After attending QuickBooks Connect, Sage Summit and Xerocon this year, 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.
What’s less clear is what the future for payroll looks like and if that future involves AI and machine learning. I’ve been thinking about this for a few years now and once you scratch the surface, it’s hard to see any part of the payroll process that couldn’t be transformed by machine learning and AI. Below are just some of the ways that we’ll start seeing machine learning and AI change payroll in the future.
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.
In addition, if the system notices that you don’t have enough staff to cover a busy weekend or seasonal period, it could communicate with your HR system to let you know that you need to start hiring new staff.
Imagine operating a retail store over Christmas and three months out, your rostering system analyses your staff leave patterns, estimated requirements and predicted sales based on a combination historical sales data and industry forecasts for the current year and automatically suggests that you should hire and train three new staff members as you’ll be short for the four weeks leading up to Christmas. This is just one of the many scenarios that machine learning will drastically improve.
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.
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.
The most exciting thing, is that these features are closer than you think – we’re already looking at how we can leverage the power of AI and machine learning within KeyPay.
If you’ve got any thoughts or ideas on how AI and machine learning could be used to change the way payroll is processed, we’d love to hear from you in the comments or via firstname.lastname@example.org.