Why AI adoption stalls without a culture-first HR strategy

She was also sceptical that classroom-style training changes behaviour on the job. “When people get back onto their jobs, onto the tools, they’ve probably only got about 10 per cent retention of what they learned in an academy or an online course or like a face to face training,” Colussi said.

Instead, she pointed to organisations building learning directly into daily workflows – for instance, giving a call centre worker AI-generated prompts to choose between in real time, with the system learning from each choice made.

Rather than layering AI on top of existing roles, Colussi argued the more effective approach is to pull jobs apart and rebuild them from scratch. “How do we decompose the jobs and then rebuild them with AI in the loop and human in the lead, and make sure that we’re getting the best out of the employees and the best out of our tech investment as well,” said Colussi.

Why visible experimentation from leaders builds trust

At Lucid Software, Stallings described how openness from senior leadership – rather than a formal mandate – drove grassroots adoption inside his own team. “I would say that the biggest goof-off with AI has been our boss. I mean, he tries everything,” he said of the company’s chief marketing officer. “He’s sharing his experiments and he’s talking about it frequently with everyone, and he’s encouraging us to try things out as well.”

That openness changed how comfortable employees felt experimenting on work time. “At first when we had access to the tools, it felt a little bit like cheating to check it out,” Stallings said. “But then he comes in and he’s like, here’s what AI did for me this weekend and look at these results. I liked this, I didn’t like this, here’s the things I’ve learned.”