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The massive computing power of artificial intelligence (AI) offers many opportunities for businesses and their human-resources teams – from removing bias from the hiring process to recruiting top talent to identifying problems and conditions that cause an existing employee to quit.
"What AI is able to do is use pattern recognition to help with insights so we can make better decisions," Amy Wright, managing partner of talent and transformation at IBM Global Business Services, said during the November 4 panel, "New Use Cases of AI for HR," a part of the "HR Innovation and Prioritizing People" event presented by Workplace from Facebook and moderated by Insider's entrepreneurship editor Emily Canal. "It does not make decisions for us. It uses this massive computing power to use historical data."
Wright said during the session that technology can speed up hiring by identifying roadblocks and time gaps and assigning candidates to an individual to push them through the process. AI also identifies an individual's skill sets and enables organizations to identify what adjacent skills are needed for the roles they're trying to fill.
AI simulations of specific jobs let workers and employers "almost try before you buy new roles," said Kyle Jackson, CEO of the tech company Talespin, "The goal of using simulations is to give people a better view into those future roles or almost pre-qualify themselves for fit."
Removing bias in hiring is another use case for AI. Wright said the technology can recognize bias-based language "to identify where there potentially could be an issue with diversity, age, or ethnicity," so someone in HR can do something about it. "It doesn't stop bias on its own," she added.
AI also focuses on competency and skill level without knowing who an applicant is. Wright said her company works with Takeda Pharmaceutical Co., which deployed AI to establish competency-based interviews that remove information identifying the applicant.
With people quitting their jobs in record numbers, the technology can help identify employee skill gaps or whether specific roles are actually a good fit for someone, Jackson said.
"Once you have a skills profile, then you're able to identify the gap," Wright said. "It suggests education and experiences for each of our employees so that they can build their skills for the future as they have their current job."
AI offers "predictive attrition," enabling businesses to identify what factors lead employees to quit – for example, because their manager changed multiple times or they had a personal issue.
"It's not typically one factor but a combination of factors," Wright said. AI looks at historical data on why other employees have left or stayed with the company. "You're able to correlate that to your existing employees," she said.
To get started with AI, Wright suggested businesses identify a specific issue to focus on and involve experts to help them understand the insights.
"They'll be surprised by some of the insights," she said. "So it's really important to start with the business issue that if you use AI, it can then show how great it can be and how it can actually have business impact."