The rise of generative AI tools in the workplace has been meteoric. In early 2024, 75% of global knowledge workers reported using generative AI at work, a figure that nearly doubled in just six months.
ChatGPT, for example, reached 1 million users in only five days(versus five years for Netflix), illustrating the breakneck pace of AI adoption.
Business leaders have eagerly embraced these tools, hoping to boost efficiency amid economic pressures to “do more with less.” In fact, 96% of executives expect AI to increase productivity.
Many organizations have even dubbed 2023 the “Year of Efficiency,” pushing teams to accelerate output as they integrate AI into workflows.
Yet as AI technologies proliferate, a growing chorus of employees and experts are warning of an unintended side effect: digital overwhelm and fatigue.
The Accelerating Adoption and Expectations of AI
A 2024 Upwork survey found that 81% of C-suite leaders increased their demands on employees over the past year, often assuming AI would help workers accomplish more. More than a third of executives specifically expected staff to use AI tools to boost output.
It’s no surprise then that 85% of companies are mandating or encouraging AI tool use in some form. Generative AI has been heralded as the key to greater efficiency, from Microsoft’s Copilot in Office apps to Notion AI for note-taking. Leaders see these as transformative co-pilots that can automate grunt work and supercharge results.
However, this “AI-everywhere” momentum comes with sky-high expectations. In their enthusiasm, some managers assume AI solutions will instantly solve complex problems and eliminate bottlenecks.
This has led to unrealistic productivity targets and a belief that employees should dramatically speed up their pace of work. One study noted that many leaders are under pressure to capitalize on AI’s hype, creating a “near-relentless hype” cycle that raises short-term demands on workers.
Executives may be bullish, but cracks are beginning to show in this narrative, both at the leadership level and among employees themselves. Notably, half of business leaders in one late-2024 poll said company-wide enthusiasm for AI is already declining, citing “AI fatigue” after a year of intense change.
And more than half of those leaders admitted they personally feel like they are failing in their role amid AI’s rapid growth.
When “Productivity” Tools Create More Work
On the ground, many workers report that AI tools have not magically lightened their load, in fact, the opposite. A major 2024 survey by Upwork’s research institute revealed a striking reality: 77% of employees using AI say these tools have decreased their productivity and added to their workload.
In other words, the very tools meant to streamline work are, so far, creating extra work. Employees frequently spend significant time reviewing or correcting AI-generated outputs, moderating errors and refining content, which eats into any time saved.
In the Upwork survey, nearly 4 in 10 workers (39%) said they are devoting more time to double-checking AI’s work, and 23% are investing time to learn the new tools instead of performing their normal tasks.
Additionally, 21% reported being assigned even more tasks directly because of AI; for example, being expected to take on extra projects since “the AI will help.”
It’s clear that the path to efficiency isn’t plug-and-play. “Our research shows that introducing new technologies into outdated work models and systems is failing to unlock the full expected productivity value of AI,” notes Dr. Kelly Monahan of Upwork, adding that without rethinking workflows, AI is creating “more hurdles than solutions” for employees.
Workers themselves feel this disconnect. Nearly half (47%) of AI users say they have no idea how to achieve the productivity gains their bosses expect.
And about 40% of employees feel their company is asking too much of them when it comes to AI adoption.
The result is a troubling paradox: while 96% of executives remain convinced AI will make teams more productive, a majority of those teams are struggling with tech-induced inefficiencies.
These struggles are exacerbated by a lack of support and training.
In many cases, employees are handed powerful new tools but left to figure out how to integrate them on their own. It’s no wonder enthusiasm turns to frustration. Without guidance, adopting AI can feel like one more job on top of the day’s duties, learning the quirks of an AI assistant, experimenting through trial and error, and staying alert for the mistakes the AI might make.
One CEO described it bluntly: “The implementation of AI tools often requires extensive training… feeding data into AI tools, ensuring accuracy, and troubleshooting issues can be overwhelming,”leading employees to juggle their regular responsibilities with “AI maintenance” work.
When AI fails to deliver immediate results, any gap in output falls back on employees to fill, further increasing stress levels.
The much-promised productivity boost has yet to materialize for many, and in the meantime, workloads have grown.
Digital Overload, Fatigue, and AI Anxiety
The emerging consequence of this dynamic is “AI fatigue,” a blend of mental exhaustion, information overload, and anxiety specifically tied to AI-powered work.
Artificial intelligence is everywhere and in everything, as one commentator observed, and people are starting to feel overwhelmed by AI’s rapid proliferation.
AI fatigue refers to the sense of exhaustion or burnout from the constant engagement with AI technologies and the pressure to adapt continually.
Unlike past tech rollouts, the pace of generative AI’s arrival has been unprecedented (again, think of ChatGPT’s overnight ubiquity).
This fast evolution leaves many workers feeling they can’t keep up, and indeed 68% of employees say they struggle with the pace and volume of work today.
The introduction of AI is part of that volume: new chatbots, copilots, automated systems, each with its own learning curve and quirks.
AI Fatigue Manifests in Many Ways
Psychologists and workplace experts note several common symptoms of AI-related overload.
- Cognitive Overload: Mental strain from constantly interacting with AI tools (chatbots, recommendations, etc.) and learning new systems, leading to exhaustion.
- Technological Overload: Feeling overwhelmed by the sheer number of new AI platforms, updates, and features. It’s challenging to keep up with ever-changing tools, which can cause paralysis or resistance to using them
- Increased Workload Expectations: A worry (often justified) that deploying AI will simply raise the bar on output without removing any tasks, effectively expecting more work from employees with no extra resources.
- Rapid Pace of Change: Anxiety stemming from how fast workflows and skill requirements are evolving. The constant need to adapt can generate fear and uncertainty.
- Emotional Strain and Distrust: Some workers feel uneasy or skeptical about AI decisions (for example, AI evaluations of their performance), or they harbor ethical concerns, which over time can turn into fatigue and cynicism.
- Job Insecurity (AI Anxiety): A fear that AI could replace one’s job, often termed “AI anxiety.” In a 2023 survey, 38% of employees worried that AI might make their role obsolete. This worry is not trivial; those with high AI anxiety were far more likely to report stress (64% vs 38%) and poor mental health at work. The mere anticipation of being displaced or devalued by technology can be a chronic stressor.
One stark illustration of these pressures is how employees behave with AI when nobody’s looking. Recent research from Ivanti found that nearly one-third of employees (32%) who use generative AI at work keep it a secretfrom their bosses.
Why hide it? Some view it as a “secret advantage” over their peers, but many conceal their AI use out of fear; 30% worry it could put their jobs at risk, and 27% feel “AI-fueled impostor syndrome,” not wanting colleagues to doubt their own abilities if they rely on AI.
In other words, people are afraid that using AI, or admitting they need help from it, might make them look replaceable or less competent.
This kind of insecurity is a form of performance anxiety amplified by AI’s presence. It aligns with Microsoft’s finding that 53% of workers worry using AI on important tasks makes them seem replaceable.
Workers are walking a tightrope: encouraged to use AI for productivity, yet anxious about the very real implications for their job security and self-worth.
Beyond these psychological strains, burnout is on the rise. Burnout is a state of chronic physical and mental exhaustion often caused by prolonged stress or overwork.
Multiple surveys in 2023–2024 suggest that AI’s rapid integration is contributing to burnout levels. Upwork’s study reported 71% of employees are now burned out, with 65% specifically struggling to keep up with increasing employer demands.
Another global index found about 46% of workers feel burned out as they grapple with high workloads and “digital debt”(like overflowing inboxes and back-to-back virtual meetings).
Significantly, when employees perceive that their company prioritizes productivity over their well-being, they are much more likely to feel overwhelmed; 73% feel overwhelmed in such “productivity-first” cultures, versus 56% in organizations perceived to value employee well-being.
This perception gap is dangerous. Despite 84% of executives claiming their company values well-being over output, only 60% of employees agree.
The pressure to perform (often augmented by AI tools) without commensurate support is a recipe for exhaustion.
Coping with AI-Driven Work Pressure
The good news is that businesses and individuals are not powerless in the face of AI-related overwhelm. A growing body of best practices is emerging to manage the rapid shift in expectations and to harness AI’s benefits without burning out employees. Here are several research-backed strategies.
Acknowledge the Learning Curve
Organizations should recognize that productivity gains from AI may follow a J-curve: initial adoption often brings a dip in efficiency before improvements kick in. Instead of demanding immediate returns, leaders must allow time for experimentation, training, and iteration. As one expert noted, there is an upfront “investment of time and energy” required, learning the tools and integrating them, which should be planned for. Setting realistic timelines and expectations can relieve the short-term performance pressure on teams.
Invest in Training and Skills
A lack of proper training is a major barrier turning AI into a burden. Empowering employees with the skills and confidence to use AI effectively is critical. Yet currently only 1 in 4 companies have AI training programs. This needs to change.
Business leaders are beginning to respond; in one survey, 59% of senior leaders said they plan to expand training on responsible AI use in the next year(up from 49% previously).
Training should cover not just how to use AI tools, but when not to use them, how to interpret their output, and how to collaborate with AI on tasks. The goal is to reduce the cognitive load and uncertainty employees face, replacing it with a sense of mastery. When people know how to make AI work for them, the technology’s benefits are more likely to outweigh its costs.
Redesign Workflows (Don’t Just Pile On)
Simply layering AI onto broken processes or maxed-out schedules will backfire. Experts urge a fundamental “work redesign” to truly leverage AI. This means reevaluating which tasks are handled by humans vs. AI, and reorganizing work to eliminate low-value manual chores rather than accelerating alltasks indiscriminately.
For example, if an AI drafting tool saves a manager two hours on writing reports, that time could be reallocated to creative planning, not immediately filled with mundane admin work.
Upwork’s research director recommends co-creating new productivity metrics with employees and focusing on outcomes, so that AI is used to enhance quality of work and employee well-being, not just output volume.
In practice, this could involve automating routine emails or data entry to give employees more focus time on deep work. It also means ensuring workloads are adjusted as AI takes over certain duties, instead of simply expecting higher throughput from the same number of people.
Organizations should strive for “AI augmentation” rather than “AI overload,” redesigning jobs to make them more sustainable and engaging.
Foster Open Communication and Involvement
Fear and anxiety around AI often flourish in an information vacuum. To counter this, the American Psychological Association (APA) emphasizes transparent communication about AI initiatives.
Leaders should openly share howAI will (and won’t) be used and involve employees in discussions about implementation.
When people understand the purpose of new tools and have a voice in how their work is changing, it can dispel rumors and reduce the stress of uncertainty.
APA’s 2023 Work in America report advised companies to “provide information about AI and monitoring technologies and involve employees in these processes”to mitigate anxiety.
Equally important is creating a culture where employees feel safe to ask for help with AI, admit mistakes, or even push back if a tool isn’t working well. If workers are hiding their AI usage out of fear, managers should address that directly, making it clear that using AI ethically and thoughtfully is encouraged and will not make someone obsolete in the company’s eyes.
Balance Productivity with Well-Being
Finally, organizations must actively balance the drive for productivity with employee well-being. This isn’t just a platitude…it has measurable impacts.
When companies visibly prioritize well-being (through policies, workload management, mental health resources, and respectful expectations), employees are less likely to feel overwhelmed.
Some practical steps include:
- setting boundaries on after-hours communications (to combat digital overload),
- encouraging employees to take regular breaks and time off to recharge,
- and monitoring workloads to prevent chronic overtime.
It’s also helpful to celebrate quality work and innovation with AI, rather than just quantity.
By redefining productivity to include sustainability, companies can avoid the trap of squeezing employees too hard during the AI transition.
Leaders at Slack even suggest that introducing AI should go hand-in-hand with rethinking how work gets done, possibly adopting more flexible schedules or re-prioritizing tasks, so that technology truly makes work better, not just faster.
To wrap it up, the advent of AI in the workplace is a double-edged sword. On one side, we have unprecedented tools that canautomate drudgery, spark creativity, and boost performance.
On the other side, we see the very real human cost of adapting to these tools at breakneck speed: mental fatigue, stress, and a feeling of always falling short of rising expectations.
The key for both organizations and professionals is to navigate a balanced path: embrace AI’s potential without letting its hype dictate an unsustainable pace.
That means being honest about the challenges, patient with the process, and proactive in supporting the people at the heart of it all. As the early data from 2023–2025 shows, unchecked AI-driven “productivity” pressure can overwhelm even the most capable workers.
But with thoughtful strategies, training, communication, realistic goal-setting, and a renewed focus on well-being, AI’s promise can be realized in a way that enhances work and sustains the workforce.
The question “Is AI productivity overwhelming you?” should ultimately yield an answer of “No, it’s empowering me,” but getting to that point will require deliberate effort and empathy from employers and employees alike.