Irrelevant data wastes hours daily as workplace AI falls short

A new report has found that 42% of the information employees access at work is irrelevant, leading to significant productivity losses and increased frustration among staff.

The fifth annual EX Relevance Report titled "The Search for Relevance: Can AI Connect Employees to What Matters?" was released by Coveo, which collaborated with Arlington Research to survey 4,000 adults working for large companies in the United States and the United Kingdom.

The research highlights ongoing challenges in the workplace, with employees on average wasting three hours each day searching for the information they need to do their jobs effectively. The report also explored the rapidly evolving role of artificial intelligence in addressing these challenges, particularly in relation to accurate and relevant information retrieval.

According to the findings, 47% of employees feel burned out or frustrated due to not having the right tools or access to information required for success in their roles, representing a 12% increase compared to the previous year. Of those surveyed, 47% indicated that essential information is spread across multiple applications, identifying fragmented knowledge as a key barrier to productivity.

The study found that younger employees, including those from Generation Z and the Millennial cohort, are particularly affected. Gen Z employees reported searching for information for 30% of their day on average, while Millennials spent 29% of their working day on similar searches. Across the broader workforce, employees accessed an average of four different data sources in attempts to locate information relevant to their jobs.

Additionally, one quarter of employees acknowledged they do not know where to begin searching for necessary information, suggesting gaps in both knowledge management practices and employee training. The prevalence of irrelevant information adds to this challenge, as 42% of the content encountered while searching is not applicable to employees' roles.

An emerging issue outlined in the report involves the accuracy of artificial intelligence tools. Nearly half (49%) of employees reported experiencing so-called "AI hallucinations", a term referring to instances where AI generates incorrect or misleading information, emphasising the need for reliable and context-sensitive AI solutions in the workplace.

Despite these concerns, there is growing recognition of the potential of generative AI technologies to address productivity and information relevance. Customer self-service was identified as the top use case for generative AI adoption at 34%, with knowledge management (28%), employee productivity (26%), and self-service for data and analytics (26%) following closely. 42% of respondents indicated their organisations have invested in generative AI and related training aimed at improving job performance.

Commenting on the report, John Grosshans, Chief Operating Officer at Coveo, said, "Employees are empowered by the potential of advanced tools and intelligent solutions that can boost their productivity and well-being. In an age where artificial intelligence is more accessible than ever, it's essential to harness this potential to ensure employees can leverage it to its fullest. Relevance is key: employees need timely, tailored information through the channels they prefer. This report highlights how AI-search, unified knowledge platforms, and generative AI tools that are grounded in user context can help employees quickly find what they need, enhancing efficiency and creating a more seamless, rewarding work experience."

The report suggests organisations could benefit from unified digital workplaces and AI-powered knowledge discovery tools. These strategies aim to centralise information and reduce time spent searching, in turn alleviating frustration and risk of burnout among staff. The findings indicate that, while digital transformation and AI integration remain central to future workplace strategies, there are substantial gaps in current implementations that need to be addressed to realise promised improvements in efficiency and employee experience.