- A quarter of UK workers say they spend 7+ hours a week acting as AI middleware
- British workers are more likely to experience busy but unproductive days
- Workers still feel like they’re making progress and being more productive
New research has claimed human workers are increasing becoming ‘middleware’, plugging gaps between disconnected AI systems and data sources, reducing the efficiency of both AI agents and human workers.
The findings from Workday say the issue has become so bad, UK employees are now spending nearly an entire working day each week dealing with disconnected AI tools and systems, the software vendor says.
More specifically, around one in four workers spend upwards of seven hours per week copying information between apps, reconciling conflicting data and feeding context manually into their AI prompts.
Humans have become AI ‘middleware’
In its report, Workday fully acknowledges artificial intelligence has had proven benefits on productivity, however current inefficiencies switching between systems, verifying outputs and manually moving data are effectively removing those gains.
“Too many employees are serving as the human middleware between disconnected AI systems,” Workday VP Daniel Pell summarized.
The problem could be more pronounced in the UK, where more than 60% frequently experience busy but unproductive days, up from 43% globally. A similar number (62%) of workers also spend at least half their working time translating and coordinating between multiple, siloed systems, rather than creating actual value.
However, worker sentiment differs from reality. Around nine in 10 reported a stronger sense of progress, ownership over their work and a clear connection to organizational goals, and nearly half (45%) already say that AI has accelerated work in a productive way.
As for why companies are still struggling to deeply embed AI into workflows, Workday identified a number of barriers, including high volumes of approvals and governance checks (27%), uneven AI training and access (26%), rigid workflows and systems (26%) and poor data quality (24%).
“The companies seeing the most value from AI are building it directly into the systems where their people, data and work come together,” Pell concluded.
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