Smartsheet's recent research report, The Great British Productivity Paradox: Helping Leaders Burst the 'Busy Bubble', identifies a notable gap in UK business operations. While there is strong belief in AI’s potential to support productivity improvements, many organisations continue to rely on established metrics such as hours worked and tasks completed.
The report highlights a contrast between attitudes and practice: although 80% of leaders say AI is helping to improve productivity, traditional evaluation methods remain widely used. As a result, teams may spend time on lower-value activities, with some reporting the equivalent of one working day per week not directed toward strategic tasks.
Awareness of limitations in conventional productivity measures is relatively high. Around two-thirds of leaders say that “hours worked” is not a useful indicator of productivity, although more than a quarter still use it. A similar pattern is seen with “tasks completed”: 60% consider it outdated, yet around a quarter continue to rely on it, particularly in the public sector.
The report also notes that 68% of leaders associate “being busy” with being productive. According to the findings, this can influence workplace behaviour, with employees prioritising visible activity alongside core work responsibilities.
In terms of impact, the report estimates that teams may lose the equivalent of 10 weeks of productive capacity per year, or around £12,000 per employee in potential output. For larger organisations, this may represent significant financial value.
It also suggests that time spent on lower-value or administrative tasks can affect innovation and employee engagement. Six in ten leaders report observing what the study describes as “task masking” within their organisations, which they link to factors such as unclear priorities or workplace pressure.
The report suggests that addressing these issues may require changes in both systems and organisational practices. It recommends that leaders reassess how productivity is defined, focusing more on outcomes and business impact rather than activity-based measures, with AI playing a supporting role in enabling this shift.
It also highlights organisational culture as a factor, noting that clearer expectations and reduced emphasis on visible busyness may support engagement and performance.
In addition, the report points to AI-enabled work management systems as a way of providing greater visibility of work patterns and supporting prioritisation of higher-value tasks.
While UK leaders acknowledge that adopting new approaches may be challenging, the report frames this transition largely as a change management issue alongside technology adoption. It suggests that with appropriate tools and processes, organisations may be better positioned to use AI to support productivity goals over time.
