Artificial intelligence (AI) has become ubiquitous in our personal lives. It facilitates our shopping, automates household chores by vacuuming our floors, arranges rides for us, and even ensures that we smile in our photos. However, despite the buzz surrounding AI, companies have been cautious about leveraging the AI already built into their human capital management (HCM) and workforce management (WFM) systems. According to a recent UKG study, just 42% of employees globally say they’re using AI-powered devices in their day-to-day work. Why is this the case and what can be done to improve adoption?
What’s Holding Back AI Adoption?
Recently, I had an opportunity to meet with several HR, labor operations, and IT professionals to discuss challenges with AI adoption — people who use their organizations’ HCM and/or WFM systems every day. While I heard many reasons why they are not using AI, three reasons stood out:
- Lack of understanding about AI. People understand how their systems work today. They know the ins and outs of their algorithm and rulesets that create schedules, recruit new candidates, flag payroll exceptions, etc. AI is new. Many do not understand how AI works, how their companies’ and employees’ data will be used, how to evaluate AI’s performance, or even how to get started with AI.
- Skepticism about the return on investment (ROI) of AI. The professionals I spoke with questioned whether AI can live up to the hype that media and their vendors have given it.
- Lack of internal guidance on AI use. Many lack clarity as to how AI is allowed to be used in their organizations or if it can be used at all. Without an acceptable-use policy, it is easier to do nothing than to try and fight for something that you don’t understand and an ROI that you’re unsure about.
When competing priorities are coupled with one or more of these items, it is little wonder why AI quickly falls to the bottom of the to-do list.
Solve Real Issues with AI — Now
It is ironic that competing priorities can delay AI adoption when AI can solve some of the most pressing issues HR and WFM professionals face. Let’s look at two examples:
- Liberate valuable time for strategic initiatives. HR practitioners often find themselves repeatedly answering the same questions, which hinders their ability to engage in strategic work. By leveraging an AI-powered chatbot, routine inquiries receive prompt responses, while complex issues can be seamlessly escalated to human experts. This empowers HR team members to focus on impactful tasks that enhance business outcomes, as well as tackle more engaging work.
- Enhance scheduling accuracy through improved forecasts. WFM professionals understand that effective schedules and adherence to payroll budgets hinge on precise labor predictions. Hours are dedicated to meticulously refining these forecasts. Leveraging machine learning consistently yields forecasts that surpass traditional methods by 5% to 25% in accuracy, all while requiring less effort.
Beyond these examples, there are many ways AI can be used to overcome the challenges preventing adoption and delivery value today.
Easy Steps to Get Started with AI
Still, the journey toward successful AI adoption requires organizations navigate a path that balances innovation, risk, and tangible benefits. Let’s explore three essential steps that pave the way for leveraging AI effectively in HCM and WFM systems and processes.
First, engage experts. Leverage your HCM and WFM vendors, along with trusted advisors such as consultants, to gain insights into AI within your existing systems. Understand how AI utilizes your data, identify low-hanging opportunities, and receive clear guidance on initiating the process. These experts can also play a crucial role in educating your leadership, ensuring everyone is well informed about the risks and benefits of AI.
Second, start small. Begin with targeted initiatives, rather than a large-scale rollout. Focus on ways the HR or WFM teams can benefit from using AI at the corporate office or among a subset of employees. A gradual approach not only addresses skepticism about ROI but also mitigates risk while fostering education and awareness.
Finally, test and learn. Rather than expecting AI to function flawlessly right from the start, begin by experimenting in a controlled sandbox environment. Pilot AI in production and roll it out in manageable phases. Evaluate the results along the way. This deliberate, iterative approach not only facilitates team learning but also promotes agility, allowing your team to verify that AI indeed delivers a tangible ROI.
Following these three steps will help your company — and your people — build confidence in AI, overcome obstacles to adopting AI, and unlock the transformative potential of AI in HCM and WFM.
