The capabilities and usability of AI has developed dramatically over the past few years: today it helps us plan our schedules, calculate bills, compile shopping lists, heat our homes, and more. The technology is also becoming ubiquitous – with Amazon estimated to have its ‘Echo’ device in over 10 million homes, and Google’s ‘Assistant’ app now installed on over 2 billion devices.
HR & Payroll Applications
With such innovation and potential at our fingertips, it’s easy to see why business across the world are starting to take note of the commercial capabilities of AI. HR and payroll processing are two of the processes which might benefit most from the automated, algorithmic possibilities of AI tech – since both involve the coordination and handling of large amounts of data, and the need to navigate a spectrum of complicated compliance issues.
The proximity and interconnectivity of payroll and HR means that the role AI plays within both involves significant crossover. It’s clear that we’re in the midst of a period of heavy investment and development in AI and machine learning that will play a key role in shaping the future of the accounting industry.
Employee assessment
What’s less clear is what the future for payroll looks like and if that future involves AI and machine learning. Below are just some of the ways that we’ll start seeing machine learning and AI change payroll in the future.
AI can be used to identify and assess characteristics and trends across an entire employee population, or narrow that focus to individual employees. From an HR perspective, this has obvious benefits: AI screening can quickly identify productivity issues or skill shortages, without the uncertainty and bias of human subjectivity. In payroll contexts, AI can be used to classify employees quickly and efficiently, and ensure the correct tax bands are assigned.
Smarter Rostering
Through the use of machine learning and AI, we’ll soon be able to automatically build rosters that will take into account historical work patterns, stress profiles, employee skills and performance, leave and availability records, sales data and hundreds of other data points or build rosters that are optimised for cost and performance. Through machine learning, rostering will be able to take in external inputs like weather, sporting events or concerts, public and school holidays or other seasonal variations and predict the staffing requirements and build the roster accordingly.
Streamlined data management
One of the most time-consuming aspects of payroll is managing all the data that is input before you can even get to the point of processing a pay. Timesheets, leave requests, expense claims and payroll changes all need to be reviewed and approved by a manager before being processed in a payroll. Not only is this time consuming, but manual intervention means that there is room for error in the processes. Through the use of machine learning, the approval process could be eliminated, with only exceptions being surfaced to managers for approval, saving countless hours in unnecessary manual approvals.
Continuous compliance
The payroll landscape is continually changing and it’s impossible for business owners to be expected to run their businesses and also be on top of payroll legislation, the interpretations of those legislations and the impact on their business. Using AI, payroll systems will be able to track legislative changes and analyse the impact of those changes on a business’ payroll, notifying business owners and payroll admins of potential issues.
Deep learning
Beyond the short-term collection and interpretation of HR and payroll data, AI brings a deeper level of analysis to both processes over the long term. ‘Deep learning’ is the identification of trends and inconsistencies within large amounts of data over long periods of time – which may be difficult or too subtle to spot from a restricted, real-time, human perspective. Through deep-level analysis of HR and payroll data, AI can be used predict future trends – and positively transform those systems in ways which might seem initially surprising to human administrators.
Payroll is one of the largest expenses for business and can equate to as much as 70 per cent of total business costs. The objective for payroll teams managing this cost is perceived as a relatively simple one – pay your people correctly, at the right time and in the right way.
So the question is, will we see machines replace people, as businesses look to cut costs and implement smart AI payroll technologies?
Why people still matter
For the foreseeable future, humans will still be the decision makers, with technology providing support through insight and information. AI technology, as it stands today, is not ready to deal with highly dynamic environments. Automation, for instance, ensures workers are paid on a schedule, but there is not likely an AI function that can accommodate for spontaneous adjustments, like a payment outside of a salary cycle yet.
And this is crucial. With AI still being some years away – and, we are talking over 10 years from now – you’ll need to know what parts of payroll are ready to take the technological leap and which ones still require human interaction. Much like automation before it, it will be the incremental AI updates that will eventually change the industry as a whole.
As much as AI is set to change the world as we know it, it is still a while away from having a significant impact. As such, payroll will still require a human touch in the years ahead.
Additionally, it’s important for businesses not to just implement AI for AI’s sake. Although the hype and benefits make it sound like the silver bullet to help solve your problems, it is important to take a measured approach. The technology is still in its infancy and a long way off from replacing humans.
For payroll managers and businesses looking to take advantage of AI, it is crucial to build it up gradually. That means learning what tasks AI could help us to achieve in the future and understanding where, as a payroll professional, we can add further value to the business.