AI is changing what workplaces will reward

Look at what people are rewarded for in the workplace, and you’ll get a more honest account of what an organisation values than any carefully worded statement of corporate values can offer. Communication, adaptability, and sound judgement may all be praised, but the most tangible rewards have generally remained attached to technical expertise, measurable output or the ability to generate revenue. Human capability has always mattered, although that importance hasn’t necessarily been reflected in how organisations recognise professional value.

The arrival of AI appears to be changing this stance. Ernst Young’s US business recently announced that it’s investing $100 million in employee rewards for people who develop the capabilities the firm believes will matter in a technology-led workplace. These include business acumen, judgement, and adaptability, alongside the ability to experiment constructively with AI. The awards range from smaller acknowledgements of everyday contribution to payments of as much as $25,000 for work that makes a material difference to the firm.

The size of the investment naturally attracts attention, but the more revealing part of the announcement is the decision to reward these capabilities at all. Organisations frequently say that their people are their greatest asset. EY is attempting to put a financial value behind that familiar sentiment.

KPMG and PwC have also implemented similar initiatives.

It raises an interesting point about what was being valued before AI entered the workplace. Exercising judgement, communicating well with colleagues, being able to adapt when circumstances changed…none of these was invented by generative technology. These capabilities have always influenced the quality of work.

What AI has done is make such contributions harder to ignore. Once a machine can produce a competent first draft, analyse large quantities of information or complete a routine technical task, producing the output is no longer necessarily where the greatest value lies. The more important contribution may come from the person who can recognise whether that output is useful, understand what has been missed, and decide what should happen next.

That represents a considerable change in how work is understood. Technical proficiency has traditionally offered organisations something reassuringly visible. A qualification can be verified, a task can be completed, a target can be counted. Human capabilities are more difficult to separate from the circumstances in which they’re used, so they’ve often been lumped under the oft-used label ‘soft skills’.

The phrase itself has probably contributed to the problem. ‘Soft’ can make these capabilities sound pleasant but secondary, as though they improve the atmosphere around the serious work without forming part of it. In reality, technical knowledge doesn’t decide how to approach a sensitive client conversation or when an apparently efficient solution could create consequences elsewhere. It cannot determine how firmly to challenge a colleague without closing down the relationship that makes an honest conversation possible.

These are not decorative additions to professional competence. They shape what technical knowledge becomes.

AI is making that distinction clearer because it can replicate parts of a task without assuming responsibility for what follows. It can generate an answer, but the existence of an answer doesn’t remove the need for someone to assess it. If anything, an authoritative and polished response can make human judgement more important because errors are no longer announced by clumsy presentation. They can arrive looking entirely plausible.

This is where the conversation becomes more interesting than a simple comparison between human beings and machines. EY isn’t offering bonuses simply for resisting AI or preserving a collection of qualities that technology cannot reach. Its reward programme recognises experimentation with technology and the ability to use it in ways that produce meaningful results. The value lies in the relationship between technological capability and human understanding.

That relationship asks more of people than merely learning how to operate the latest tool. Employees need to understand when AI can improve their work and when its apparent efficiency may be misleading. They must remain curious enough to explore what it can do whilst retaining enough independence of thought to disagree with what it produces. The future workplace may therefore depend less on who can generate the most information and more on who can make responsible sense of it.

This has implications for the way organisations understand their people. If human contribution is becoming more valuable, leaders will need a fuller appreciation of how it develops and how it appears in everyday behaviour. Adaptability isn’t simply enthusiastic agreement with every new initiative, for example. It involves responding appropriately to a changing situation, which may sometimes mean slowing down long enough to understand what the change requires.

Our behavioural framework is built around the understanding that people aren’t restricted to one fixed way of behaving. Individuals have preferences, but they can learn to navigate beyond those preferences when the situation calls for a different response. In an AI-enabled workplace, that self-awareness may become an increasingly important part of professional capability.

Someone who naturally enjoys exploring new possibilities may be well placed to experiment with emerging technology, but they may still need to recognise when greater caution is required. Another person may be highly attentive to risk and detail, yet need the confidence to engage with an unfamiliar tool before every uncertainty has been resolved. Neither approach is more human than the other, and neither provides everything an organisation needs on its own.

This is one reason the EY announcement matters beyond the employees who may receive the awards. Reward systems influence how people interpret success. When organisations promote technical specialists, praise high output, and build performance measures around productivity, employees learn which contributions carry status. A statement about the importance of human skills will struggle to compete with years of evidence pointing elsewhere.

Putting real money behind these capabilities sends a different signal. It suggests that using judgement well is not simply evidence of being a thoughtful colleague; it’s a contribution with organisational value. There’s still a larger cultural change required. A reward scheme can recognise valuable behaviour, but it cannot by itself alter every assumption about expertise or performance. If human capabilities are genuinely becoming central to work, they will also need to influence recruitment, professional development, and the everyday decisions through which careers progress.

This may prove to be one of AI’s less expected effects. Much of the workplace conversation has focused on what technology will replace, yet its more lasting influence may be on what organisations finally learn to notice. When a machine can perform more of the visible tasks, the contribution surrounding that task becomes easier to see: the interpretation, the awareness of other people, and the capacity to adjust when the obvious response isn’t the right one.

The irony is that organisations may need increasingly sophisticated technology before they fully appreciate capabilities that have been present in their workforce all along. People have always brought context and lived experience to their work, although those contributions haven’t been as straightforward to measure as speed or output. AI hasn’t made them valuable, but it may force organisations to become more honest about how much value they create.

EY’s investment is therefore significant not because it proves that human skills have won some contest against technology. It suggests that the terms of workplace value are beginning to change. The organisations that respond well won’t simply add a new set of competencies to an appraisal form. They will develop a better understanding of how their people think and how they can extend their behavioural range as the nature of work continues to evolve.

The workplace doesn’t need to choose between technical intelligence and human capability. It does, however, need to stop treating one as serious expertise and the other as a useful extra. EY’s decision brings that imbalance into view, and it may prompt more organisations to examine whether their own rewards reflect the qualities they now claim will shape the future of work.

Understanding how people prefer to think, communicate and respond to change can help organisations recognise and develop the human capabilities that AI is making increasingly important. Jigsaw Discovery provides a framework for exploring those preferences and helping people extend their behavioural range. If you’d like to discuss how this could support your people as the workplace continues to evolve, please get in touch.