AI is quietly redrawing career paths – and the divide is already visible

Promotions, pay rises and access to high‑impact work are increasingly being shaped by a new factor in the workplace: how well you use AI.

New research from Northern Kentucky University (NKU) suggests that professionals who regularly use tools like ChatGPT, Claude and Gemini are pulling ahead of their peers on multiple fronts – from earnings and performance reviews to confidence in their future career prospects. At the same time, experts warn that without deliberate action from employers, AI could become a “silent filter” that decides who gets ahead and who is left behind.

A 28% pay gap between AI users and non‑users

The NKU survey of 1,000 workers and students found a stark difference in outcomes between frequent AI users and those who rarely or never touch the tools.

Frequent AI users reported earning about 28% more annually than non‑users: $67,525 versus $52,681. They were also twice as likely to say their job performance had improved over the past year (51% versus 25%), and more likely to report receiving a raise and feeling confident about their career advancement.

In conversation with HRD, Wei Hao, MSCYS, program director and Professor in the Department of Computer Science at NKU, said those numbers reflect a meaningful shift, not a passing fad.

“Our research indicates that frequent AI users benefit from a significant advantage, he said. “Although no AI can guarantee a promotion, it is evident that frequent AI usage is associated with enhanced job performance and earning potential, which directly affects career progression.”

The pattern is similar in education. Nearly half of frequent student users (47%) said their academic performance improved in the past year, compared with just 23% of non‑users. Students who avoided AI were also more likely to report lower GPAs. That suggests the “AI advantage” is starting well before people enter the workforce.

AI as both amplifier and equaliser – but not equally

Why are early adopters moving ahead? Both Hao and Ilona Charles, CEO and co‑founder of people advisory firm Shilo, believe AI is doing two things at once: boosting strong performers and, in some cases, helping others close gaps.

“The data indicates that AI is having a dual effect, and the amplification effect is significant,” Hao explained. “AI helps to close the skill gap by assisting in drafting, research, and developing ideas. However, critical and strategic thinkers will benefit the most from AI. This creates a significant divide.”

Charles is seeing the same dynamic play out inside organisations.

“In practice, it is doing both, but not evenly,” she said. “AI tends to amplify existing strengths first, particularly for people who already have strong critical thinking, communication, and problem‑solving capability. For others, AI can help close certain skill gaps, but only when it is paired with learning, context, and good judgement.”

In other words, AI doesn’t magically make someone a better employee. It multiplies whatever is already there – good or bad. Workers who come in with strong judgment and curiosity are using AI to extend their reach, experiment and take on more complex work. Those with less support, training or confidence are more likely to dabble or avoid it altogether.

“This is why early adopters are often moving faster, not because they are more capable, but because they are better supported to experiment, use their imagination and apply AI meaningfully and with thought,” Charles added.

From output to judgment: what promotions look like in the AI era

One of the clearest shifts Charles is observing is how organisations are redefining what they reward.

“We are already seeing AI influence career progression, but not always in the way organisations expect,” she said. “We are starting to see greater emphasis placed on human judgement, maximising the use of AI, together with the relevant technical skills in order to secure jobs with greater responsibility.”

Where once promotions and pay rises were heavily tied to visible output – how many reports, decks or lines of code a person could produce – they are increasingly tied to the quality of decisions and impact. AI is quietly enabling that shift by taking over a share of routine drafting, summarising and analysis work.

“Promotions and pay rises are increasingly tied to impact and decision quality, rather than pure output, and AI is amplifying this shift,” Charles noted. “The risk for HR is assuming this happens organically, rather than intentionally designing career pathways that recognise new forms of contribution and leadership.”

For employees, that means the winners in an AI‑rich workplace are not those who can generate the most content with a chatbot, but those who can frame the right problems, interrogate AI output, and turn faster insight into better, more accountable decisions.

The everyday AI habits that compound into career advantage

Much of the benefit, Hao stressed, doesn’t come from flashy, experimental AI projects, but from mundane, repeatable use cases embedded in daily work. In technical roles, the tools are becoming a quiet co‑pilot.

“ChatGPT is also used by IT professionals to troubleshoot error messages and generate code, scripts, and command-line instructions,” Hao said. “These activities sit at the very heart of knowledge work. An employee who can synthesise information quicker, communicate more effectively, and prepare better for a task will immediately become more productive and reliable.”

Because these small gains occur dozens of times per week – faster email drafting, clearer briefings, better‑prepared meetings, more robust analysis – they compound over time into a noticeable performance gap. The NKU research found frequent users also reported better mental health, lower stress and improved work‑life balance, suggesting that AI may be helping them manage workloads more sustainably.

Will non‑users be left behind?

With such a clear association between frequent AI use and better outcomes, the obvious question is whether those who don’t (or can’t) adopt AI are destined to be left behind.

“There is a real risk that they will, but not because they lack the necessary technical skills,” Charles warned. “People fall behind when organisations fail to create safe, supported ways to learn and apply AI in day-to-day work.”

Hao’s analysis of the data points to a similar concern. Lower academic performers were more likely to be non‑users, and in the workplace, non‑users reported weaker performance improvements and lower confidence in their advancement prospects. That suggests that AI avoidance can both reflect and reinforce disadvantage.

“When AI adoption is left to individual initiative, it can quietly reinforce inequality at the individual, community, and organisation levels,” Charles explained. “The responsibility sits with individuals, leaders and the organisation to ensure AI becomes a shared capability, not a silent filter determining who gets ahead.”

The new AI literacy: verify, practise, integrate

For mid‑career professionals who want to be in the “higher pay and faster advancement” group rather than the “left behind” group, both experts say the solution is not to outsource more thinking to AI, but to build disciplined habits around it.

Hao highlights three in particular:

1. Verification: The NKU study found that only 38% of students always double‑check AI output. That might slide in a classroom; it will not in a high‑stakes business context. Treat AI as a fast first draft, not an authority.

2. Intentional practice: Effective AI users invest in learning how to ask better questions. That means specifying audience, tone, format, constraints and success criteria, then iterating based on the results.

3. Integration, not substitution: “Professionals who will advance most rapidly will be those who can use AI as a tool to enhance their knowledge, not replace it,” Hao says. The strongest performers use AI to broaden their analysis, pressure‑test their thinking and explore options – but the judgment and final decisions remain firmly human.

Charles agrees, adding that organisations need to match individual efforts with structure and support: clear policies, hands‑on training, time to experiment, and career paths that explicitly value AI‑enabled judgement, not just tool proficiency.

A new filter for merit

The NKU findings and emerging workplace trends point to a new reality: AI literacy is fast becoming a core component of career capital, in the same way that digital literacy and data skills did in previous decades.

Those who learn to use tools like ChatGPT to extend, rather than replace, their own thinking are already reporting better performance, stronger well‑being and higher pay. Those who are excluded from AI, or who avoid it without support, risk seeing existing gaps in opportunity and confidence widen.

The next phase, experts say, will be defined less by who has access to the technology, and more by how organisations and individuals choose to use it.

If employers design fair pathways, invest in AI education and reward judgement over raw output, AI could become a powerful equaliser. If they don’t, it may become exactly what Charles warns against: a silent, invisible filter determining who gets ahead in the age of intelligent tools.