EY US is investing $100 million in a new employee rewards programme designed to recognise the skills and behaviours it believes will matter as artificial intelligence changes professional work.
The programme rewards technology adoption, but EY is making clear that simply using AI is not enough. It is also targeting qualities including business acumen, judgement, adaptability, experimentation, collaboration and leadership — the human capabilities needed to decide how technology should be used and whether its output can be trusted.
The Wall Street Journal reports that the programme includes spot bonuses of up to $500, while individuals and teams making a more significant contribution can receive awards of $10,000 to $25,000.
EY has organised the rewards around three progressively larger forms of impact:
Leading in everyday work: recognition for actions that contribute to learning, experimentation, collaboration and leadership in day-to-day work.
Delivering measurable transformation: larger recognition for people whose ideas or actions produce demonstrable change through technology, innovation, disruption or growth.
Creating firm-wide impact: the highest category, reserved for individuals or teams whose contribution has a material and enduring effect on EY.
“The pace and complexity of change in our industry require confident leadership.
“This significant investment reinforces our commitment to building the workforce of the future by recognizing the skills and behaviors needed to lead our profession and serve our clients with excellence.”
This is an important shift in what the firm is explicitly rewarding employees for.
From AI adoption to human judgement
For much of the Big Four’s AI race, the organisational message has been about adoption: use the tools, automate more work, increase productivity and redesign services.
But Big4News has been documenting the other side of that transition.
In a recent Big4News interview on AI governance, former GHD global CFO Wayne Banks warned about what he calls “automation deference” — the gradual erosion of professional scepticism when people become accustomed to receiving plausible, polished answers from AI systems.
Banks put the problem particularly starkly: professional judgement has to be exercised if it is to remain strong. If reviewers begin to approach AI-generated work as presumptively correct rather than as something that must be interrogated, one of the central safeguards of professional work begins to weaken.
The risk is not just theoretical.
Big4News has documented how reports published under the KPMG, Deloitte and EY brands contained fabricated or distorted citations, claims or case studies. PwC subsequently became the fourth Big Four network linked to reports containing serious fabricated or unsupported material.
Those cases illustrate why the qualities EY has chosen to reward matter. AI can produce fluent work. The professional’s contribution increasingly lies in determining whether that work is right.
Seen in that context, EY’s $100 million programme looks less like a conventional bonus scheme and more like an attempt to put financial incentives behind the antidote to automation deference.
The Big Four are redesigning how judgement is developed
The same shift is already visible in the way firms are training their youngest employees.
In July, KPMG US redesigned the training of nearly 1,000 audit and assurance interns, placing greater emphasis on professional judgement, critical thinking, fraud detection, agility and business acumen as AI takes over more routine audit work.
The problem KPMG is confronting is fundamental to the traditional Big Four career model. Junior auditors historically developed judgement partly by spending years performing relatively basic procedures themselves. If technology increasingly performs those procedures, firms must find another way to develop people capable of reviewing the machine’s work.
Research underlying KPMG’s programme sharpened the concern. In a study involving 523 early-career professionals, participants fell broadly into three groups.
50.1% were “AI Amplifiers” who outperformed the AI-only baseline, using their own analysis and judgement to create additional value.
25.8% were “AI Delegators” who produced results comparable to the AI working alone. They generally accepted its output with limited scrutiny and added little independent judgement.
24.1% were “AI Apprentices” who performed below the AI-only baseline. Despite attempting to critique the AI’s work, their interventions often focused on irrelevant issues or steered the system in the wrong direction.
The findings suggested that giving junior professionals access to better technology does not automatically produce better professional work: the outcome depends heavily on whether they have developed the judgement to know when to accept, challenge or improve what the system produces.
EY is tackling the same problem through its new Career Residency programme.
Selected assurance interns will be able to remain with EY for another eight to 12 months while completing university, combining project work with coaching and deliberate development of skills including critical thinking, professional judgement, curiosity, collaboration and technology fluency.
The approaches are different, but the direction is remarkably consistent.
KPMG is changing what junior professionals are taught. EY is changing how long selected interns are given to develop. And now EY is changing what employees are financially rewarded for demonstrating.
Regulators are grappling with the same issue. PwC has urged the PCAOB to make AI in audit its “foremost priority”, including guidance on automation bias, unreliable evidence and the need for humans to retain responsibility for critical audit judgements.
Why it matters
The economics of professional services have traditionally rewarded expertise, leverage and billable human time.
AI disrupts that equation.
If technology can perform more research, analysis, testing and drafting, then the value supplied by the human professional moves further up the chain: framing the problem, recognising when something does not make sense, challenging assumptions, weighing contradictory evidence and accepting responsibility for the conclusion.
That is particularly important in audit. No matter how sophisticated the technology becomes, professional responsibility for the audit opinion remains human.
EY’s new scheme therefore marks an interesting evolution in the Big Four AI race.
The firms have spent billions building technology and encouraging employees to use it. The emerging challenge is making sure the people working alongside those systems retain the capability — and the confidence — to challenge them.
EY is now putting $100 million behind that proposition.
First the Big Four invested in AI.
Now they are starting to invest in the people who have to know when not to trust it.
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About the author: Claudine Cassar is the founder and editor of Big4News, covering audit, consulting, regulation and governance across Deloitte, PwC, EY and KPMG.
Automation deference is the right name for it, and the reward scheme is the interesting part. Judgement has never responded well to being announced. It responds to what gets rewarded, and until now the incentive ran the other way: the reviewer who accepted the polished output moved faster than the one who interrogated it. The number worth watching is not the hundred million. It is whether anyone gets paid for the finding that slowed a job down.