During National Payroll Week 2026, Nik Brooks, our Director of Payroll, and I joined the Chartered Institute of Payroll Professionals (CIPP) to discuss how AI and automation will shape the payroll team of the future. Here’s a summary of our thoughts:
Our view is that AI will not replace payroll professionals. Used carefully it can take on routine admin such as data entry, reporting, and chasing. That leaves payroll teams more time for interpretation, advice, and the judgement calls AI should not make.
How much time does payroll spend on admin?
Earlier this year we surveyed our clients and received 262 responses from payroll and HR professionals. A large proportion told us they spend three or more days a week on admin, around 60% of the working week.
As Nik pointed out, that time is rarely one big task. It is more often 20 tasks of 20 minutes each. These include:
- Collecting data from different spreadsheets and emails
- Checking gross-to-net reports line by line
- Keying figures into pension portals
- Keeping court order records up to date
Calculating the payroll is seldom the slow part. Much of the time goes on entering the same data into more than one system, so better integration is as important as better tools.
A healthy scepticism
Only 25% of respondents said their team was ready to fully adopt AI. We do not see that as a problem. Payroll demands precision, and payroll professionals are accountable for every payslip. Caution is the right starting point. AI should guide people, not replace their judgement.
Breaking AI down
Part of the hesitation comes from how broad the term “AI” is. We find it more useful to think in four areas.
| Area | What it means |
|---|---|
| Data in | Entering information, such as a new starter's details, through a simple conversation, with the system prompting for anything missing. |
| Data out | Requesting reports in plain language rather than building them field by field. |
| Workflows | Setting rules for routine approvals, such as low-value expense claims with valid receipts, so they no longer create bottlenecks. |
| Rules | Turning policy documents, such as a maternity policy, into system settings without hunting for the right screen. |
What is missing from that list matters just as much. We do not believe AI should calculate pay, because the risk of it being confidently wrong is too high. Nor should it make judgement calls on unusual cases or compliance questions. If AI makes a team seven times faster but increases the error rate, it has not made the team more efficient.
From administrator to professional
If AI takes on more routine work, the payroll role changes. There is less data handling and more interpretation. That means reading legislation and contracts, explaining a figure to someone outside payroll, and advising on the cost and practicality of a new benefit. It gives payroll a stronger voice in the business. We employ payroll professionals, not administrators, and AI should let them spend more time using that expertise.
| Less of this | More of this |
|---|---|
| Collecting and keying data | Reading legislation and contracts |
| Entering the same data into more than one system | Explaining a figure to someone outside payroll |
| Chasing other departments for information | Advising on the cost and practicality of a new benefit |
This raises questions for the profession. If fewer entry-level tasks remain, how do people build the knowledge they need to progress? Research from the Stanford Digital Economy Lab suggests the concern is real. In the US early-career workers aged 22 to 25 in the most AI-exposed occupations saw a 16% relative decline in employment. The declines were concentrated in jobs where AI automates work rather than supporting people. But we do not have a complete answer. Qualifications are likely to become more important, and the industry will need to work through this carefully.
Start with security
Anyone exploring AI tools should begin with data security. Know where your data goes, make sure it stays protected, and have a clear AI use policy so everyone understands what is permitted. At Cintra the rule is simple: if IT has not installed it, it is not used for work.
The figures show why. IBM’s 2025 Cost of a Data Breach Report found that one in five organisations had a breach involving shadow AI (AI tools used without approval). Most breached organisations (63%) had no AI governance policy or were still developing one.
Automate the chasing
Chasing other departments for timesheets, salary changes, and new starter details should not be a human task. Automated reminders can handle much of it, leaving payroll teams free to focus on work that needs their judgement.
AI will not remove the need for payroll professionals. Used carefully, it will let them do more of the work that matters.
FAQs
Q: Will AI replace payroll professionals?
A: No. AI can take on routine admin but payroll professionals remain accountable for every payslip. Their role moves towards interpretation, advice, and judgement.
Q: Where can AI help a payroll team?
A: We find it useful to think in four areas: data in, data out, workflows, and rules. Automated reminders can also handle much of the chasing for timesheets, salary changes, and new starter details.
Q: Should AI calculate pay?
A: We do not believe it should. The risk of AI being confidently wrong is too high. Nor should it make judgement calls on unusual cases or compliance questions.
Q: How should payroll teams start using AI safely?
A: Start with data security. Know where your data goes, make sure it stays protected, and have a clear AI use policy so everyone understands what is permitted.
