What finance hiring managers actually pay for in 2026

Two thirds of finance and accounting hiring managers are willing to pay above market rate for the right candidate. That is the headline figure from the Robert Half 2026 UK Salary Guide: 67%.

It is a significant number. But it tells you less than you think until you look at what “the right candidate” actually means. Because the skills commanding that premium are not the ones most finance professionals lead with on their CVs. I have seen this firsthand. The gap between what candidates emphasise and what hiring managers actually value has widened, and AI is the reason.

The finance director role is already changing. The salary data tells you where the market thinks it is heading next.

The three skills that command premium pay

The Robert Half data names three: financial reporting, agentic AI capability, and data analytics.

On paper, those sound like standard competencies. In practice, what employers mean by each has shifted substantially.

Financial reporting does not mean the ability to produce a P&L. It means producing information the board can act on, fast, with commentary that tells the commercial story. I have built board packs for businesses turning over millions across multiple currencies. The reporting skill that commands a premium is not accuracy. Accuracy is the baseline. It is the ability to interpret the numbers and surface what matters before someone has to ask.

Agentic AI capability does not mean having used ChatGPT. It means understanding how AI agents operate within finance workflows: reconciliation, forecasting, exception management, and process orchestration. When I have evaluated candidates for finance roles recently, the ones who understand where AI tools fail are more valuable than the ones who can list the tools they have tried. Supervision requires judgment. Judgment requires experience.

Data analytics does not mean proficiency in Excel. It means the ability to interrogate data across systems, identify patterns, and translate findings into commercial insight. Not producing dashboards. Producing answers.

All three share the same structure. None is purely technical. None is purely about soft skills. Each one is a blend of technical competence and commercial judgment. That blend is what the premium pays for.

AI has not created new roles. It has rewritten the old ones.

There has not been a wave of new job titles in finance because of AI. What has happened is less visible but more significant. The expectations attached to existing roles have changed.

Chris Lawton, Group Managing Director of Executive Search at Robert Half, puts it directly: “Job descriptions are evolving. You are seeing more emphasis on systems experience, data tools, and exposure to automation or AI.”

I have seen this play out. Five years ago, a management accountant job specification listed reconciliation, month-end close, and reporting. Today the same role lists those plus “experience with automation tools”, “comfort with data visualisation”, “ability to work with AI-assisted processes.” The core accounting requirement has not changed. The expectation of what you bring alongside it has.

This is not a dramatic shift in any single role. Cumulatively, it means the baseline for every finance position has moved. The candidate who was competitive three years ago with solid technical accounting and strong Excel skills is now competing against people who bring that plus systems fluency plus a working understanding of how AI fits into the workflow.

The question is not whether AI changes what stays human in the finance function. It does. The question is whether the people applying for finance roles have noticed that the job they are applying for is no longer the job it was two years ago.

The AI CV problem

Here is an irony I did not expect.

AI tools that were supposed to help candidates stand out in the job market are making them blend in. Lawton is blunt: “A lot of CVs and applications are becoming more generic. Candidates are using AI tools to write them, which can make it harder to differentiate between applicants.”

When everyone optimises for the same keywords using the same tools, nobody stands out. I have reviewed CVs where the structure, phrasing, and keyword placement are so similar you could swap the names and not notice. The output is polished. It is also indistinguishable.

This creates an opportunity for finance professionals who can demonstrate specific, evidenced capability rather than keyword-optimised summaries. Real examples. Named systems. Quantified outcomes. A point of view that could not have been generated by a prompt.

The parallel to writing in your own voice when AI writes everything is exact. When the default output is competent and generic, distinctiveness becomes the competitive advantage. Whether that distinctiveness appears in a board report or a job application, the principle is the same.

Adaptability beats any single technical skill

The Robert Half data identifies adaptability as the single most valued trait employers are looking for. Above any specific system. Above any individual certification.

This makes sense. When the tools, processes, and expectations are moving at this pace, someone who has mastered one system is less valuable than someone who has demonstrated the ability to learn systems, work through transitions, and remain productive while everything around them changes.

I have implemented two ERP systems, built API integrations between platforms that were never designed to talk to each other, and sat with finance teams until the new process worked. The technical skills mattered. But the thing that made those projects succeed was not the technical knowledge. It was the willingness to keep learning when the system did something nobody expected, and the ability to bring the team along rather than leaving them behind.

The concern that AI devalues human capabilities has it backwards. Soft skills and critical thinking are becoming more valuable in an AI-driven environment, not less. Lawton puts it clearly: “AI can generate outputs, but it cannot replace human judgement or context.”

When the transactional processing is handled by machines, the human skills carry more weight than they did when the job was primarily technical execution. Judgement. Communication. The ability to interpret and challenge what the AI produces. The ability to lead a team through change that most people instinctively resist.

The finance professionals who command premium salaries will not be the ones who know the most about AI. They will be the ones who combine what they know with the judgement, communication, and leadership that AI cannot replicate.

Where the jobs actually go

The persistent fear that AI eliminates finance jobs is not supported by what I am seeing. What is happening is redistribution.

Transactional processing roles are contracting. Commercially focused roles are expanding: financial analysis, business partnering, strategic reporting, data interpretation. Lawton’s view is that AI could actually create more finance jobs in the long term: “Those jobs are growing because AI is enabling finance teams to do more, not less.”

Neil Cutting, Transformation Director at Oracle, adds context. Finance has always adapted to technological change. “Finance people are good at growing and developing, they always have been. Especially when it comes to tech.”

He is right. I started my career in Big 4 tax before the tools that exist today were conceivable. The shift from Lotus 1-2-3 to Excel to ERP systems to AI-assisted workflows is a continuum, not a rupture. The people who thrived at each stage were not the ones who knew the most about the outgoing technology. They were the ones who adapted fastest to the incoming one.

The net effect may be more finance roles, not fewer. But of a fundamentally different kind. For finance leaders building teams, the hiring profile has shifted. The team you built three years ago may not be the team you need three years from now.

That 67% figure is not abstract. It represents real money, available now, for finance professionals who have positioned themselves correctly. The positioning is not complicated. Demonstrate specific capability with the tools and processes that matter today. Show adaptability through evidence rather than assertion. And whatever you do, do not let an AI write your CV in a way that makes you sound like everyone else.

Data and quotes in this post are drawn from the ICAEW’s April 2026 analysis of the Robert Half 2026 UK Finance and Accounting Salary Guide, featuring Chris Lawton (Robert Half) and Neil Cutting (Oracle).