Will AI Make Work Better or Just Busier?

Fun fact: it took smartphones many years to become ubiquitous after the iPhone launched in 2007. ChatGPT, on the other hand, hit a billion monthly visits just four months after its debut. That makes it the fastest-spreading tech platform in history—and a signal that AI isn’t coming; it’s already here, woven into workflows, creeping into inboxes, and changing the rhythm of daily work across industries.

A contemporary office setup features a desktop computer displaying the motivational phrase "do more," promoting productivity.

Every major leap in workplace productivity—assembly lines, spreadsheets, Slack—has arrived with the same hopeful tagline: this will help us do more, faster, and ultimately work less. But has it? 

Generative AI is no different, except now that promise is dialed up to eleven. But if history is any guide, new tools rarely lighten the load. More often, they raise expectations.

While headlines warn that AI might replace workers, I worry about a different outcome: that it won’t free us from the burden of work at all, but instead will accelerate burnout by making overwork the new normal.

The burnout cycle

When I was in a corporate role, I loved finding ways to work more efficiently, but eventually learned that the payoff for speeding up often wasn’t time back. It was more projects, faster deadlines, fewer relationship-building moments, and higher expectations. In other words: a fast track to burnout.

Burnout isn’t just a buzzword—it’s the result of chronic workplace stress, and it shows up as emotional and physical exhaustion, mental fatigue, and a creeping sense of cynicism. Productivity drops along with the ability to meet the demands of the job, and even the best employees can start to question whether they can keep up.

AI is often pitched as the cure for overload. And yes, it has the potential to reduce the burden. But we need to be honest about the fact that it can also be a stressor. As AI becomes more powerful, it brings with it a flood of anxiety. Will my job disappear? Can I keep up with the learning curve? Am I falling behind without even realizing it? Will I lose my livelihood and my ability to provide for my family?

That’s what keeps me up at night when it comes to AI: not whether it works (it clearly does), but whether we’ll use it to create breathing room and sanity in our lives, or just fill every open space with new demands and anxieties like slowly filling sand into the empty voids.

The productivity paradox

The stakes are high. More than 30% of all workers could see at least half of their job tasks disrupted by generative AI. And this time, it’s not only the factory or administrative jobs that have previously been disrupted by automation that are on the line—it’s jobs that have long required advanced degrees and complex thinking, like analysts, marketers, lawyers, software developers, and, dare I say, HR professionals. The disruption is already happening, and while regulatory bodies are moving slowly, the real challenge isn’t technical—it’s human. 

The conversation about AI can’t just be about automation or productivity—it has to be about people. AI has the potential to be a powerful equalizer in the workplace, but to what end? For example, it can help lower-output workers level up by offering structure, streamlining tasks, and speeding up routine work, potentially narrowing the gap between them and so-called “star employees.” But then how do today’s high performers continue to differentiate themselves? My hunch is that they will figure out how to use these new tools in even more sophisticated ways, further accelerating their already strong output. The result? The bar rises for everyone, the productivity gap persists, and everyone continues to just work harder. (Side note: Don’t get me wrong - I am all for growing and improving, until it’s detrimental to your health.) 

One place this is showing up is in the job search. It used to be easy to spot a strong candidate by their resume and cover letter. Typos hinted at poor attention to detail, while a tailored cover letter showed critical thinking and genuine interest. Now, anyone can plug a rough resume and job posting into AI and get a polished application in return. What does this lead to? Flooding of resumes to job postings and the talent getting lost in the volume. LinkedIn reports a 45% increase in job applications over the past year. Yikes!

That levels the playing field—but also blurs the signals of standout talent. So, top candidates are forced to spend more time networking, optimizing LinkedIn, and showing up in ways AI can’t. And recruiters are forced to work longer hours, wading through a higher volume of candidates who appear qualified in order to sort the wheat from the chaff. 

The point is that this cycle of nonstop productivity “gains” might boost short-term profits, but it can potentially come at a long-term cost: a burned-out workforce. The fallout—higher turnover, rising healthcare expenses, higher unemployment, and declining work quality—can quickly erode any gains made on the balance sheet.

Who benefits?

It’s easy to get excited about the promise of AI-fueled productivity, but harder to pinpoint who actually benefits from it. Will organizations translate those gains into higher wages, broader equity ownership, or more inclusive performance bonuses? Or will greater output simply justify shrinking headcount and asking fewer people to do more, leading to greater unemployment? Right now, there’s no one-size-fits-all answer.

Some companies, like Publix Super Markets and Proctor & Gamble, have stock ownership and profit-sharing, giving employees a direct stake in any upside that comes from AI. Others, like Amazon and many other technology companies, lean on narrow performance bonuses that typically reward only top performers. While broad-based ownership models distribute value more equitably, bonus-heavy strategies tend to concentrate rewards among a small group, often leaving the rest of the workforce behind.

This is a pivotal moment for HR to rethink what fair and inclusive reward structures look like in an AI-enhanced workplace. Rather than defaulting to elite-only incentives, HR leaders can design policies that connect productivity gains to shared success through equitable compensation, transparent growth paths, and accessible upskilling. Because if AI is helping the business win, employees should feel like they’re winning too.

What HR leaders should be doing

As generative AI transforms the workplace and regulation struggles to keep pace, HR leaders play a pivotal role and must be proactive in recognizing the impact on people and ensuring that the technology supports people, not just productivity metrics. That starts with asking better questions.

• Instead of “What’s the ROI of AI for our organization?” we should ask, “What’s the ROI of AI for our people, and how are we defining productivity in an AI-augmented world?” Is it about volume and speed, or quality and well-being?

• Instead of “How does the company benefit from AI?” we should ask, “Are we equitably sharing the gains from AI?” Who benefits when output increases—just shareholders, or people at all levels of the organization?

• Instead of “How can we level up our productivity?” we should ask, “What boundaries do we need to set for employees to avoid burnout, and how are we proactively monitoring them?” Culture is shaped by what we normalize and reward.

  
  

To lead responsibly, HR teams should take proactive steps:

• Model healthy boundaries and monitor for burnout by encouraging leaders to log off, respect asynchronous communication, and use AI to reduce—not redistribute—burnout.

• Redefine performance expectations by shifting away from input-based metrics (hours worked) and toward outcomes and innovation. We got a taste of this with the unexpected shift to remote work in 2020, when observing desk-sitting was no longer an option to measure effectiveness.

• Create equitable compensation models that ensure productivity gains are shared through performance bonuses, profit-sharing, or other inclusive benefits.

• Get moving on skills and interests inventories so that when some tasks shift away from a person’s job, we have clear insight into what the employee is good at and interested in doing. This takes ongoing dialogue. 

HR has the chance to ensure that AI enables not just more work, but better work.

AI’s impact isn’t predetermined; it’s shaped by the policies we put in place. While there are undoubtedly structural and policy concerns - like how we define full-time work, whether reduced hours threaten access to benefits, or how we support lower-skilled workers as roles evolve - HR has the chance to ensure that AI enables not just more work, but better work.

The good news - and maybe the bad news - is that this is a collective problem that requires a collective solution. 

Designing worker-friendly AI policies is a bit like addressing the impact of smartphones and social media on teenagers: we know the current trajectory isn’t healthy, but without a shared agreement to change course, we keep following the momentum, even when it works against us. 

In the same way, if we don’t intentionally shape how AI is used in the workplace, we risk defaulting to a culture of constant acceleration and burnout. The challenge and opportunity is for work culture to align around using AI not just for greater output, but for greater well-being.

The bottom line

AI isn’t inherently good or bad - it’s a tool. But how we use it, who benefits from it, and whether it leads to burnout or balance? That’s a leadership choice. If we treat AI as just another productivity lever, we risk accelerating the pace of work without improving the quality of life for the people doing it. But if we’re intentional about how we define productivity, share gains, and set cultural norms, we have a real shot at creating a future of work that’s not just faster, but more human.

If the past has taught us anything, it’s that gains in human productivity aren’t guaranteed wins. They can come with a cost: burnout, rising health issues, and strained relationships. The real question isn’t what AI will do. It’s what we’ll do with it.

Interested in learning more about coaching and building human workplaces? Send me a note at Katherine@worksproutpartners.com. I look forward to hearing from you!