BioSpace spoke to talent acquisition leaders about how they think artificial intelligence will shape the future of their function.

How life sciences organizations can apply artificial intelligence (AI) to various disciplines and processes has been a key topic for years. Talent acquisition is no exception. The subject has appeared on the agenda at LEAP TA and LEAP HR, events designed for talent acquisition and human resources professionals in the industry, as businesses consider how to optimize workforce management and the opportunities and challenges AI presents.

Many life sciences organizations have faced change in recent years in response to a tough funding environment that has required restructuring, budget constraints and rapidly evolving skill gaps. How tech stacks can improve business practices and make talent acquisition more efficient has become an important discussion point particularly because of these challenges. According to a Gallup study on AI adoption, 93% of Fortune 500 chief human resources officers say their organization has begun using AI tools and technologies to improve business practices.

To explore this important and timely topic, BioSpace spoke to talent acquisition leaders for their predictions on how AI will impact the future of talent acquisition practices.

Applications in Sourcing, Candidate Engagement

Ryan Maglione, senior vice president, talent at Syneos Health, has spent a lot of time over the past year considering AI, its implications and its potential for the business.

“It’s going to allow us to do better quality work,” he said, explaining how AI will improve automation as it is applied to various aspects of talent acquisition, including sourcing, marketing and candidate engagement, in the next year or so. “We have a lot of automation built into some of our CRM tools and our ATS. And the reality is, we’re not using the automation as well as we could, but I think AI might help us to use that automation better.”

It takes work to prepare for AI, Maglione emphasized. How AI impacts talent acquisition and organizations depends on the risk tolerance and how firmly users embrace it.

Dante Maiden, executive director of talent acquisition sourcing and engagement at Bristol Myers Squibb, expressed a similar sentiment.

“The one thing I think is most important is making sure that your agility and rigor around implementing the technology is matched with your plan for learning and training and capability build for the team that’s using it,” she said.

Maiden and her team are using data-generated insights, and she thinks this is where AI will evolve and be applied over the next year at BMS.

“If I had to think about the one-year plan for AI, it’ll probably be to continue to drive insights,” she said. “I think it’ll become commonplace in terms of using AI for workforce insights, thinking a little bit about talent planning, demand planning.”

Maiden believes that in five years, AI will support a broader framework for talent assessment in areas including executive recruiting, hiring practices, internal mobility and succession planning. Maiden said peers should think about all the ways they could use predictive support and insights in talent acquisition, such as implementation of a skills hierarchy.

Maglione agreed that AI will support assessment for skills, motivational fit or cultural fit—though he believes that compliance and bias may be a hurdle for meaningful AI assessments that can identify top talent.

“When you say five years out, I feel like that’s the hope,” he said.

Maglione also thinks longer-term AI will provide significant administrative efficiencies—such as for scheduling—and improved candidate communication. He noted that the main reason candidates do not feel their recruitment experience is positive is due to the timeliness or thoroughness of communication.

“If we get AI right, I think it can serve as a true extension of our team,” Maglione said.

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