Research from Atera surveyed 1,000 employees and 500 C-suite and senior enterprise leaders. It found that too many employees spend their days fighting broken systems instead of doing their own, value-adding work. 

AI is being embedded at pace in a drive to improve efficiency, yet the research suggests there is still friction in traditional systems which is limiting productivity.

Coined the ‘friction tax’, inefficiency in existing workflows appears to be costing employees significant time. 68% of employees report spending more than 10% of their day on “meta-work,” such as navigating processes, re-logging issues, and resolving technical difficulties, with 18% suggesting they spend more than 40% of their time on these time-consuming tasks.

As well as a time cost, there is a significant financial cost to organisations of ‘friction tax’. 

Among employees, 70% estimate delays cost them over $100 a week, and 36% estimate losses exceed $200 weekly. When this loss is multiplied across teams and functions, this results in significant time and financial loss for organisations. This issue is prevalent regardless of seniority, with 47% of leaders reporting losing 3+ hours per week to these same inefficiencies.

What is considered a small inconvenience, adds up to huge organisation wide losses, however the cost of which is likely widely underestimated. 

The report suggests 37% of employees experiencing a technical issue won’t submit a support ticket, with instead half finding their own workaround. While workarounds can be seen as problem-solving from employees, it creates a significant blind spot for organisations. Unreported issues lead to a lack of visibility into the full scale of operational drag, lost time and organisational cost. 

Despite Glitches, Demand for AI-Driven Productivity Gains Remains Strong

In the report, 58% of employees confirmed they were comfortable with AI handling autonomous tasks on their behalf. The employees noted improving work quality (47%), reducing friction (43%), automating routine tasks (41%), and enabling focus on higher-level work (37%) as their main motivators of using AI. 

However trust in AI also improves confidence. When AI can remove blockers, 33% reported an increased feeling of trust in AI. The report suggested low-stakes tasks help build this trust in the first instance, before AI use cases can become more widely and confidently adopted. 

Demonstrable ROI was paramount for 68% AI leaders, reducing interruptions was a priority for 60% of leaders and increasing operational control for 59% was key.

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Leaders appear to be embracing AI more confidently than lower level employees, with 91% reporting being comfortable with AI participating in higher-stakes, judgment-based work. 

However the blind spot is still prevalent with 74% of leaders believing their IT teams are aware of only 75% or fewer of the problems employees actually experience. The other 26% of leaders believe IT is exposed to less than half of issues. 

In order to overcome these blind spots and efficiency issues, AI must first be applied to everyday workflows where friction is currently inhibiting work.