UK productivity is growing again. Barely.

ONS's January to March 2026 release shows output per hour worked up by 0.4% on the same quarter last year, and 3.5% above pre-pandemic (2019 average) levels (ONS, Productivity flash estimate and overview, UK, January to March 2026). Output per worker actually fell — down by 0.1% on the year, because the number of people working grew slightly faster than what they produced.

The ONS's own framing is the useful bit: this quarter's growth is in line with the trend that's held since 2009. That trend is itself well below what the UK managed before the 2008 financial crisis. Growth hasn't collapsed. It's just been sitting in the same weak band for over 15 years, and the latest number confirms it's staying there.

Which raises an obvious question. 

If organisations have spent the last few years investing heavily in AI, automation and digital tools, why hasn't productivity accelerated?

The answer emerging from the evidence is that technology alone doesn't change organisational performance. The OECD's latest research on AI in the workplace concludes that AI has significant potential to improve productivity, but the gains depend on how organisations redesign work, invest in skills and support employees through change. In many workplaces, AI is speeding up existing processes rather than fundamentally improving them.

It isn't even the same story everywhere. By industry, information and communication has pulled away from the pack — output per hour there was up by 35.7% against 2019 levels by the end of 2025, driven by strong output growth. Human health and social work activities pulled the other way, down by 1.1% against 2019, largely because hours worked have grown faster than output. "UK productivity" isn't one number with one cause. It's several different problems wearing the same headline.

There's a measurement wrinkle too, worth a mention because it says something about how murky this all is. A newer approach using payroll data (Real Time Information) tells a rosier story than the traditional survey method — output per hour up by 2.1% on the year rather than 0.4%. Even measuring the puzzle accurately is, itself, a bit of a puzzle.

Productivity versus work intensification

There's another reason productivity isn't as simple as "more AI equals more output".

The OECD's 2024 report Using AI in the Workplace found that while AI can improve efficiency, workers also report higher work intensity, greater monitoring, and faster-paced work when implementation is poorly managed. Earlier OECD case studies reached a similar conclusion: AI often changes how people work rather than reducing workload altogether.

That aligns with what UK employees are already telling us. The Trades Union Congress' 2023 Work Intensification report found that 

more than 50% of UK workers believe the pace and intensity of work has increased. 

AI didn't create that trend, but it risks amplifying it if organisations simply ask people to do more with the time technology saves.

This may help explain why AI adoption and productivity growth have become disconnected. ONS business survey data suggests that AI adoption is increasing across UK businesses (rising from 12%-35% adoption between 2023 and 2026). Around 60% larger organisations report predominantly using AI to improve operations, however, relatively few have yet embedded it deeply enough to transform productivity at scale.

Technology can make work faster. It doesn't automatically make organisations more productive.

What the research says actually moves the number

None of this is solved by policy alone, and organisations aren't powerless while economists argue about the macro picture. The research consistently points to the same internal levers.

The Productivity Institute, the UK's dedicated productivity research body, continues to argue that management quality, leadership capability and workplace practices explain a significant share of the productivity gap between high- and low-performing firms.

The OECD's AI research reaches a similar conclusion. The organisations seeing the greatest productivity gains aren't simply deploying AI; they're redesigning jobs, investing in skills, and involving employees in how new technologies are introduced.

CIPD's Good Work Index continues to find that job quality — autonomy, manager relationships, manageable workloads, and meaningful work — is associated with stronger wellbeing and better organisational performance.

Gallup's State of the Global Workplace likewise links employee engagement with higher team performance and lower absenteeism.

The common thread is remarkably consistent. 

People who understand why their work matters, who trust their manager, and who feel their contribution counts, tend to perform better. 

This is exactly what our own Cracking the Culture Code research found back in 2018: a well-defined and embedded vision and purpose, backed by the right behaviours, drives intrinsic motivation and, with it, performance.

Seeing it play out right now

IN PRACTICE:  CULTURE POWERING PRODUCTIVITY AND VALUE

A major pharmaceutical manufacturer we have supported faces a significant productivity challenge: realising substantial operational savings over the next five years. AI and new operating models will contribute. But the foundation is cultural.

You can’t deliver transformation through technology alone if the culture isn’t change-ready. What they’re building is an integrated view of their culture, creating the conditions where people can be taken through disruption, reskilling happens in the right places, and the organisation can adapt faster because it’s more coherent.

The winners won’t be the ones that adopt AI fast. The ROI evidence on those who have rushed it is already clear. The winners will be the ones doing it thoughtfully, through the lens of culture, moving well, not just quickly.

As our MD Niall Cluley put it in The Times back in 2019: 

“Engagement is an outcome of how you manage culture, not a programme you bolt on. Meaningful work, good managers, human-friendly policies, fair pay and clear communication. Concentrate on these essentials and skip the other gimmicks.”

The UK's productivity challenge isn't simply a technology problem. It's a work design and management problem. AI may prove to be part of the solution, but the evidence increasingly suggests organisations only realise its benefits when they pair technology with better leadership, better jobs, and healthier workplace cultures.

The national puzzle isn't solved. But inside individual organisations, it's a puzzle you can actually work on.

If you want a clearer view of what's driving — or draining — productivity in yours, get in touch about a performance, productivity, and return on investment approach.

Sources

• Office for National Statistics (2026). UK productivity introduction: January to March 2026 and October to December 2025. https://www.ons.gov.uk/employmentandlabourmarket/peopleinwork/labourproductivity/articles/ukproductivityintroduction/januarytomarch2026andoctobertodecember2025
• OECD (2024). Using AI in the Workplace: Opportunities, Risks and Policy Responses. https://www.oecd.org/en/publications/using-ai-in-the-workplace_73d417f9-en.html
• OECD (2023). The Impact of AI on the Workplace: Evidence from OECD Case Studies of AI Implementation. https://www.oecd.org/en/publications/the-impact-of-ai-on-the-workplace-evidence-from-oecd-case-studies-of-ai-implementation_2247ce58-en.html
• Trades Union Congress (2023). Work Intensification. https://www.tuc.org.uk/research-analysis/reports/work-intensification
• CIPD. Good Work Index (latest edition). https://www.cipd.org/uk/knowledge/reports/good-work-index/
• Gallup. State of the Global Workplace (latest edition). https://www.gallup.com/workplace/state-of-the-global-workplace.aspx
• ONS. Artificial intelligence in UK businesses: 2023 to 2026 (2026). https://www.ons.gov.uk/businessindustryandtrade/business/businessservices/articles/artificialintelligenceinukbusinesses/2023to2026