Business investment in AI reached $252.3 billion in 2024, per Stanford research, but these expenditures will produce no returns if workers reject the technology.
“When organizations don’t prepare their people to use AI reliably, employees won’t trust and adopt it,” says Ted F. Tschang, associate professor of strategic management at Singapore Management University.
This is the AI paradox facing businesses today: While business leaders are investing billions in AI, many frontline workers remain deeply skeptical for many reasons.
A Pew Research Center A survey released earlier this year found that nearly a third believe it will result in fewer long-term job opportunities for them. In the meantime, an investigation carried out by the University of Melbourne and KPMG A study of more than 48,000 people across 47 countries found that only 46% of respondents are willing to trust AI systems.
Closing this gap – getting workers to trust and adopt AI – has become one of HR’s most pressing challenges. Getting to grips with AI takes time and practice, but most organizations rarely spend the time on it, Tschang says.
Ted F. Tschang, associate professor of strategic management at Singapore Management University. Singapore Management University
“That’s why HR leaders need to create space for safe learning and experimentation with the uses and limitations of AI, starting with their own teams,” says Tschang.
To do this effectively, HR leaders must develop fluency in AI, which means they must understand the technology well enough to identify where it can solve real problems and guide their employees in its use. It’s easier said than done.
“A place of credibility”
Heather Conklin, CEO of Torch. Torch
The standard HR competency includes both operational tasks, such as recruiting, onboarding, benefits and compliance, as well as strategic tasks such as talent development and organizational change management. Simply put, this is not a department known for being particularly tech savvy.
But as the AI era dawns, that’s changing, says Heather Conklin, CEO of Torch, a business coaching firm that helps companies adapt to change, including AI adoption. “It’s forcing HR to reinvent itself,” she says. “And the ones I see succeeding are the ones who leave first.”
These teams treat their own services as testing grounds, experimenting with different tools and learning what works and what doesn’t, Conklin says. “They are learning about AI themselves, even if they are not technical,” she adds. “They can’t convey it to the entire company if they haven’t experienced it. They have to do it from a place of credibility.”
This credibility becomes commonplace when employees are distrustful. CHROs who appeal to people are leading with problems worth solving, says Dexter Bachelder, CEO of Propel People, an AI recruiting platform for the construction industry.
Dexter Bachelder, CEO of Propel People. Dexter Bachelder
“This isn’t about HR promoting AI. It’s about the questions that employees care about: How can AI take care of some of my paperwork so I can leave work earlier and go home to my family faster? How can I automate some of the manual tasks in my job that aren’t fun? How can I improve or speed up this process?” Bachelder said.
In other words, when workers see how AI makes their daily jobs easier, they are more likely to use it. “If you’re solving employee problems, you’re using technology for a purpose,” he says. “
Nothing drives trust and adoption faster than asking a colleague to explain it. When a foreman explains to another foreman how he uses a certain tool in the field: ‘Here’s how it works on our project, here’s how it might work on yours’ – that goes a long way,” he says. “It doesn’t come from IT, management or HR. It comes from a peer, and that’s what really drives adoption. »
“There is a real opportunity here”
Part of teaching HR to work with AI and gaining employee trust is to understand what is no longer working in the organization and what AI could do to fill those gaps.
HR managers have their own interest in this transformation. Many departments have long struggled with inadequate technology, and many tools and processes that HR has relied on for years weren’t designed for the moment, Bachelder says.
“To some extent, I don’t think HR has had much say in the technology they use, because a lot of the tools are tied to financial systems,” he says. “There’s a real opportunity here.”
Traditional learning management systems, for example, struggle to keep pace when skill requirements change more frequently than every few years. Annual engagement surveys do not capture employee sentiment quickly enough to respond to rapid organizational change.
Additionally, performance review cycles designed around setting annual goals are often disconnected from organizations where priorities change on a quarterly basis. And recruiting systems designed to screen for specific technical capabilities may lack candidates with the desired problem-solving skills needed to fill AI-related roles.
Of course, upgrading HR systems won’t entirely solve the trust problem. Employee fears about job security and algorithmic bias go beyond what any tool can solve. And HR leaders still need to answer employees’ questions about transparency, fairness, and who is responsible for AI decisions.
“It’s a challenge to do this right now,” says Conklin of Torch. “But if HR leaders fail to understand this, they will be left behind.”
