Jan 17, 2019
The technology sector is buzzing with both excitement and concern over artificial intelligence (AI) and the role it should play in our daily lives. But what exactly is AI, and how might it impact your finance and HR organizations in the (very near) future?
AI, a term coined only in the last century, describes the ability of machines to be creative and process abstract “ideas” much like humans do. There are several categories that fall under the umbrella of AI, but machine learning and predictive analytics are the most prevalent form in today’s workplace. Machine learning is a field of AI that uses statistical techniques to give computer systems the ability to "learn" from data, without being explicitly programmed. 1 Predictive analytics allows decision-makers to understand what their current data means for the future and act accordingly.
With advanced machine learning and predictive analytics tools at your fingertips, you can gain big-picture insights and visualize patterns and future trends derived from huge data sets within a matter of seconds. The significance of this technology is far-reaching. A task that usually takes a team of people many hours to complete – which includes reviewing, analyzing, drawing conclusions, and making future predictions from large amounts of financial data – will only take a few seconds for a computer equipped with AI.
This means that now, more than ever, it’s critical for organizations to strive for high data quality across their systems. For example, imagine changing the oil in your car and not noting the number of miles on your vehicle or resetting the number of miles on your trip meter. You realize this a couple months later and have no way of knowing what the correct number of miles should be to get another oil change. Your future success is limited by the lack of information retained, and you’ll either change the oil sooner than it needs to be done, or when it’s too late. It’s the same with your organization’s financial and HCM data.
AI is already here, and organizations with varied, disparate systems that have stale data risk missing out on the many benefits of this technology. Let’s examine two key areas in which AI is already starting to evolve finance and HR organizations.
1. Talent Management
The low-hanging fruit in any organization looking to leverage AI is talent management. There are numerous companies already integrating machine learning in their recruiting practices to more efficiently find and hire the best talent. The hope is that, on top of dramatically reducing the time spent pouring over stacks of resumes, the innate human bias that causes poor hiring choices and lack of diversity will be removed altogether from the process. 2
Another application is in the day-to-day interactions that HR representatives will have with employees. Chatbots that imitate human intelligence can ease the administrative burden on HR organizations: fielding repetitive questions from employees regarding benefits, or assisting new hires throughout the onboarding process. 3
An exciting possibility also exists in the ability of AI to help us better understand our talent data and make more informed decisions based on performance reviews. The opportunities are endless if your organization has accurate, complete, and consistent data ready to be analyzed by intelligent tools.
2. Reporting & Analytics
Few things are more critical to an organization than gaining insights from its data. How can leaders make better, smarter decisions about their organizations with the help of AI? While many organizations struggle to keep up with their spreadsheets and manual processes for gathering and analyzing data, those who utilize a unified, cloud-based system are already off to a good start.
Workday is focused on making sure its customers have the tools to be successful in the AI realm. The company has recently acquired several cutting-edge AI companies like Rallyteam, SkipFlag, and Stories.bi, which offer advanced methods for gathering insights from organizational data that were previously not possible. For example, Stories.bi allows for conversational responses to data inputs. Pete Schlampp, vice president, Workday Analytics, explains in a blog post:
“Stories.bi specializes in augmented analytics, a powerful approach that leverages machine learning and artificial intelligence technologies to automate analysis and deliver insights into what’s happening in a business. Stories.bi takes this a step further by identifying topline trends, issues, or opportunities in the organization, and then delivers personalized insights to a business user in a conversational, headline form such as ‘Actual shipments were $283,000 behind plan last quarter, 62% of which originate in Singapore.’ From there, a user can go deeper to easily understand the drivers behind the headline — such as how this compares to previous quarters or the reasons for the change — and understand which actions they should take next.”
AI, including machine learning and predictive analytics, is not a far-off, futuristic technology. It is here now and only getting sleeker and more usable with time. Your organization is far from the only one looking for a way to make more informed, efficient, and profitable business decisions. What’s clearer now, is that the ability to make these fully-informed decisions with actionable insights is dependent on an investment in systems that promote the maintenance of clean, accurate data.
As more organizations invest in AI, leaders need to focus on preparing their organizations to capitalize on the technologies that will soon be the new normal. Curious about how to start using AI within your Workday system? Want to understand how you can work AI into your transition to Workday? Click here to send in a request and our team would be happy to answer your questions.
Are you looking to embrace digital transformation in your organization? Learn more about how you can leverage technology to maximize finance & HR transformation success in our free eBook, “6 Value Drivers for Finance and HR Transformation Success”
1 Koza J.R., Bennett F.H., Andre D., Keane M.A. (1996) Automated Design of Both the Topology and Sizing of Analog Electrical Circuits Using Genetic Programming.
2, 3 Bersin, Josh. (2018) AI in HR: A Real Killer App.