SOFIAH NICHOLE SALIVIO

News Editor

Bureau has urged businesses to use artificial intelligence to redesign workplaces for concentration rather than rely on software alone to raise productivity. The workplace design firm said poor office environments cost UK businesses an estimated £488 billion a year.

The argument comes as employers continue to spend heavily on AI tools while pressing ahead with return-to-office policies across the public and private sectors. Tyson Gundersen, co-founder of Bureau, said the physical office has changed little over the past decade despite rapid investment in automation, software and digital systems.

Many organisations still operate open-plan layouts that expose staff to noise, interruptions and distraction, he said. In his view, that mismatch between modern technology and outdated office design is undermining efforts to improve output.

The productivity gap

Gundersen argued that the central issue is not a lack of technology or talent, but the effect of constant disruption on employees’ ability to focus. Research cited by Bureau suggests workers can take up to 23 minutes to regain concentration after an interruption, while Microsoft’s 2025 Work Trend Index found employees are interrupted by meetings, emails or messages as often as every two minutes during the working day.

He said this repeated loss of attention creates a cumulative cost for employers. The claim adds to a wider debate over whether productivity gains from AI will be limited if workers remain in environments that make sustained concentration difficult.

Return-to-office requirements have made that question more pressing. A 2024 University of Pittsburgh study cited by Bureau found that 99% of organisations introducing return-to-office mandates recorded a decline in employee satisfaction.

The study does not explain the reasons for that decline, but Bureau pointed to office quality as one factor employers should examine more closely. It argued that the productivity debate has focused too narrowly on software, dashboards and automation, while giving less attention to the spaces where work takes place.

Role of AI

Rather than adding to digital noise, Gundersen said AI should be used to reduce low-value tasks and cut friction in the working day. He also argued that the technology can be applied to the design and management of office space.

Bureau pointed to AI-driven space planning as one example of how employers can track how workplaces are used and adjust layouts in response. Booking systems, acoustic monitoring and environmental controls can help identify quieter areas, limit distractions and refine office settings over time, it said.

That approach would shift office design from a fixed model to one that changes with observed work patterns. In practice, companies would use data not only to measure output and headcount, but also to assess conditions such as focus and friction in the workplace.

Design and focus

The company’s position reflects growing interest in the relationship between office design and employee performance. Open-plan workplaces have long been criticised for making concentration harder, yet they remain common because they are often seen as efficient uses of space and a way to encourage collaboration.

Bureau is calling for a more deliberate balance between collaboration and privacy. In its view, offices should do more than provide desks and should actively support concentration, privacy and productive work.

Gundersen said businesses have invested billions in AI tools, software, platforms and automation, yet most offices still look much as they did a decade ago.

“Businesses have spent billions adopting AI tools, new software, new platforms and new ways of automating work, yet most offices today look almost identical to what they did a decade ago. The same open plan layouts, with lots of noise, interruptions and expensive distractions. The technology has evolved, but the workplace hasn’t, and that disconnect is where productivity is being lost,” said Tyson Gundersen, co-founder of Bureau.

He said employers should rethink how they frame the link between productivity and technology.

“Businesses have spent years asking how AI can make employees more productive. The better question is how AI can help create workplaces where productivity is actually possible. AI didn’t create the modern office’s biggest challenges, but combined with smarter workplace design, it may finally help solve them,” Gundersen said.

Cokethorpe School has secured planning permission to transform the former headmaster’s residence into a new nursery for children from nine months until they start school.

Work is already under way to prepare the building, with the school also progressing the registration process and meeting the regulatory requirements needed ahead of opening.

READ MORE: US coffee chain ‘pulls out’ of historic market town

The nursery is expected to open towards the end of 2026, subject to the completion of the necessary approvals, including Ofsted registration.

The new nursery school building at Cokethorpe School near Witney (Image: Fortitude Communications)

The new nursery will be based within the school grounds and is intended to offer high-quality early years provision for children before they start school, creating much-needed additional nursery places for families in Oxfordshire.

Harriet Stapleton, Bursar at Cokethorpe School, said: “We are pleased to have secured planning permission for the nursery and are now continuing with the work needed to prepare the building, complete the registration process and meet the regulatory requirements ahead of opening.

Harriet Stapleton, bursar of Cokethorpe School (Image: Cokethorpe School)

“This is an exciting milestone in the development of our nursery, offering an early years provision in a setting that makes the most of Cokethorpe’s beautiful rural surroundings, extensive outdoor space and excellent facilities. We look forward to sharing further details as the project progresses.”

Cokethorpe School is an independent, co-educational day school for pupils aged four to 18, set within a 150-acre parkland estate in Oxfordshire.

Founded in 1957 and co-educational since 1992, the school provides a research-informed education in a happy, rural environment that nurtures and celebrates a broad range of talents and interests.

SOFIAH NICHOLE SALIVIO

News Editor

Reading Room found that only 27% of UK marketing leaders always review AI-generated outputs before using them. The survey also found that 12% rarely or almost never review them.

The figures come from a survey of 75 senior marketing leaders at UK organisations with revenue above £30 million, conducted as part of wider research into AI use among medium-to-large businesses.

Most respondents fall between those two groups, suggesting checks on AI-generated material are often applied inconsistently rather than built into workflow. For marketing teams, that matters because much of their work appears in customer-facing channels, where errors can quickly become public.

The research also pointed to a broader gap between AI adoption and results. A third of marketers said AI’s impact had been lower or significantly lower than expected, while only 4% said all of their AI programmes had moved beyond the pilot stage.

Governance gap

Security and compliance concerns were cited as the biggest barrier to AI programmes delivering greater value. Yet the survey suggests those concerns are not always matched by systematic review of outputs before publication or use.

The tension comes as businesses face growing scrutiny over inaccurate or misleading material produced with generative AI. Public examples have already emerged in the UK, including withdrawn reports containing fabricated or inaccurate information.

Reading Room argued that pressure on marketing teams to produce more content with fewer resources may be contributing to the inconsistency. Teams are being pushed for scale and speed while also being expected to manage risks around accuracy, bias and compliance.

Amanda Falshaw, AI Enablement Lead at Reading Room, framed the issue in brand terms.

“Marketing is usually the shop window to an organisation – often where outputs are more likely to be seen by the public, customers, stakeholders and journalists. This means the reviewing gap becomes less of an internal process problem and more of a brand and reputational issue. As a minimum, we should all be asking of AI outputs: what’s missing? What assumptions have been made? How would we verify this? Would I be comfortable putting my name to this?” Falshaw said.

Content risks

The findings add to a wider debate over how companies govern the use of generative AI in functions that publish large volumes of external material. Marketing has become one of the earliest and most visible corporate use cases for AI tools, spanning copywriting, campaign development, search content and personalisation.

That visibility also leaves the function particularly exposed when mistakes slip through. Inaccuracies, invented claims, and repetitive or generic language can weaken trust in brand communications, especially when AI output is published with limited human checking.

Falshaw said the issue extends beyond factual mistakes to the quality and distinctiveness of brand communications.

“From a marketing perspective specifically, much of today’s content is suffering from pattern saturation and when nobody with the right expertise is stopping to critically review the output, this sameness starts to creep into how brands communicate. This then undermines distinctiveness during a time when having a recognisable human voice is becoming a critical marker of brand trust,” she said.

Scaling problem

The survey was part of a broader study of 150 digital transformation leaders, split evenly between senior digital and marketing roles. The low proportion of respondents who said every AI programme had scaled beyond the pilot stage suggests many organisations are still struggling to move from experimentation to routine use.

That may help explain the mismatch between interest in AI and reported outcomes. If governance processes are weak or uneven, companies may be less willing to expand deployment into higher-risk or more visible areas. Equally, if teams are adopting tools faster than review practices can be formalised, pilot projects may remain stuck before wider rollout.

For marketing leaders, the data points to a basic operational problem rather than a lack of awareness. Respondents identified security and compliance as major concerns, yet only a minority said they always reviewed outputs. That gap suggests some organisations have yet to embed consistent human oversight into day-to-day use.

Reading Room said marketers should build a routine habit of scrutiny around AI output, checking for errors, bias and compliance issues before material is used externally. The survey found that just 4% of marketing leaders said all of their AI programmes had successfully scaled beyond the pilot stage.