sustainable productivity gains by reducing workforce capacity without investing equally in the capabilities people need to make AI work?
The research, involving 300 C-suite leaders and 1,000 employees, forms part of Businessolver’s 11th annual State of Workplace Empathy study. “AI does not create value on its own. People create value when they’re enabled with the right set of skills and confidence,” said Sony SungChu, Chief AI Officer at Businessolver. “If leaders reduce capacity without building capability, they could risk undermining the very productivity gains they’re chasing.”
AI COST-CUTTERS INVEST LESS IN WORKFORCE CAPABILITY
The upskilling gap forms part of a broader difference in how executives prioritising headcount reductions are investing in AI. Alongside the 18% versus 35% divide in AI upskilling, executives focused on reducing headcount are also less likely to prioritise predictive analytics – 21% compared with 44% among other executives.
According to Businessolver, they also place less emphasis on investments designed to save employees time, improve productivity and reduce administrative work. The findings suggest two different approaches to AI investment may be emerging: one focused primarily on reducing workforce costs, and another focused more heavily on increasing workforce capability.
That distinction matters because organisations across the world are already grappling with whether their people, jobs and skills are ready for AI. As recently reported, businesses may still be underestimating the people challenges of AI.
That global research found just 14% of CHROs strongly agreed their organisation’s learning and development capabilities were AI-ready, compared with 36% across the wider C-suite. Only 13% of CHROs strongly agreed job designs were AI-ready, versus 28% of executives overall. Together, the findings point towards a growing tension: businesses are investing in AI faster than some are preparing their people to work alongside it.
HALF OF EMPLOYEES LEFT TO FIGURE OUT AI THEMSELVES
Businessolver’s findings also expose a substantial gap between how executives think employees feel about AI and what workers themselves report. Some nine in 10 C-suite executives believe employees are excited about AI. Yet among employees:
- 39% worry about their future at their organisation
- 31% fear they are falling behind in their ability to use AI
- 49% say they have been left to figure out AI on their own
That last finding becomes particularly significant when considered alongside Businessolver’s earlier research. The company’s August AI Special Report found employees who received adequate employer-sponsored AI training reported substantially stronger outcomes than those receiving limited training.
Some 78% of adequately trained employees said AI was accelerating their career progression, compared with 51% of those receiving limited training. Similarly, 80% felt confident keeping up with AI trends, compared with 57%, while 73% said AI enabled them to do higher-value work, versus 50%. These are self-reported associations rather than evidence that training alone caused the stronger outcomes. Nevertheless, the findings reinforce the potential value of workforce investment as organisations introduce AI.
AI SKILLS ARE BECOMING MORE IMPORTANT
The apparent underinvestment in upskilling comes as employers increasingly value AI capability. Recent UK research found that almost two-thirds of employers say AI has changed what they look for when hiring. Some 36% cited AI skills as an attribute they now value in candidates, placing AI capability ahead of previous work experience at 31%.
Yet the same study revealed that 23% of workers did not believe their AI skills were sufficient to compete in an increasingly AI-driven jobs market. That creates a potential contradiction for workers. Employers increasingly expect people to possess AI skills, while Businessolver’s findings suggest almost half of employees feel they are largely being left to develop those capabilities themselves.
CIOs & CFOs SEE AI RISK DIFFERENTLY
Businessolver’s findings also reveal significant differences within the C-suite itself. Some 88% of CIOs and CTOs worry technology will advance faster than their organisation’s internal systems or workforce skills can keep pace. Among CFOs, that falls to 63% – a 25 percentage-point gap.
The difference is notable because these executives approach AI transformation from different vantage points. Technology leaders are often closest to implementation, infrastructure, systems integration and technical capability, while finance leaders play a central role in investment, costs and expected returns.
The findings don’t establish why their assessments differ. But they highlight the importance of organisations bringing technology, finance, HR and operational leadership together when making decisions about AI investment and workforce redesign. Otherwise, organisations risk making technology, workforce and financial decisions in isolation when all three increasingly depend on one another.
GROWING COMPANIES ARE ALSO CUTTING JOBS
Perhaps surprisingly, workforce reductions are not confined to organisations experiencing poor financial performance. Businessolver found that C-suite executives reporting significant financial growth during the previous year also reported more than twice the level of layoffs – 23% versus 11%.
At the same time, those organisations reported more recruitment – 37% versus 29% – and lower benefits investment, at 48% versus 61%. Businessolver interprets this combination of greater layoffs and greater recruitment as a sign of targeted workforce redesign rather than straightforward downsizing.
The survey itself does not establish why individual organisations cut and recruit workers simultaneously, so that interpretation should be treated cautiously. Nevertheless, the findings highlight an important feature of the current AI-driven workforce transition: job losses and recruitment can happen at the same time as businesses change which capabilities they need and where they deploy people.
WHAT HAPPENS TO THE FIRST RUNG OF THE CAREER LADDER?
That workforce redesign also raises longer-term questions about how organisations develop future talent. AI can increasingly perform some of the routine administrative and cognitive tasks traditionally assigned to junior employees.
Previous research found 62% of workers believe AI is already reducing entry-level hiring. That matters because entry-level jobs do more than provide immediate labour. They allow people to learn how organisations operate, develop professional judgement, build relationships, solve problems and acquire the experience needed to progress into more senior positions.
As Fair Play Talks has previously highlighted, removing too many junior opportunities could deliver short-term savings while creating future shortages of experienced talent. Businesses therefore need to consider not only which tasks AI can perform today, but how people will acquire the expertise organisations will need tomorrow.
THREE IN 10 AI JOB-CUTTERS SAY EMPATHY GETS IN THE WAY
One of Businessolver’s most provocative findings concerns attitudes towards workplace empathy. Among C-suite executives prioritising AI-driven headcount reduction, 30% say organisational empathy “gets in the way” of their personal business goals. That compares with 19% of other executives.
The finding doesn’t mean most executives pursuing headcount reductions oppose empathy. Seven in 10 in that group did not give that response. But the difference raises questions about how some leaders perceive the relationship between employee considerations and commercial decision-making during AI transformation.
Jon Shanahan, President and CEO of Businessolver, argues that difficult workforce decisions make empathy more important rather than less. “AI will change jobs and economic pressure will force hard decisions,” said Shanahan. “These are challenges but also opportunities for companies to demonstrate empathy in the face of a generational workplace shift, while creating stronger, more resilient companies – not just more efficient ones.”
EMPATHY DOESN’T REMOVE THE NEED FOR DIFFICULT DECISIONS
The tension is important. An empathetic approach to AI transformation does not mean organisations cannot automate tasks, redesign jobs, restructure teams or make difficult workforce decisions. It means considering how those decisions are made and how people experience them.
That could include communicating openly about why jobs are changing, involving employees in redesigning work, providing meaningful retraining, giving people sufficient time to adapt and supporting those whose roles disappear.
Managers also need the skills to handle those conversations. Recent research found that only four in 10 managers feel adequately prepared for difficult conversations involving AI anxiety, layoffs and workplace conflict.
That creates another workforce-readiness challenge. Businesses may invest in sophisticated AI systems while overlooking whether the people responsible for implementing workplace change have the human skills required to bring employees through it.
CUTTING CAPACITY BEFORE BUILDING CAPABILITY
Taken together, Businessolver’s findings expose a potential strategic contradiction. Businesses investing in AI understandably want the technology to produce greater efficiency and stronger financial returns.
But organisations seeking those returns through headcount reduction are also less likely to prioritise the workforce upskilling that could help AI deliver greater value. That matters because AI implementation itself requires human capability.
Employees need to know how to use the technology, when to trust it, when to question it and how to apply their own judgement when AI gets something wrong. Recent research found that four in 10 US workers using AI admitted accepting answers they suspected were wrong.
Only 22% worked under a written employer policy requiring verification. Meanwhile, other research has found that organisations with strong trustworthy AI practices are 15 times more likely to report strong or high returns from their AI investments. That study does not establish that trustworthy AI practices cause stronger returns. But it adds to evidence that technology investment alone does not determine whether AI delivers value. Governance, data, workforce capability, human judgement and trust all matter.
WHAT EMPLOYERS & BUSINESS LEADERS SHOULD DO NEXT
Build capability before removing capacity
Organisations considering AI-driven workforce reductions should first understand whether the technology and remaining workforce can genuinely absorb the work. That means assessing skills, workflows, AI reliability, management capacity and the additional human work required to check and correct AI outputs.
Invest in AI upskilling
Employers should not assume workers will acquire AI capabilities independently. They should provide practical, role-specific training that helps employees understand how to use AI effectively, where its limitations lie and when human judgement should take precedence.
Align the C-suite
AI strategy should bring together technology, finance, HR, risk and operational leaders. Different functions may see different risks and opportunities. Organisations need those perspectives around the same table before making major workforce decisions.
Measure capability alongside cost savings
Headcount reduction provides an immediately visible financial measure. Capability loss is harder to see. Businesses should therefore assess whether restructuring affects institutional knowledge, customer relationships, innovation, management capacity, critical thinking and the ability to supervise AI effectively.
Protect future talent pipelines
Before automating junior work, organisations should consider where future specialists, managers and leaders will gain the experience those tasks once provided. Apprenticeships, mentoring, work experience, rotational programmes and redesigned entry-level roles can help preserve pathways into work.
Prepare managers for difficult conversations
Managers need more than technical information about AI. They also need the confidence and skills to discuss uncertainty, changing roles, reskilling, performance expectations and potential job losses with employees.
Treat empathy as part of change management
Empathy does not require leaders to avoid difficult commercial decisions. It requires them to understand how those decisions affect people and communicate and implement change with transparency, fairness and respect.
WHY THIS MATTERS FOR RESPONSIBLE BUSINESS
The debate about AI and employment is often reduced to a single question: how many jobs will AI replace? Businessolver’s findings suggest businesses should ask another one: What happens if organisations remove workforce capacity faster than they build AI capability? Among executives prioritising AI-driven headcount reduction, just 18% also prioritise AI upskilling, compared with 35% of other executives.
At the same time, almost half of employees say they have been left to figure AI out for themselves. That combination should matter to any organisation expecting AI to produce sustainable productivity gains.
Fewer employees do not automatically mean greater efficiency if the people who remain lack the skills, confidence, time or organisational support needed to use AI effectively. And workforce transformation cannot be judged solely by the amount of work technology can automate.
Businesses also need to consider which capabilities they retain, which they develop and how tomorrow’s workforce will acquire the experience it needs. The organisations that gain most from AI may therefore not simply be those that become leaner. They may be those that become more capable.
Read the full report here.
RELATED ARTICLES
Nearly eight in 10 business leaders expect AI to boost growth and profitability, yet HR leaders are far less convinced organisations are ready for the workforce transformation required, reveals new study.
Some 42% of US workers surveyed who use AI on the job admit they have accepted an AI answer they suspected was wrong, while 30% say inaccurate AI output has already caused problems at work, reveals new research.
Managers are expected to lead employees through AI disruption, organisational change and difficult workplace conversations, yet only four in 10 say they have received the training they need, according to new global research.
New global research exposes a growing workplace trust and governance gap as employees embrace AI faster than workplace norms can keep up.
Nearly two-thirds of workers believe artificial intelligence is reducing entry-level hiring opportunities, according to new research.
