AI is reshaping the workplace, not just in how tasks are completed, but in how value is created. In offices and teams across industries, a new divide is emerging between those who embrace AI tools to supercharge their productivity and those who don’t.
The rise of hyper-personalised productivity is forcing us to confront a difficult but necessary question: should mastering AI come with a financial reward?
While this may be a controversial and uncomfortable question to ask ourselves, it is an important scenario for HR leaders to consider. There are people I know who use AI multiple times a day to improve their output. But there are also people I know who don’t use it at all and don’t appear to have any desire to use it.
This has led me to ponder the idea that AI is introducing hyper-personalised productivity, where the same role and the same pay produces wildly different value contributions.
This means two employees with the same title might be operating at radically different levels of output. This is especially poignant at this point in time, where in many roles AI adoption is discretionary. Not every employee is embracing AI voluntarily in their role. While some were digital pioneers who saw AI’s ability to augment their work, others are far slower and hesitant to use these tools.
This leads to a pay and promotion dilemma: should those using AI to outperform others be paid more or given more promotion opportunities?
With AI now introducing the possibility of hyper-personal productivity, this makes internal pay equity and perceptions of fairness quite fragile.
When machines do the work, who gets paid?
Research from the World Economic Forum estimates that 47% of work tasks are currently performed mainly by humans alone, with 22% performed by technology, and 30% by a combination of both. Within just five years, it’s expected that almost 70% of our tasks will be completed by tech alone or a combination of tech and humans – with just 33% left to humans alone.
This leads us to ask other important but complex questions. If the ongoing share of the total economic output delivered by humans declines, then an organisation’s output is increasingly created by machines. If the majority of output is created by machines, or with the help of them, to what extent are humans able to share in the prosperity of the work involved?
To ask it bluntly, should we get paid the same if most of our historic work is now being produced by machines?
Designing reward systems for blended human-machine roles
Current pay bands and grading frameworks are typically based on inputs (role/responsibility) or market benchmarks – not output variability. With AI now introducing the possibility of hyper-personal productivity, this makes internal pay equity and perceptions of fairness quite fragile.
Not a lot of information, research or opinion on this topic appears online. But if you think about it, it does seem that AI is creating new ethical dilemmas around employee pay.
If AI is making an individual employee more productive, should they be paid more? Historically, if an employee has mastered a tool that enables them to produce greater or higher-quality outputs, they have been able to charge a premium for developing these skills.
From ploughs to spreadsheets to AI
In the 1980s, when spreadsheets entered the workplace, financial analysts, accountants and admin staff suddenly had greater data manipulation opportunities. Those workers who mastered software like Excel or Lotus became more efficient, more valuable and often rose faster in their careers. We can see from this specific example that those people benefited from their ability to master new tech.
Looking even further back to the Iron Age, we can see that employees mastering new technology were paid a premium. A single farmer with a plough and Ox could till far more land than one by hand. Those with access to ploughs were more productive, produced more food and earned more money. Skilled ploughmen were more valued and productive than basic labourers. In a scarce-resource economy, they were able to boost not only their output but their social standing.
Where this example differs from our current-day dilemma is that, unlike expensive farm machinery, AI is currently available to all employees.
Racing with the machine: The urgent need to reskill
The reality is that AI is working with humans to enhance productivity. A 2024 Stanford and MIT study found that generative AI tools can boost productivity by as much as 40% compared to workers who don’t use them. Tools like Microsoft’s Copilot are making employees 29% faster in tasks like searching and writing, with 70% of users saying they are more productive when using a tool like this.
But it seems it’s the workers with the least experience that are set to gain the most from this type of AI. A 2023 paper used data from over 5,000 customer support agents to conclude that access to AI assistance increased worker productivity by 15% on average for lower-skilled workers, but with little effect on high-skilled workers.
According to the World Economic Forum’s 2025 Jobs Report, on average, workers can expect that two-fifths (39%) of their existing skill sets will be transformed or become outdated by 2030. That is not long at all.
Given these evolving skill demands, the scale of expected workforce upskilling and reskilling remains significant.
If the world’s workforce was made up of 100 people, 59 would need training by 2030. Of these, employers will see that 29 could be upskilled in their current roles and 19 could be upskilled and redeployed elsewhere within their organisation. However, 11 would be unlikely to receive any reskilling or upskilling, potentially leaving their employment at risk.
At this moment, even if pay isn’t adjusted for those with the initiative and keenness to use AI in their role, those who see the value of these tools are likely pushing ahead, potentially creating a bigger proportion than the 11% expected to be left behind. So is this a question of AI impacting pay equity, or is it about a widening skills gap?
AI skills as a non-negotiable
Rather than debating whether those who master AI should earn more, perhaps the more urgent question is: why isn’t AI mastery built into every role by design?
Just as literacy in Excel or digital tools became non-negotiable in the modern workplace, AI should no longer be an optional add-on. It must become a foundational layer of how work is done – regardless of what you do, or where you do it.
Leaving adoption to individual initiative risks deepening inequality, especially as AI becomes central to productivity and performance.
If we want to ensure that no one is left behind, we must shift from passive encouragement to active integration, embedding AI into workflows, training, and job design. Should an employee’s pay hinge on who happens to pick up the tools? Or should it be about ensuring everyone has them in hand?
