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Diving overview:
- A study by Glean’s Work AI Institute found that three-quarters of knowledge workers say AI has increased their productivity, but only 13% report that the technology has significantly improved their company’s performance. Glean surveyed 6,000 digital workers and used insights from AI leaders using its platform for its inaugural Work AI Index report.
- Research shows that automation saves employees about 11 hours per week on average, but employees report spending much of that time managing AI. Workers said that out of the time they spent interacting with AI, they spent slightly more time managing the tools than using them to generate work. Only 27% of the time was spent learning how to use tools and building agents.
- The report found that successful AI implementation in enterprises depends on the human infrastructure surrounding AI. To improve use cases, leaders must commit to entrenching AI in the enterprise context, training employees on use cases, treating shadow AI as a signal that company-approved tools are inadequate, and embedding governance into daily decision-making.
Dive Insight:
While AI is offloading tasks that were previously done by humans, employees are now spending their time doing unobtrusive tasks that make the AI output usable, such as providing context to agents, checking work, flagging mistakes, organizing answers, and more.
According to the report, employees spent nearly six and a half hours a week on these maintenance tasks. Additionally, monotonous work can easily lead to mistakes. If employees stop carefully reviewing output and checking whether AI recommendations make sense (69% report doing so), mistakes will slip through the cracks.
“Too many companies treat AI adoption like a vanity metric: more seats, more prompts, more usage,” Rebecca Hinds, director of Glean’s Work AI Institute, said in the report.
However, increasing use of AI does not equate to productivity and technological transformation, she says. The report found that for every hour employees spend getting useful output from AI, they spend another hour making the AI usable. Green found that more than a third of AI sessions fail completely, requiring employees to either start the task over or significantly rework it.
When employees spend too much time managing AI, Hines said, companies aren’t eliminating jobs, they’re just creating new types of jobs and increasing overhead costs for employees and managers.
Companies that make AI part of how they actually do business will be more successful than those that use AI for AI’s sake, Hines said. Successful companies are further building their human infrastructure around the use of AI and training employees on when and how to use AI and the guardrails around it.
They will also learn to reinvest the time saved by AI into higher-quality, human-centered work and stronger AI skills, rather than making the most of AI, the report says.
Success in large companies is more likely with foundations at the individual, team, and organizational levels.
“It’s based on the right context, measured against actual results, and managed in a way that supports our employees to move quickly without lowering quality standards,” Hines said.
