Hello and welcome to Work Week, the podcast where we tackle one big question about the rapidly evolving workplace, explore what the research says about the topic, and explain what it all means for you.

I’m Dr. Gabby Burlacu, Senior Manager at The Upwork Research Institute. And what you’re hearing is a digital proxy of my voice — created by our team with the help of AI. 

Today, we’re going to discuss a workplace trend that’s as timely as it is disruptive.

For this week’s big question, we’re asking: How can organizations address AI anxiety in the workplace?

You’ve probably seen headlines about quiet quitting — employees who are doing the bare minimum and opting out of the hustle culture. These employees are disengaged, unlikely to take on additional assignments or prioritize their professional growth, and are just getting by. And while quiet quitting describes a phenomenon that isn’t new, it does give us the language to describe what happens when employees feel burned out. 

Quiet cracking is a related, but different, phenomenon. The term was coined by TalentLMS in a twenty twenty-five research report featuring insights from one thousand U.S. employees across industries. The report describes workers who experience quiet cracking as often caring about doing their job well, but feeling that the pace of change is so intense, the expectations so high, and the tools so unfamiliar, that they feel like they’re constantly behind and breaking under the pressure. They are past the level of change fatigue, and are on the cusp of fully burning out. 

The report further defines quiet cracking as an ongoing sense of unhappiness people feel in the workplace that leads to disengagement, poor performance, and an increased desire to quit. Data from the report shows that more than half of workers surveyed experience some levels of quiet cracking. 

Many professionals, especially younger workers, feel that the root cause of the rapid change, high expectations, and sense of increased pressure they feel is either AI itself, or the way their companies are implementing AI. 

Let’s start with what the data is showing us.

LinkedIn Corporate Communications and Censuswide recently surveyed more than nineteen thousand professionals to learn more about their feelings surrounding AI expectations. Over half of respondents — fifty one percent — said that learning AI feels like taking on another full-time job. 

Think about that for a moment. Rather than being perceived as a helpful tool, AI is seen as a second job layered on top of their existing — and growing — responsibilities. 

The data also shows that one-third of workers admit they feel embarrassed by how little they understand AI. And thirty-five percent of respondents said they feel nervous even talking about AI at work. They’re worried they’ll sound uninformed. They’re staying silent — not because they’re uninterested, but because they’re afraid of sounding like they’re behind the curve.

And the emotional toll is real. Forty-one percent of professionals say the current pace of change brought on by AI technologies is negatively impacting their wellbeing. Not their productivity or engagement — but their overall sense of health.

And if you think this is mostly happening with older generations — those who didn’t grow up with smartphones and social media — you’d be mistaken. The data shows that Gen Z professionals — the digital natives often assumed to be the most fluent in tech — are nearly twice as likely as Gen X to exaggerate or even lie about their AI skills at work.

When people feel pressured to show competence they don’t feel internally, they often disengage. Not outwardly or loudly. But quietly and persistently. They stop asking questions. They stop experimenting. They stop learning.

They keep showing up, but inside, they’re shrinking — or quiet cracking. 

This is the emotional reality AI transformation creates in many workplaces — and it’s not because people don’t want to learn. It’s because they feel anxious about not knowing.

At The Upwork Research Institute, we’ve also been tracking how AI adoption is playing out in the workplace. And one of the most striking patterns we’ve seen — which we discussed in episode eighteen of Work Week — is that the workers who are most productive with AI are also the ones most likely to report feeling burned out.

Findings from our research report titled From Tools to Teammates: Navigating the Human-AI Relationship show that eighty-eight percent of workers who are most productive with AI reported feeling burned out.

Let that sink in. The top AI adopters aren’t breezing through the workday on autopilot. They’re often overloaded, stretched thin, and emotionally taxed.

So the question becomes: If AI is supposed to make work better, why do many workers feel as though AI makes work more challenging? 

The answer lies not in AI technology itself, but in how organizations are rolling it out, communicating about it, and supporting — or failing to support — the people using it.

Let’s talk about what leaders can do to address the anxiety, burnout, and quiet cracking surrounding AI adoption. 

If you’re in a leadership role, the first step is to normalize not knowing. Be open and honest when you’re still learning — whether it’s a new AI tool or a new in-demand skill. Talk about what’s confusing. Admit when you don’t fully understand a new tool. Modeling this kind of vulnerability gives others permission to do the same. And when people stop pretending, real learning can begin.

Second, shift your focus from mastery to mindset. AI transformation is in its early stages. No one is supposed to have this all figured out. What matters more than expertise right now is curiosity. The willingness to try. The courage to learn in public. Celebrate effort, experimentation, and shared discovery.

Third, build time for learning into the actual structure of the work. If half of your workforce feels like learning AI is a second job, this indicates that AI adoption is being treated like an extracurricular. But it needs to be part of workers’ core responsibilities. Create space for training. Encourage peer-to-peer sharing. Host weekly team demos. Even short blocks of time dedicated to AI training can shift the perception from “this is extra work” to “this is essential.”

And finally, check in on your high performers. Especially those leading the charge with AI tools. They may seem like they’re thriving, but they could be quietly overextended. Ask how they’re doing — not only what they’re producing. Burnout can hide behind excellence.

Now let’s turn to the individual side of the equation — because even if you’re not a leader, you’re still part of this shift, and you have more agency than you might think.

If you’re feeling anxious about AI — whether you have feelings of confusion, intimidation, or pressure to catch up fast — start by giving yourself permission to be a beginner. No one becomes fluent in AI overnight. You don’t need to master every tool this quarter. You just need to start.

Find your preferred way of learning. Maybe your best option is video tutorials. Maybe it’s reading articles. Maybe it’s joining a Slack channel where people share prompts and AI experiments. The important step is to choose a method that fits your style — and then carve out a little time each week to practice.

And here’s a tip: Practice out loud. Talk with a coworker about something you’ve tried. Share a quick tip with your team. Offer to demo a tool you’re experimenting with. When you normalize being a learner, you do more than build your own confidence — you also help others feel less alone in their learning journey.

Another helpful strategy is to track your progress, even informally. Keep a note or document where you jot down which tools you’ve explored, which tasks you’ve used AI to complete, and what you want to try next. Sometimes seeing how far you’ve come is the best way to stay motivated to keep going.

As we always do, let’s end the episode with an action you can implement immediately and a reflection question to consider throughout the week.

If you’re leading a team, here’s your action step — carve out time this week to have a low-pressure, honest conversation with your team about AI. Don’t focus on adoption metrics or upskilling goals. Make the conversation about emotion and connection. Ask your team what’s exciting them, what’s confusing them, and what kind of support would make learning feel less overwhelming. Listen with curiosity, not judgment.

And if you’re an individual contributor or early-career professional, here’s one small but powerful step you can take this week. Pick one AI tool — whatever catches your interest — and set aside thirty minutes to practice with it. Try using it to simplify or speed up a task you already do regularly. Take note of what feels intuitive, what doesn’t, and what you’d like to learn more about. You don’t need to turn into an expert — just as someone who tried.

Now, your reflection for the week: Are you showing up at work as someone who’s willing to learn — or someone who’s afraid to be seen as a beginner?

This is a tough, but important, question. Because the workplaces of the future — the organizations that succeed with AI — will be built by workers who are agile and eager to learn. 

That’s a wrap for this episode of Work Week. I’m Gabby Burlacu and today we explored how AI adoption can lead to quiet cracking — and what organizations and individuals can do to address AI anxiety.

If this episode resonated with you, share it with a colleague or friend. And don’t forget to subscribe to stay up to date on the trends shaping the future of work.