Artificial intelligence is creating a new Reward problem. The issue is no longer simply whether artificial intelligence skills have value. In parts of the labour market, there is already strong evidence that some of these capabilities attract a meaningful wage premium. The harder question is what an organisation should do when the market begins attaching a premium to a capability that may later become an ordinary requirement of the job.
This is an important distinction because higher base salary is only one possible response. An organisation might use a temporary skills allowance, a hiring premium, a retention intervention, variable Reward, development investment or, in some circumstances, no separate Reward adjustment at all. The appropriate response depends on what the organisation is actually paying for, how long that value is expected to persist and whether the value sits primarily in the individual, the labour market, the job or the business outcome.
The central Reward question is therefore not simply whether artificial intelligence capability deserves recognition. It is whether the value being recognised should become a permanent part of salary architecture.
1. The market is sending a signal, but not a universal answer
PwC’s 2026 Global Artificial Intelligence Jobs Barometer, based on more than one billion job advertisements across 27 countries and territories, found that jobs requiring specific artificial intelligence skills carried an average wage premium of 62 per cent compared with comparable roles that did not require those skills. The premium varied significantly by industry, reaching 118 per cent in consumer markets while standing at 16 per cent in government and public-sector work. PwC also found that jobs requiring artificial intelligence skills were growing substantially faster than the overall jobs market. (PwC)
That evidence is important, but it should not be interpreted as a universal recommendation to increase salaries by a particular percentage. PwC’s methodology compares salaries offered for comparable roles requiring artificial intelligence skills with those that do not. It therefore demonstrates a labour-market differential, not an automatic prescription for how every employer should structure base pay.
Employer practice confirms that the market remains unsettled. Payscale’s 2026 Compensation Best Practices Report, based on 3,413 survey responses, found that 61 per cent of organisations had updated existing roles to include artificial intelligence-related skills or competencies. Yet 55 per cent had made no compensation adjustment for those capabilities. Fourteen per cent reported higher base pay, 10 per cent used bonuses and 9 per cent used equity or long-term incentives. (Payscale)
Taken together, these findings suggest that artificial intelligence capability can clearly influence labour-market pricing, while the Reward response remains far from standardised. The market may tell an organisation that a capability is scarce and valuable, but it does not automatically tell Reward whether that value belongs in permanent base pay.
2. Reward must separate market scarcity, job value, individual capability and business value
The difficulty arises because several different forms of value can exist at the same time. A capability can be scarce in the external market, valuable when held by an individual, increasingly important to the future requirements of a role and capable of generating measurable organisational value. Those conditions are related, but they are not interchangeable.
Market scarcity tells the organisation that demand currently exceeds supply. That may justify paying more to recruit or retain people with the capability. However, scarcity can decline. Training supply can expand, tools can become easier to use and a capability that differentiates candidates today may become an expected part of competent performance tomorrow. A current market premium therefore does not automatically justify permanent salary treatment.
Job value requires a different assessment. An employee becoming more capable with artificial intelligence does not necessarily mean the underlying job has become more valuable. Reward should still examine whether accountability, decision authority, organisational impact, complexity, risk or responsibility have materially changed. If those fundamentals remain substantially the same, the organisation may have a market-pricing issue without having a job-grading issue.
Individual capability introduces another distinction. One employee may possess advanced artificial intelligence expertise that materially improves performance even though the organisation does not yet require that capability from every person doing the same job. In that situation, the organisation is recognising something the individual brings to the role rather than something universally required by the role. Both may deserve recognition, but they do not necessarily require the same pay mechanism.
Business value adds the final layer. Possessing an artificial intelligence capability is not the same as generating sustainable organisational value through it. PwC’s 2026 research is relevant here because it finds that roles being “professionalised” by artificial intelligence, where technology amplifies expertise and increases the importance of judgement and leadership, are experiencing stronger employment and salary growth than roles where artificial intelligence primarily makes work easier for less specialised workers. (PwC)
The longer-term premium may therefore sit not simply in knowing how to use a particular tool, but in combining technology with judgement, domain expertise, accountability and the ability to translate capability into business outcomes.
3. The case for base pay becomes stronger when the capability becomes a sustained job requirement
Base salary matters because it converts a current market judgement into recurring fixed employment cost. That does not mean organisations should avoid incorporating artificial intelligence capability into base pay. In some circumstances, doing so will be entirely appropriate. The case becomes stronger when the capability moves beyond being optional, temporary or individual and becomes a sustained requirement of the role.
A useful test is whether the organisation would require the same capability from the next person appointed to the role. If the answer is yes, and if external market evidence repeatedly shows that comparable work requiring that capability commands a higher market price, incorporation into job requirements and salary positioning becomes more defensible. The case becomes stronger again when the organisation reasonably expects the requirement to remain relevant beyond a short technology cycle.
Even then, however, a base-pay decision should not automatically become a job-grade decision. The external market price of a role can change without the internal value of the job changing to the same extent. Market pricing tells the organisation what it may need to pay to compete for labour. Job evaluation addresses the relative size and value of the role inside the organisation. A disciplined Reward architecture needs both perspectives without treating them as the same decision.
This distinction is especially important in artificial intelligence because rapidly changing labour-market scarcity can increase salaries before the underlying accountability or organisational contribution of a role has changed materially.
4. Temporary pay mechanisms may be stronger when scarcity is real but its duration is uncertain
Artificial intelligence labour markets are changing quickly. That speed creates a structural risk for salary design because an organisation can convert a temporary scarcity problem into permanent fixed cost before it understands whether the shortage will persist.
Where a capability is genuinely scarce but its longer-term market value remains uncertain, a temporary skills allowance may be more appropriate than immediately embedding the full premium into base salary. A hiring payment may address an immediate recruitment constraint without permanently resetting salary relationships. A targeted retention intervention may be appropriate where a business-critical employee faces a credible external market premium. Variable Reward may be more suitable where the organisation wants to recognise measurable outcomes rather than simply possession of the capability.
Development investment should also be part of the economic comparison. If an organisation can build a capability internally at an acceptable cost and speed, repeatedly buying it from the external labour market at a scarcity premium may not be the strongest long-term solution.
Recent practitioner discussion reinforces this uncertainty. Korn Ferry has argued that as artificial intelligence becomes increasingly embedded in everyday work, some capabilities are moving from specialised advantage towards expected baseline, while differentiation may shift towards people who combine artificial intelligence with strategy, leadership and business impact. A recent Korn Ferry LinkedIn discussion makes the same point explicitly: the premium may increasingly move away from technical proficiency alone towards the ability to turn that capability into enterprise outcomes.
Pave’s current compensation discussion presents the other side of the market tension, highlighting continued strong competition for advanced artificial intelligence and machine-learning talent and the need for employers to plan for the cost of scarce technical expertise.
These perspectives are not contradictory. They indicate that different artificial intelligence capabilities may be at different stages of the scarcity cycle. That is precisely why a universal premium would be difficult to defend.
5. The RewardEdge Premium Migration Test
Before moving an artificial intelligence-related premium permanently into base pay, I would apply five connected tests. I refer to this as the Premium Migration Test, a RewardEdge practitioner lens rather than an established academic model.
The first test is role requirement. Has the capability become a genuine and continuing requirement of the job? One practical question is whether the organisation would require the same capability from the next person appointed. If it would, structural treatment becomes easier to justify. If it would not, the economic value may still sit primarily with the individual rather than with the job.
The second test is market persistence. Is the premium supported by repeated evidence rather than a single difficult recruitment exercise? Reward should examine external market data, hiring outcomes, turnover exposure, replacement difficulty and the availability of alternative sources of capability before converting short-term market pressure into permanent salary cost.
The third test is job change. Has artificial intelligence materially changed accountability, decision authority, complexity, organisational impact or risk? If so, the organisation may need to re-evaluate the role itself. If these factors remain substantially unchanged, a scarcity premium should not automatically become a grading adjustment.
The fourth test is economic purpose. Can the organisation clearly explain what the additional pay is purchasing? It may be buying access to scarce labour, specialised individual capability, retention protection, materially different work or measurable business outcomes. If the organisation cannot identify what the premium is intended to buy, it will struggle to determine how permanent that premium should be.
The fifth test is pay mechanism. Even when additional Reward is justified, base salary may not be the only or strongest instrument. The organisation should compare permanent base pay with temporary allowances, hiring payments, retention mechanisms, variable Reward, capability development and, where necessary, job redesign.
The purpose of the Premium Migration Test is not to prevent an artificial intelligence premium from entering base pay. It is to make the migration deliberate. Temporary market pressure should become permanent Reward architecture only when the underlying rationale is sufficiently persistent to justify that transition.
6. The governance risk exists at both extremes
Organisations can make two opposite mistakes. The first is to pay an artificial intelligence premium simply because current market narratives suggest that these skills command more money. The second is to continue adding artificial intelligence expectations to jobs while never reconsidering whether the market price, role requirements or Reward treatment should change.
Payscale’s evidence makes this tension especially visible. Sixty-one per cent of surveyed organisations had already updated existing roles to include artificial intelligence-related skills or competencies, while 55 per cent reported making no compensation adjustment for those capabilities. Payscale reiterated the same finding in September 2026, noting that compensation practices have not fully caught up with the changing work landscape. (Payscale)
That outcome is not automatically wrong. Artificial intelligence capability may be becoming part of ordinary competent performance. Existing market rates may already capture some of the change. The capability may not materially alter the value of the job. Or the organisation may reasonably choose to build the skill internally rather than attach a separate premium to it.
The governance problem emerges when none of those explanations has actually been tested. Reward does not need to respond to every new capability with additional pay, but it should be able to explain why the organisation is paying differently, or why it has consciously decided not to.
This is the distinction between a passive market response and an intentional Reward decision.
7. The executive question
The artificial intelligence pay debate is often framed around a simple question: who deserves an artificial intelligence premium? I think that framing is too narrow.
The stronger executive question is:
What exactly are we paying for, and should that value live permanently in base pay?
Sometimes higher base salary will be the right answer because the capability has become a durable requirement of the role and the labour market consistently prices comparable work differently. Sometimes a temporary premium will be stronger because scarcity is genuine but its duration remains uncertain. In other situations, variable Reward may better reflect the organisation’s desire to recognise measurable outcomes. A materially changed role may require formal re-evaluation, while a capability that becomes part of ordinary competent performance may eventually require no separate premium at all.
Those outcomes are not inconsistent. They represent different economic conditions and different Reward problems.
The real risk is therefore not paying an artificial intelligence premium. The risk is paying one without understanding whether it represents temporary market scarcity, individual capability, changed job value or sustainable business value.
Once a temporary scarcity premium becomes permanent base salary, a short-term talent response becomes part of the organisation’s long-term fixed Reward architecture. That decision can affect salary relationships, internal equity, future pay progression and the cost structure long after the original scarcity has changed.
A market premium can be completely rational.
Making it permanent requires a stronger test.
Inviting perspectives
I would particularly value the perspectives of Andrew Nowak, Eric Lint, Naotake Momiyama and Mike McClain on one boundary in this discussion:
When an artificial intelligence capability attracts a market premium, what evidence should determine whether that premium belongs permanently in base pay rather than remaining a temporary market intervention?
Different perspectives may produce different answers, and that is precisely why I think this deserves a more deliberate Reward governance discussion.
RewardEdge Daily Insights | Edition 19 Muhammad Ahsan Mehboob Founder, RewardEdge Consulting
Research note
The central evidence in this edition has been revalidated against PwC’s 2026 Global Artificial Intelligence Jobs Barometer, Payscale’s 2026 Compensation Best Practices Report and recent practitioner discussion from Korn Ferry and Pave. PwC supports the existence of significant artificial intelligence-related wage differentials but not a universal premium. Payscale demonstrates that employer responses are highly varied and that most surveyed organisations adding artificial intelligence capability to jobs have not yet introduced a separate compensation adjustment. Recent Korn Ferry and Pave discussions illustrate the current market tension between artificial intelligence capability becoming more commonplace in some jobs while highly specialised artificial intelligence talent continues to attract scarcity premiums. (PwC)
The Premium Migration Test is presented explicitly as a RewardEdge practitioner framework and not as a validated academic or industry-standard model. The article therefore keeps a clear boundary between externally validated evidence and RewardEdge interpretation.
