For decades, the talent conversation between HR leadership and a hiring manager followed a familiar script. But Ciara Harrington, chief people officer at Skillsoft, says that the script is being rewritten because the nature of work itself is changing in ways that require a different starting point.
“You’re no longer thinking, I’ve got work to get done, who’s the right person to do it?” Harrington says. “You’re thinking, what’s the best method to get this work done? Is there a system I can automate it in? Can an agent do it? Do I need a human? Or is it some combination of the above?”
That reframing is central to how Harrington is approaching talent strategy at Skillsoft, a learning technology company whose product is in the midst of an AI-driven transformation. It puts her in the unusual position of navigating AI workforce questions both as an internal people leader and as someone whose company helps other organizations do the same.
The conventional talent pipeline framework asks HR to decide which skills to hire externally versus develop internally. Harrington says that calculus still applies, but AI has made it more urgent and more complex. “There is clearly a massive shortage of AI-specific skills,” she says. “We don’t have millions of people who just did four-year bachelor’s degrees in AI. It just doesn’t exist.”
For companies whose core product needs to become AI-native, that shortage is acute. Firms cannot build an AI-driven technology, Harrington says, without people who are deeply skilled in it. But for corporate services functions and organizations whose products are less technically driven, the approach looks different.
“I’m not out there looking for one AI person to turn [the company] into an AI-forward organization,” she says. “I’m taking the technical people within my organization, trying to get them thinking more AI-forward and trying to partner closely with our internal team to have them upskill my team.”
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A gap HR has seen before
Harrington draws a useful parallel to when companies first integrated systems like SAP and PeopleSoft and the two groups existed in their own silos. There were business experts on the HR and finance side and IT coders on the other. Eventually, what emerged was a new kind of role, someone who understood the technology and the business well enough to link them together.
“I think it’s no different than that era right now,” Harrington says. “We’re still figuring out how to bridge that gap between a really super AI expert and the reality of a corporate business environment.”
That role requires curiosity, according to Harrington. This means not accepting the first response or solution, while also not locking into the way things have always been framed. “With AI, you can’t just accept the first answer,” she says. “You’ve got to think bigger and broader and keep asking.”
Don’t wait for perfect conditions
One pattern Harrington sees frequently is organizations stalling on AI adoption because their data or processes aren’t in order. “By the time you’re doing that, everyone else is gone,” she says. Instead, she argues, AI can be part of the cleanup, but not the reward at the end of it.
At Skillsoft, her team built an AI-powered system to handle employee policy questions. Instead of routing a query about a day off through a human agent in another time zone, the system answers it directly. But the less obvious value is what happens when the system reveals inconsistencies in company materials. “If AI finds three answers, it sends them to a human,” Harrington says. “It says, I just found three documents. One references it as a day off, one as a half day and one doesn’t reference it at all. What’s the answer?”
That flag becomes a data-cleaning mechanism. A human reviews, resolves and removes the outdated document, while the system learns. “My AI agent will not make the same mistake twice,” Harrington says.
HR’s leadership pivot
None of this leaves HR untouched, and Harrington is candid that the profession built its identity around human skills such as coaching, influence and communication. The expectation that HR leaders now need technical fluency is new, and for some people, it’s uncomfortable. She does not dismiss that tension, acknowledging that different organizations are moving at different speeds, and some HR professionals will choose more human-centered environments, at least for now. But for HR leaders at technology-driven companies, she says expectations are already changing.
Specifically, the HR business partner role has to expand. Supporting a hiring conversation now means helping a manager think through whether a hire is even the right answer and, if so, what kind of person can operate in an environment where their work sits alongside agents and automated systems. “We need to be prepared as HR, and then partner with IT to be able to work with managers and help direct them to answer those questions,” Harrington says. “That’s the big shift.”
She is also watching how organizational structures will adapt. The swim lanes that have defined corporate functions start to look arbitrary when an AI system can field all of them from one place. “They’re all just employee questions at the end of the day,” she says. “Shouldn’t this be a centralized area?”
Harrington’s consistent advice to her own team and to others navigating this moment is to start moving. “If you try something out and it doesn’t work, that’s still something we’ve learned,” she says. “Always be curious. Always be trying. Always be pushing the boundaries.”
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