According to recent media reports, some companies that deployed AI to replace job roles like customer service have been on a rehiring spree after realizing chatbot technologies came up short. In the HR tech space, there’s been less focus on using AI to replace people and more focus on shifting from experimenting with AI to delivering demonstrable returns on investment in the technology.
That’s the way it should be. AI is an exciting technology that can reduce workloads and drive efficiency, but human oversight remains vitally important. This is especially true in the HR sector, as even a 1% error can lead to compliance risk. As even its most passionate adopters know, AI isn’t perfect, and there is no room for error in handling highly sensitive employee health and compensation data.
HR is emerging as a powerful proving ground for AI applications, due to the sensitivity and quantity of data and the need for 100% accuracy. Here’s a look at some of the challenges HR tech leaders face when deploying AI and five tips they have used to successfully roll out AI tools in the human resources context.
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1. Focus on data hygiene first: As every HR tech professional knows, AI is only as smart as the data it consumes, so a thorough audit of internal data is needed before any AI deployment begins. Prior to taking the AI plunge, it’s critical to make sure the dataset is complete, free of biases and well structured.
Excellent data governance is a must in this situation and setting the standards before AI deployment will ensure that AI output is as accurate as possible. That’s important in any business context, but especially in HR.
2. Train AI on internal data: AI trained on publicly available data can be useful as a starting point for research and to expedite routine office tasks that take time away from employees. But to generate maximum value in the HR context, it’s important to select AI tools that can access and learn from data in the company’s human resources information system.
This approach will require working with vendors or in-house talent with specific expertise on the company’s HRIS ecosystem. It will also require strong guardrails to ensure sensitive internal data isn’t exposed in a public cloud.
3. Start small: Being overly ambitious and attempting to overhaul the entire talent management system in a short timeframe can backfire. HR tech leaders are better served by identifying low-risk, high-friction tasks and automating them before moving on to more complex functions.
Tasks like interview scheduling, policy writing and FAQs can be a great place to start. While it’s difficult for humans to navigate a huge information library to find an answer to a specific question, an AI prompt can return answers from an enormous knowledgebase instantaneously and start delivering value quickly.
4. Keep humans in HR workflow loops: AI is a transformative technology and is evolving by leaps and bounds, but as HR tech leaders know, human oversight is still absolutely necessary. Otherwise, AI can unintentionally inherit and scale biases, leaving the company and its leaders at risk both reputationally and financially.
For example, large corporations have already had to pay hefty settlements and penalties due to class-action lawsuits holding businesses liable for using recruiting or hiring engines that disproportionately disqualified older applicants and women. AI can efficiently analyze, summarize, audit or recommend a course of action, but ultimately, the final call should be left to a human.
5. Be transparent with employees: Even employees who are excited about using AI are also anxious about how it might affect their jobs. That’s understandable since AI is a black box, a complex system that most people don’t fully understand. HR tech leaders can assuage employees’ fears by explaining how AI can help them do their jobs and augment their skills, rather than replacing them.
The best approach is to be specific about how AI will help with certain tasks. For example, explaining to HR and IT staff how using AI to vet data before it’s loaded into a third-party system can help people do more implementations. Armed with this knowledge, employees will feel more secure about their own role.
Executives are eager to move past all the AI hype and start seeing bottom-line results. The human resources space is demonstrating that it is possible for AI to help HR professionals accelerate hiring, streamline workflows and handle essential tasks like payroll and benefits administration more efficiently.
However, patience and careful planning are the key to successful deployment. As recent high-profile studies have found, many companies that have made huge investments in AI don’t yet see the returns they expect. That’s because they tend to view AI as a magic bullet rather than a tool that requires careful process redesign and organizational adjustments.
It’s important to keep in mind that an AI project will require other systems, processes and organizational structures to be redefined to work effectively. HR tech leaders who embrace those changes first will be in a better position to move past the initial AI hype cycle and start delivering real value.
About Veritas Prime
Veritas Prime, is a consulting firm specializing in Human Experience Management (HXM) technology, particularly SAP SuccessFactors software, and a range of services beyond Human Capital Management (HCM) implementations.
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