Artificial Intelligence (AI) is reshaping the way white-collar work gets done. A survey published earlier this year by LinkedIn and Microsoft found that a large majority – three-quarters – of non-manual workers are using AI for work tasks, often without their employers’ knowledge or permission. While this hidden use of AI allows employees to work more efficiently, it raises some serious questions for both workers and managers.
Ethan Mollick, associate professor at the Wharton School of the University of Pennsylvania, calls these workers “secret cyborgs”. They’re leveraging AI to boost productivity and create higher-quality work, but they’re not being upfront about it.
Why? In many cases, using AI hasn’t been authorized by their employers, and staff are afraid of potential backlash. They may also be (and should be) concerned about the risks of sharing sensitive information, as AI tools may use this data for their own training, which could lead to breaches of intellectual property.
But the biggest issue is how AI is fundamentally changing the nature of “knowledge” work, which involves jobs that focus on using information, not physical labor. With these tools, employees like software engineers, content creators, and even consultants are becoming more productive, often doing the same amount of work in less time.
So, who benefits from this? Should the employees who are producing more get rewarded? Or should employers expect more work in the same amount of time? This tension raises important questions about the future of work and how AI is influencing white-collar jobs, especially the generative kind that can produce text, images, music, or code in seconds, and at a level that mimics human behavior.
“While AI is automating more routine tasks, the broader impact has been about changing how work gets done, rather than cutting positions.”
At this stage, AI isn’t eliminating jobs outright, but it’s taking over a lot of individual tasks for many people – often without managers even knowing. For instance, McKinsey reports that up to 30% of work hours could be automated by 2030, mainly due to generative AI. But the firm says: “We see generative AI enhancing the way STEM, creative, business and legal professionals work, rather than eliminating a significant number of jobs outright.”
The International Labour Organization (ILO) agrees, stating that AI will likely improve jobs by automating specific tasks, particularly in fields like clerical work. The main challenge for workers will probably be adapting to new job activities rather than worrying about widespread job loss. “The greatest impact of this technology is likely to not be job destruction, but rather the potential changes to the quality of jobs, notably work intensity and autonomy,” the ILO says.
While AI is automating more routine tasks, the broader impact has been about changing how work gets done, rather than cutting positions. But as employers gain more visibility into how AI is being used, that could change.
We know that many workers are using AI tools discreetly to boost their productivity, allowing them to accomplish more without their company requiring fewer employees. It’s entirely possible that this may have delayed direct job losses, particularly in white-collar sectors.
The productivity boosts in professions like marketing are already hard to ignore, and it’s likely that as AI becomes more mainstream, we’ll see shifts in workforce dynamics. In marketing, some companies are seeing big improvements, such as a 40% increase in response rates and a 25% reduction in deployment costs when using AI for targeted marketing efforts, says McKinsey.
In response, some employers are tightening controls on AI. Large companies like Apple, Spotify, Verizon, and Samsung have either banned or placed strict limits on how their employees can use generative AI tools at work. On the other hand, some organizations are embracing AI more openly.
Deloitte, for example, is introducing a generative AI chatbot to 75,000 employees across Europe and the Middle East. The tool is designed to help with tasks like creating PowerPoint presentations, writing emails, and coding to boost productivity.
But only 21% of companies have clear policies for how employees should use generative AI, according to McKinsey, typically focused on reducing risks like data inaccuracy and cybersecurity issues.
The challenge for firms is that AI is advancing so quickly that it’s becoming harder and harder to tell what work is human-generated and what isn’t. As a result, it’s tough for managers to accurately assess the contributions of their employees when AI can do tasks just as well, if not better, than humans.
According to the Stanford Institute for Human-Centered Artificial Intelligence, AI has outperformed humans in tasks like image recognition, visual reasoning, and understanding English. However, it still struggles with more complex challenges, such as advanced math, common-sense reasoning, and planning.
Even though AI can generate a strong starting point, savvy employees should know they need to refine and customize the output to make it believable.
This is where things get complicated for managers. If AI can generate high-quality work that’s nearly indistinguishable from what a human might produce, how do you measure an employee’s true value?
Even though AI can generate a strong starting point, savvy employees should know they need to refine and customize the output to make it believable. My colleagues Heather Cairns-Lee and Sarah Toms note that it’s still important for workers to add a personal touch to avoid raising red flags that the work is too polished or mechanical.
But for managers, the big challenge is finding a way to encourage employees to be transparent about their AI use without creating a culture of fear or mistrust.
To encourage transparency around AI use, companies should embrace AI as a valuable tool, offering controlled access while discouraging unsanctioned use. Standardizing AI in workflows can boost productivity, and as those gains grow, it’s key to reskill and redeploy employees. This approach reduces job loss fears and shows AI as a tool to enhance, not replace, their roles.
There’s also a concept known as “rate-busting,” where certain workers can outperform their peers, producing more work than what’s expected. These employees might hesitate to disclose their methods, especially their clever use of AI, as it could upset the balance in their team. But the longer AI use remains hidden, the harder it becomes for companies to address it head-on.
So early adopters of AI tools might keep their jobs, but they could also be contributing to the downsizing of their own profession. As AI becomes more integrated into specific fields, we may see fewer people doing the same work, and this shift will probably be accelerated as transparency around AI use increases.
AI is also changing how we think about talent and excellence. AI tools are leveling the playing field by helping those who may not have been top performers improve their work.
A study from Boston Consulting Group found that AI led to increases in quality and productivity, but the biggest gains were seen among workers who weren’t the best to begin with. So, while AI is improving the average, it may also be diminishing the value of excellence.
For managers, this presents a dilemma. Should they invest in their top performers and encourage them to use AI to push the boundaries of what they can do? Or should they focus on bringing everyone up to a higher standard using AI tools? It’s possible that AI could crowd out the need for brilliance, as the gap between great and good becomes smaller.
It’s clear that AI can boost productivity, but it’s up to managers to ensure that transparency, fairness, and accountability are maintained.
Organizations are now at a crossroads in terms of how to handle AI. Its use can certainly improve strategic thinking and help people work smarter, but it also comes with risks.
For one, there are concerns about protecting intellectual property when sensitive information is fed into AI systems. Additionally, as companies gather more data about employee workflows, AI-powered tools could emerge to assist managers, providing them with insights into how their teams are performing and who is using AI.
Managers need to be ready for the opportunities and challenges that come next. Over the next five years, AI will likely become an even bigger part of white-collar work. It won’t just take over repetitive tasks; it will probably help with strategic decision-making, communication, and even evaluating employee performance.
And, as AI gets more deeply integrated into work processes, the line between what’s done by a person and what’s done by a machine will blur even more.
The key will be figuring out how to use AI without losing sight of the human element. It’s clear that AI can boost productivity, but it’s up to managers to ensure that transparency, fairness, and accountability are maintained. In the end, how well companies adapt to this AI-augmented world will determine the future of work in the coming years.
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