UK businesses urged to rethink productivity amid AI shift

UK businesses are being urged to rethink how they define and measure productivity during the country's third annual National Productivity Week. Senior technology leaders warn that a narrow focus on doing "more with less" risks overlooking deeper structural issues that limit performance.

The government-backed awareness week has prompted commentary from industry executives who argue that traditional productivity levers no longer match the pressures companies face. They point to artificial intelligence, modern business applications and growing operational volatility as forces demanding a broader, more adaptive approach.

Many reject the idea of productivity as a simple output metric. Instead, they advocate continuous review of workflows, data use and skills, alongside careful deployment of automation. Several also stress the need for stronger partnerships with specialist providers as organisations confront complex technology choices and integration challenges.

Mark Wilson, Technology & Innovation Director at cloud and digital services provider Node4, said leaders first need a clear view of the constraints within their own operations.

"For businesses, improving productivity starts with understanding what's holding them back. Everyone is trying to work harder or 'do more with less', but what does this really mean? The reality is that it looks different for every organisation. That's why businesses need to take a step back, look across the entire company and identify where efficiencies can be unlocked. Crucially, this is not a one-off exercise. Productivity strategies need to evolve alongside the business and keep pace with technological advancements that enable businesses to automate simple tasks, enhance connectivity and unify systems," Wilson said.

His comments reflect a broader shift in thinking that treats productivity as an ongoing programme rather than a single initiative. Organisations are reviewing their use of data, collaboration tools and back-office systems with a view to simplifying processes as well as increasing output.

Wilson linked that shift directly to the use of AI and other software platforms.

"By implementing tools such as AI, and modern business applications such as ERP and CRM, businesses can begin to streamline operations, strengthen collaboration and create a more connected ecosystem. While the integrations can be overwhelming and appear costly at first, the long-term benefits will soon outweigh any concerns. Giving people the right tools can reduce overall business costs, save time on tedious tasks and ease workloads, increasing motivation across the workforce," he said.

He also argued that many organisations will need outside support as they modernise their environments and connect disparate systems.

"However, for many businesses this is a lot to take on, often in a short space of time. This is where choosing the right partner is key. Managed Service Providers can provide the technical expertise organisations need to introduce the tools and technologies that drive productivity gains, without the stress and complications they would face doing it alone. The key takeaway is this: when it comes to enhancing efficiency, productivity isn't one solution - it's an ecosystem," Wilson said.

Manufacturing leaders are framing the challenge in similarly broad terms, but with a sharper focus on operational resilience and downtime. Factory operators face rising supply chain turbulence, skills gaps and pressure on margins, placing new demands on maintenance and information flows.

"For too long, manufacturing productivity has been framed as a maths equation: more output, lower cost, fewer people. Early AI reinforced that mindset. But that's no longer where the biggest losses - or gains - are coming from.

"Today, productivity is defined by how well operations hold up under pressure. The real enemy isn't throughput; it's variability: unplanned downtime, supply chain disruption, inconsistent maintenance execution, hard-to-find information, and critical expertise walking out the door.

"The mistake isn't moving too slowly on automation - it's trying to automate everything at once. When technicians spend more time searching than solving, productivity breaks long before capacity does. AI should remove friction, turn asset data into instant answers, manuals into actionable guidance, and frontline input into repeatable execution."

"This isn't about doing more with less. In high-stakes environments, productivity comes from enabling skilled people to perform consistently on every shift, at every plant, every day," said Paraic O'Lochlainn, VP, eMaint, a Fluke Corporation brand.

His comments highlight how manufacturers are starting to evaluate AI not only on cost savings but also on its effect on maintenance quality, knowledge retention and the consistency of decisions made on the shop floor. The focus is shifting from blanket automation to targeted interventions that reduce variability and cut the time technicians spend searching for information.

Across the wider UK business landscape, executives also see scope for AI to change the nature of work by reducing repetitive administrative tasks. This, in turn, raises questions about training, oversight and performance metrics.

"Productivity in UK businesses is often limited by how much time is spent on repetitive admin tasks, rather than finding solutions to more complex issues. AI is starting to change this by speeding up how quickly teams can move from a problem to a workable solution, whether in planning, analysis or day-to-day operations. In effect, it gives employees an additional layer of support, shortening workflows and enabling faster progress from intent to outcome," said Josef Al-Sibaie, COO, Syspro.

He argued that the greatest value comes when staff use AI to expand the scope of their roles rather than simply complete existing tasks more quickly.

"The real opportunity here goes beyond efficiency. As routine work is automated, employees have more space to focus on critical thinking and more creative problem-solving. Unlocking that potential depends on leadership giving employees the freedom to experiment with AI, explore use cases relevant to their roles and build confidence through hands-on use. Curiosity and shared learning across teams sits at the heart of this, helping organisations move beyond seeing AI as just a tool for answering questions and instead view it as something that can actively carry out meaningful work, a means to automate manual workflows," Al-Sibaie said.

Al-Sibaie also pointed to skills and governance as constraints that will determine whether early experiments with AI translate into sustainable gains. Organisations need clearer measures of success and stronger analytical literacy across staff groups, he said.

"However, there are still barriers to address. Alongside ensuring that employees across the business have the technical skills to use AI to its full potential, knowing when to trust, challenge or refine outputs is also critical. Given that knowledge now sits at everyone's fingertips, it is the ability to synthesise actionable insights from this knowledge that will truly differentiate. Without those capabilities, productivity gains will be limited.

"Companies must define clear business objectives and measure the impact that AI has on achieving them, whether through reduced hours spent on a task, fewer human interventions in a process or lower error rates. These quantifiable proof points will serve as clear reminders of why AI is so powerful and drive continued excitement throughout organisations," he said.