It ought to be a corporate dream: machines that shoulder the drudgery, leaving employees to think bigger and work smarter – yet reality is proving far less seamless.
According to the new 2025 Global State of AI at Work Report by Asana’s Work Innovation Lab, employees expect to offload over a third of their tasks to AI within a year – but only 27 percent feel ready to do so today.
The hurdle? Reliability. Nearly two-thirds (62 percent) of employees say AI agents are unreliable, with many reporting that the tech ignores feedback or confidently shares incorrect information.
When things do go wrong, accountability is also murky – with a third of workers saying either “no one” is responsible, or they don’t know who is.
Speaking to UC Today, Asana’s Senior Director of Product Strategy Victoria Chin says part of the problem is that the technology often lacks the basic context required to be useful.
If AI doesn’t know who is supposed to do what, by when, and why, it’s not going to deliver the outcomes that you need,” Chin explained.
"But without proper governance models, policies or training in place – we're going to see challenges."
All in on AI
Yet despite this uncertainty, adoption is surging.
The report found over three-quarters of employees (77 percent) already use AI agents, and 76 percent view them as a transformative shift – not just another productivity tool.
The most popular tasks included meeting notes (43 percent), document organisation (31 percent), and scheduling (27 percent).
And 70 percent would rather delegate certain repetitive tasks to AI than a human colleague.
But without proper training or clear rules, AI is stuck at the “admin” level, and could be creating more work than it saves.
Over half of workers said agents force teams to redo outputs due to mistakes. Nearly half also noted that AI lacks context about team priorities, which can amplify inefficiencies rather than reduce them.
"From the technology perspective, AI is incredibly powerful – but it still can't do everything, Chin added.
AI still makes mistakes, and people have seen these mistakes and make certain assumptions."
The Training Gap
The training gap is also stark: while 82 percent of employees say training is essential for effective AI use, only 38 percent of organisations provide it.
