Feature
It’s no longer shocking that human resources departments use artificial intelligence. In fact, according to Littler's 2018 Annual Employer Survey, 49 percent said they use AI and advanced data analytics for recruiting and hiring. They also deploy AI into HR-related activities such as:
- Making strategic and employee management decisions (31 percent).
- Analyzing workplace policies (24 percent).
- Automating certain tasks that were previously done by an employee (22 percent).
So, where can HR leaders expect to see significant gains in how AI will support HR-driven uses cases? The experts weigh in.
AI Risk of Bias in HR
There are some caveats to consider with AI-infused human resources initiatives. For starters, companies should keep a close eye on how these AI tools perform as they risk inadvertently introducing bias, according to Armen Berjikly, head of AI at Ultimate Software. Last year at this time, researchers from MIT and Stanford University found that three commercially released facial-analysis programs from major technology companies demonstrated both skin-type and gender biases. “The most significant risk of AI-enabled recruiting is that AI doesn’t take risks,” Berjikly said.
“An AI-enabled hiring process gets extremely good at finding the types of candidates you train it to find, which leaves out many potentially amazing applicants who don’t fit the proverbial mold.”
Related Article: 7 Ways Artificial Intelligence Is Reinventing Human Resources
Moving Forward with AI Despite Job-Loss Concerns
And surely, there are the natural worries about AI being so efficient for departments like HR that it will eliminate jobs. Their worries are validated, robots are already conducting job interviews. Rohit Chawla, co-founder of Bridging Gaps, said he strongly feels AI will take the load off at least 25 to 30 percent of mundane HR jobs. While that may produce fear of humans losing jobs, it’s not time for companies to back away from time-saving AI initiatives for HR. “HR should [embrace the technology] as currently a lot of customer-facing aspects are being taken care by AI. It’s high time HR takes up the challenge without any fear,” he added.
Chawla, who raised questions of using AI in HR scenarios, sees these common areas where AI is helping human resources:
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- Searching right-fit candidates especially for junior-level positions.
- Similarly conducting AI-based interviews both behavioral and functional.
- Sharing regret information to rejected candidates with an extent of sharing the reason, also not possible manually.
- Using chatbots to resolve employee queries.
Related Article: AI Adoption Is Increasing But Challenges Remain
Workforce Data Leads to Predictive Advantage
Where else is AI winning in HR? Jayson Saba, senior director of product marketing at Kronos, said AI advancements in HR are helping organizations leverage transactional workforce data to predict employee potential, fatigue, flight risk and even overall engagement. This enables more productive conversations to improve the employee experience, retention and performance. “It's now possible to leverage AI to build smarter, personalized schedules and to leverage AI to review time-off and shift-swap requests in real-time based on predetermined business rules,” he said. This empowers employees, especially those with front-line/hourly positions, to take more control of their work/life balance. “Using AI for these important but repetitive administrative requests also unburdens managers, allowing them to spend more time on the floor, working with customers and training teams,” Saba added.
Intelligent Shift-Swapping
Real-time analytics can show managers the impact that absences, open shifts and unplanned schedule changes will have on key performance indicators, allowing them to make more informed decisions that avoid issues before they arise. Similarly, Saba said, using an intelligent solution to automate shift-swapping without manager intervention reduces the number of last-minute call-outs, no-shows and vacant shifts and effectively removes the need to schedule additional labor to cover for anticipated absences. "The future of work in any industry is going to rely heavily on advances in AI for HR," Saba added, "but it's important to keep in mind that AI will never replace the manager. Instead, its true value is analyzing the massive amounts of workforce data to provide managers with better informed options to guide their decisions."
Related Article: AI Technology: The Driving Force Behind a Better Workforce
Continuous Learning in Recruiting
What is the impact of AI on the recruiting industry? Berjikly said AI addresses one of the biggest challenges of recruiting. Recruiters, he said, want to cast the widest possible net but without drowning in applicants. “The machine can do a spectacularly efficient job at finding interesting candidates from a large pool and continuously learn from a recruiter’s manual actions how to refine that profile,” Berjikly said. “So, recruiters can go broad with an opportunity and have some confidence that they are spending their valuable time looking at the right resumes.”
AI Won’t Fix it All
The new artificial environments in HR will not allow the job prospect a realistic preview of the work environment. Companies and new employees will still need to make an effort to make the relationship a winning one. Companies will need to dedicate more resources to recruitment marketing, showing prospects what their company is about and what it’s like to work there, Berjikly said. “For the organization, alternative-recruitment interviews — such as group assignments or code-a-thons with prospective employees — will provide a way to test for both hard and soft skills, while exposing the candidate to more typical work experiences,” he said.
Related Article: AI in the Workplace: We're Measuring the Wrong Things
Next Steps for AI in HR in 2019
What can we expect for AI and HR in 2019 and beyond? Berjikly predicts we will see the transformation of AI from marketing to practice. “What that really means is that recruiters will have access to more powerful and efficient candidate-screening tools, so they can focus on high-quality prospects while retaining the ability to examine a large pool of applicants,” he said. “These tools will deploy technologies such as natural language processing (NLP) and AI to go far beyond traditional resume parsing into identifying candidate fit through soft skills.”
