TECHNOLOGY
Future skills for a tech-enabled payroll workforce As technology continues to evolve, so too must the skills of the professionals who manage it. The future of payroll will not only require technical proficiency but also strategic thinking, data literacy and a deep understanding of compliance and employee experience. One of the most critical skill sets will be digital fluency. Pay professionals will need to understand how to work with cloud-based platforms, automation tools and AI-driven analytics. This includes the ability to interpret dashboards, configure rule-based engines and troubleshoot data integration issues. Data literacy is another essential competency. As payroll becomes more data-driven, professionals must be able to analyse trends, identify anomalies and generate insights which support decision- making. This requires technical skills as well as the ability to communicate findings effectively to stakeholders across HR, finance and compliance functions. Soft skills will also play a pivotal role. The ability to manage change, collaborate across functions and provide a high- quality employee experience will be key differentiators. As AI and automation take over routine tasks, pay professionals will spend more time on advisory and exception management roles – human- first tasks which require empathy, judgment and communication skills. A closing reflection If the last year proved anything, it’s that payroll doesn’t need AI for novelty; it needs AI for reliability, explainability and scale. The most successful teams partnered with technology to strengthen their professional judgment, not to replace it, and insisted on designs which respect governance and local nuance. As you shape your plans for the year ahead, anchor them to outcomes your stakeholders can feel: pay that’s right first time, transparent processes and faster answers to the questions employees ask. The pay profession isn’t just keeping up; it’s setting the pace. And that’s something worth celebrating. n *The views reflected in this article are the views of the author and do not necessarily reflect the views of the global EY organisation or its member firms.
queries in seconds, pay professionals have embraced tools which reduce risk and elevate the employee experience. The result is a function that’s faster, more resilient and visibly more strategic. Technology integration: from legacy pain to interoperable platforms Despite the ‘productionisation’, maturity and scalability of AI, most breakthroughs in the past year were about plumbing, not pyrotechnics. For example, EY has developed a system-agnostic integration layer, which consumes human resources (HR), time and finance exports in native formats, transforms them to a standard model and feeds compliant country engines, speeding implementations and lowering the ongoing cost of change. It’s one thing to buy or build a clever tool: it’s another to weave it into a landscape of HR, time, finance and local gross-to- net engines. The past year has rewarded approaches which are able to ingest data in native formats, transforming it to a standard model and keeping connectors current with upstream releases. That reduces information technology effort, equips payroll for change and shortens time-to-value. Crucially, governance has kept pace. Teams are codifying AI intake, risk assessment and continuous monitoring – linking AI inventories, policy authoring, approval workflows and integrated risk management. That matters as regulatory regimes (e.g., the EU AI Act) become part of ‘business as usual.’ The lesson? Data and platform integration isn’t a one-off project; it’s a capability. When payroll owns a modern integration layer and credible AI governance, change becomes routine rather than disruptive. Over the last 12 months, the leading payroll teams have really leant into this challenge and are becoming the beacons of innovation for finance and HR teams. How to stay at the forefront of transformation: start with the end in mind The most effective programmes in the last year had clear outcomes from day one: fewer defects, faster cut offs, lower total cost of ownership and a measurably better employee experience. Technology choices followed those goals, not the other way around. In practice, that meant selecting tools that:
l slot into the existing landscape with minimal disruption l come with embedded controls and auditability l produce consistent data that finance can trust. A helpful tactic has been to tie AI investment to operational key performance indicators (e.g., variance cycle time, percentage of re-runs avoided, first contact resolution of pay queries) and to review these alongside payroll accuracy and timeliness during service governance. When leaders do this, AI stops being a ‘project’ and becomes part of how payroll runs. “When payroll owns a modern integration layer and credible artificial intelligence governance, change becomes routine rather than disruptive” And consider the challenges we still need to solve We cannot take the exceptional achievements of the last year for granted. Three years ago, most of us were only talking about AI if it had been in a science fiction film, so there’s no doubt that the inexorable march of technology will continue. Where we must stay vigilant in the coming years: Data readiness AI is unforgiving of poor inputs. Standardising sources, enforcing validation and clarifying ownership remain non-negotiable. Responsible AI and compliance As adoption outpaces controls in many companies, formal assessment frameworks and continuous monitoring are essential to maintain trust. Change saturation and skills New tools demand new skills, from prompt design to exception handling analytics, so learning roadmaps must accompany every deployment.
49
| Professional in Payroll, Pensions and Reward |
Issue 116 | December 2025 - January 2026
Made with FlippingBook - Online magazine maker