Despite promises that artificial intelligence (AI) technology would be a boon to worker productivity, an Upwork survey finds more than three-quarters (77%) of employees say AI increased their workload.
While 96% of C-suite leaders have high expectations that AI will enhance productivity, the results indicate the much-lauded tech is hampering productivity and contributing to burnout.
There is also a knowledge gap and lack of upskilling and reskilling in this technology among employees—47% of employees using AI have no idea how to achieve the productivity gains they’re aiming for.
They’re spending more time on tasks like reviewing AI-generated content (39%), learning how to use these new tools (23%) and generally doing more work overall (21%).
On top of that, 38% feel overwhelmed by the expectation to use AI at work, which adds to their stress and burnout.
Organizing Workloads
“Our problem isn’t with AI technology; it’s with outdated thinking about how we organize work and talent,” said Dr. Kelly Monahan, managing director and head of The Upwork Research Institute. “This stark disconnect between executive expectations and employee experiences is a wake-up call for business leaders.”
She added it underscores that introducing AI into outdated work models and systems is failing to unlock the full productivity potential of AI, creating more hurdles than solutions for employees.
The research also found that there’s a significant gap between the perspectives of employees and C-suite executives.
While those in the C-suite see it as a game-changer for growth and competitiveness, only 65% of employees share this optimism.
“Merely employing this new technology for efficiency improvements overlooks a crucial aspect of its potential capabilities,” Monahan said.
She explained every worker should now think of themselves as an essential part of R&D, rethinking how to best do their work and accomplish their goals considering AI advancements.
“To accomplish this, a mindset shift is needed to move beyond bottom-line productivity metrics to ones that focus on innovation and creativity,” she said.
There’s also the steep learning curve — 23% of respondents said they are investing a lot of time on learning how to use these tools effectively.
Additionally, 21% are now being asked to do more work overall, and 40% said feel they’re asking too much from them in terms of AI adoption and usage.
“It’s clear that without proper support, AI is becoming more of a burden than a benefit,” Monahan said.
She advised that to reap the full productivity value of AI, leaders need to create an AI-enhanced work model.
The research identified three core investment opportunities that enable an AI-enhanced work model, which leads to higher workforce productivity and less burnout.
Monahan emphasized the importance of incorporating outside experts to assist with AI projects, noting that 48% of global C-suite leaders are using freelancers to expedite delayed AI initiatives.
This approach has reportedly doubled innovation outcomes for 39% of these leaders, with AI adoption being notably high among freelancers.
“Nearly half of freelancers consider themselves proficient in AI, and over a third use AI tools regularly,” she said.
Monahan also advised rethinking productivity measurements, suggesting a shift from efficiency-only metrics to those encompassing creativity, innovation, strategy contributions and adaptability.
“This aligns with findings that workers who help co-create their productivity metrics report higher productivity and lower stress levels,” she said.
She also suggested a transition towards skill-based hiring and workflows, which requires investment in making existing workforce skills visible and developing those that enhance AI capabilities.
However, current awareness of AI skills within the workforce remains low, with only 40% of leaders reporting a high level of awareness.
She explained to better utilize AI tools for increased productivity, employees need comprehensive training programs focused on both technical skills and practical applications.
“Ongoing education, hands-on workshops, and access to AI specialists for personalized guidance are essential,” Monahan said.
Additionally, feedback mechanisms such as regular surveys and open forums help identify and address challenges.
She said when employees are involved in co-creating productivity measures, there is a greater emphasis on attributes like creativity, customer relationship building, and adaptability.
“Aligning AI programs with co-created productivity outcomes can help clarify AI productivity goals and balance the needs of the business and its workforce, leading to enhanced satisfaction and productivity,” Monahan said.
