KPMG UK is proposing around 200 further job cuts in its advisory business, including roles connected with data, technology, artificial intelligence, and cybersecurity.
The planned reductions represent approximately 4% of KPMG’s permanent UK advisory workforce and are subject to consultation. Employees whose posts are removed are expected to leave in October if the proposals proceed.
The latest restructuring follows previous workforce reductions as the Big Four group adjusts capacity to weaker advisory demand and lower-than-expected employee turnover.
KPMG said market conditions and low attrition meant it needed to align skills and staffing with client demand. The consultation covers client-facing advisory teams, including parts of the data and technology operation.
The inclusion of AI, cyber, data, and technology roles is notable because those capabilities are also among the areas professional-services businesses are investing in as clients increase spending on automation, security, and digital systems.
It illustrates the distinction between long-term demand for technology expertise and the shorter-term economics of consulting businesses. A capability can remain strategically important while individual teams are exposed to utilisation rates, project pipelines, skills mix, and changes in how clients procure advisory work.
KPMG’s UK advisory sales fell 3% in the year to September 2025. The organisation has already reduced headcount from the elevated levels reached during and after the pandemic, when consulting and transformation demand expanded rapidly.
Large advisory businesses usually have some ability to adjust staffing through natural employee turnover. When fewer people leave voluntarily, that mechanism becomes less effective, increasing the likelihood of formal restructuring if demand remains below the level for which teams were originally built.
Artificial intelligence is simultaneously changing how professional-services organisations deliver work. Generative and analytical systems can review documents, interrogate large datasets, produce first drafts, identify anomalies, and automate repeated processes.
Those tools can improve productivity, but they also influence the balance between junior, specialist, and experienced roles. Work that once required substantial manual effort may increasingly be completed with smaller teams supported by automation.
The impact is unlikely to amount to straightforward substitution of technology for staff. Consulting work still depends on client relationships, specialist judgement, implementation, regulation, sector knowledge, and accountability. AI systems themselves are creating demand for data architecture, governance, cybersecurity, assurance, and organisational change.
The workforce issue is consequently becoming one of skills composition as much as total headcount. Advisory groups need enough expertise in growing areas while controlling the fixed cost of teams when project demand is inconsistent.
That pressure is intensified by low attrition. Large professional-services partnerships traditionally employ substantial graduate and early-career populations and expect a proportion of employees to move elsewhere each year. When turnover falls, planned recruitment and promotion structures can become harder to manage.
The wider UK labour market has also cooled. Vacancies have continued to fall and payroll employment has weakened, making external hiring conditions less fluid than during the post-pandemic recruitment boom.
For the Big Four, workforce planning sits alongside pressure to maintain profitability while funding technology investment. Proprietary AI tools, employee retraining, stronger data infrastructure, and governance controls all require capital at a time when clients remain selective over discretionary consulting expenditure.
AI adoption also raises questions about traditional career development. Junior employees have historically acquired expertise by carrying out large volumes of research, review, modelling, and analytical work under supervision. If software takes a larger share of those tasks, professional-services businesses must ensure new recruits still develop the judgement expected at more senior levels.
The KPMG proposals therefore sit within a broader restructuring of professional services rather than indicating withdrawal from technology. AI, data, and cyber expertise remain commercially important, but the number and type of roles required to deliver those services are changing alongside client demand.
The consultation will determine the final scale of the reductions. Across the wider sector, the combination of softer advisory demand, low staff turnover, productivity technology, and continued investment in AI is likely to keep workforce design high on management agendas.
You must be logged in to post a comment.