Better salary intelligence can reveal more than what a role pays - it can show how the market sees it
What’s a job really worth? For HR teams, answering that question has rarely been straightforward.
Salary remains a major consideration for Australian workers. Hays' latest Salary Guide found half of Australians feel underpaid, while 82% of businesses reported noticeable skills shortages over the past year. At the same time, employers are being careful about how they allocate remuneration budgets. Mercer forecasts the median Australian salary increase budget at 3.5% for 2026.
Against that backdrop, getting remuneration decisions right matters. Employers need to remain competitive enough to attract and retain the people they need, while making considered decisions about where salary budgets are spent.
But knowing the market rate isn't simply a matter of finding a salary figure. A useful benchmark depends on whether the role being compared accurately reflects the work, skills, seniority, location and industry involved.
When the benchmark tells you something unexpected
Australian construction services company JP Flynn discovered this while piloting Salary Intelligence, a new AI-powered salary benchmarking product developed by ELMO Software.
Salary Intelligence enables HR teams to quickly analyse existing or new roles against comparable positions in the market, drawing on the organisation's own workforce context alongside external market data. It also provides peer comparisons and position in range (PIR), giving HR a clearer basis for pay and workforce decisions.
JP Flynn compared a Project Administrator position with a Repair Coordinator position and received almost identical salary ranges, despite paying its Repair Coordinators more. That prompted the team to look more closely at its position descriptions and a role title it had used for around 15 years.
The business had already noticed that advertising for Project Administrators was attracting stronger but often overqualified applicants. The salary comparison helped the business pinpoint a possible reason: the word "project" could be implying a more senior or specialised position than intended.
"We've recruited these roles with those names forever — 15 years — and it never really dawned on us what impact a title has on the role's perceived value in the marketplace," says Andrew Crommelin of JP Flynn.
It's an example of why salary benchmarking is about more than comparing job titles. The description and positioning of a role can have a huge influence on who applies for it.
It also demonstrates why context matters as access to salary intelligence broadens. Traditionally, organisations wanting robust market benchmarking have often relied on specialist external reports or tools. For ELMO Software CTO Josh McKenzie, the opportunity is to make useful salary intelligence more accessible while giving HR the context behind the number.
"Salary benchmarking can be a slow, manual process. Without paid tools or reports, teams can spend hours piecing together data from multiple sources and still be unsure how current or relevant it is," McKenzie said.
ELMO's Salary Intelligence aims to simplify the process. Its AI considers the role description, location, industry and company in relation to the broader environment, combining this context with publicly available market information and aggregated, anonymised ELMO data to generate a salary range.
For McKenzie, bringing salary intelligence into the same environment as an organisation's broader workforce data is also important. Rather than adding another standalone tool for HR to manage, the insight sits alongside the workforce information already available.
Trust matters when AI informs pay
Making salary intelligence easier to access is only part of the equation. Pay is a sensitive workforce decision, and HR teams also need to understand how an AI-supported benchmark has been reached and what information sits behind it.
For ELMO, that means putting safeguards and explainability around the output. The models behind Salary Intelligence are built and owned by ELMO and run on ELMO infrastructure in Australia, while each benchmark includes a confidence indicator that explains in plain English how the result was generated.
"The human still makes the decision, but with better information, clearer reasoning and far less manual effort to get there," McKenzie said.
Peer comparisons and PIR add another layer of context, helping HR understand where an employee sits within the salary range for their role. This gives HR leaders a more informed basis for considering internal equity, individual experience and performance, organisational budgets and future salary decisions. It also gives people managers more robust information to support fair and confident pay conversations with their team.
Sometimes better intelligence will show that a salary range needs attention. Sometimes, as JP Flynn found, it can prompt a different question about the role itself. And sometimes it will simply provide reassurance that an existing approach remains on track.
As AI becomes more embedded in workforce decisions, its value will come from turning relevant, explainable information into better decisions. With Salary Intelligence, that means helping HR understand not only what a role should pay, but how it is positioned in the market and in the company, whether it is likely to attract the right candidates and where existing pay settings remain on track.
This article was produced in partnership with ELMO
