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Companies spend vast amounts of time, energy, and money training their employees to handle AI tools, but recent reports show that these efforts are often ineffective or fail completely.
In its 2026 AI Readiness Gap report, Docebo found that even though AI literacy and applied skills are top priorities for both employees and learning leaders over the next 12 to 18 months, 85% of employees say they are unable to apply the AI training they received to their day-to-day work.
Docebo, a learning platform company, also found that 56% of employees are overwhelmed with so-called “pre-AI” manual tasks and don’t have time to learn tools designed to save them time. Additionally, 78% of respondents said learning happens outside of the tools they actually use, like Slack or Salesforce. This means that AI training is more of a distraction than a driver of return on investment.
Here’s what to do next if you think you’re not ready for AI, according to experts.
Setting parameters and guidelines for AI usage
First, companies should have a clearly written AI policy that outlines what tools are allowed and how they can be used. Without a policy, employees may end up experimenting on their own, Melissa Stout, vice president of operations at professional services firm Milestone, told HR Dive.
This type of experimental use is not captured by typical AI adoption tracking, and in highly regulated industries such as finance and healthcare, employees may be inputting customers’ personally identifying information into public AI tools.
But beyond avoiding compliance disasters, Stout said having policies in place that include guidelines on how to use AI can help employees adopt it. “If there’s no guidance or collaboration around it, the moment it feels too difficult or the answer is wrong, people will revert to their default state,” she continued.
Providing a place for employees to collaborate and discuss tough problems will also help them embrace AI in a way that actually improves productivity. For example, Milestone has a Slack channel for AI wins. Having a space like this to talk about AI “demystifies AI and shows us that it’s okay to talk about AI,” Stout said.
Addressing employee AI concerns and disparities in adoption rates
AI-enabled training may also assume that all employees have the same basic knowledge, understanding, and acceptance of AI. As with any new technology, people from different demographics and backgrounds will have different basic expectations when asked to use it, Stout said.
Employees may read news about AI-induced layoffs and worry that they are being told to train on technology that will eventually replace AI. They may also be concerned about the technology’s impact on the environment, Stout said. As a result, employee comfort levels with AI implementation vary. This means some people may end up on teams that don’t use AI or are stuck due to differences in adoption rates.
Rema Loras, founder and CEO of team-building platform Grozaic, says the friction isn’t the employees’ fault. Instead, she said, poor change management creates a disconnect between “organizations that are making very large investments and want things to move very quickly” and the people who are expected to use them. “It doesn’t flow downstream, and people don’t necessarily know what they’re doing.”
Build a timeline rather than a one-off approach
Teams tasked with implementing AI can be caught between executives who want a quick ROI on the money spent on AI tools and employees who are told they need to change the way they work. right now Otherwise, they will be shown the door.
“We can’t just send every employee to a one-hour AI training course,” said Megan Bean Torres, vice president of employee success at Docebo. Businesses may also be overestimated by the promise of AI and have unrealistic expectations for adoption and productivity.
Teams need to ask questions about the use of AI, she said.
“What is the original problem that AI is solving?” she said. “Let’s stop putting AI in everything.”
Rather than a one-shot approach, learning and development professionals can create a roadmap for a “learning journey” and explain “what each step of that journey is,” she said. If you’re having trouble navigating AI, you need to start with an overview of AI, including what “A” and “I” stand for. “As you start digging deeper, you start to consider the pain points of business leaders and add personalization by department.”
