Lack of training, guidance is significantly slowing AI adoption in the workplace
A staggering 82% of workers say their organizations have still not provided training for employees on using generative AI.
That’s from Asana’s State of AI at Work report, done in partnership with Anthropic, which surveyed nearly 5,000 knowledge workers in the U.S. and UK.
The boom of GenAI has been in part thanks to early adopters, those who were excited to try new technologies that would ultimately allow them to be more productive and efficient by delegating mundane tasks or brainstorming new ideas with the bots. WorkLife reported last year that C-suite execs were all-in on generative AI and people generally are less afraid and instead more hungry to reskill in AI.
But, more recent reports and workplace experts say that AI adoption is starting to slow down with early experimenters in the rearview, requiring closer detail around everything from choosing what GenAI tools to use to ensuring AI usage is being tracked closely for the more nervous group of workers.
Employers need to pivot to encourage late adopters
“As humans, we’re naturally inclined to solve problems through addition,” said Dr. Rebecca Hinds, head of Asana’s Work Innovation Lab. “Whether that’s meetings, technology, people, or money, the natural response is to throw more at it to solve a problem. I think we’re very much seeing this with AI.”
Those early adopters didn’t actually need any encouragement from their employers or leaders to try out the new technology. These folks were likely to try it either way, even without the proper guidance. In fact, Adobe’s Age of Generative AI report, which surveyed 3,000 Americans, found of the 53% of people who have used GenAI, most use it in their personal lives (81%), followed by work at just 30%.
“You have the new adopters, then you have people who are kind of jumping on board, and then you have the laggards who are kind of the last ones to try it out,” said Vivek Pandya, senior digital insights manager at Adobe.
That latter categories of individuals is where employers are starting to face challenges when it comes to AI adoption. Asana’s recent report found that 33% of employees are still concerned that generative AI will replace human workers, despite experts myth-busting this frequently. 26% are concerned about being perceived as lazy by their colleagues for using the technology and 23% are concerned about being labeled as frauds for using it.
Without direction from an employer, this group of individuals may take significantly longer to consider adopting GenAI tools.
‘A multi-faceted strategy‘
“You need to have a multi-faceted strategy,” said Hinds. “You need to approach those individuals who are more resistant and hesitant and more fearful of the technology differently than you approach the individuals that are more enthusiastic and inclined to personally experiment with the technology.”
In Asana’s report, it outlines the 5 C’s, a suggestion to increase adoption: comprehension (formal education to boost AI literacy), concerns (not investing in the right tools), collaboration (seeing how others are using AI), context (around AI deployment), and calibration (measuring AI’s value).
A big part of that is showing how impactful the technology has already been for some people. Asana’s report also found that those using AI more often are seeing greater productivity gains, with 69% of workers using GenAI reporting so. Dayforce’s 2024 Pulse of Talent survey also found that of the nearly 9,000 people surveyed, 69% say new tech investments have increased their productivity in the past year.
“That concept of one and done to make work life better and not worry about the mundane really has a lot of credibility when you hear about it in the realm of AI today,” said David Lloyd, chief AI officer at Dayforce.
Early signs of readiness
And some who might not have adopted GenAI entirely yet are beginning to show signs of readiness, which will require employers to encourage them the rest of the way with proper policies. That same Dayforce study found that 80% of surveyed employees were at least slightly interested in their employer using AI to recommend skills development opportunities. And 50% said they think that AI can improve their productivity at work.
“The challenge for many organizations that we see today is the ‘any road will get you there,’” said Lloyd. “You have a lot of experimentation, which I think is important, but what’s the guardrails under which that experimentation is occurring?”
Asana’s report fount than more than half (56%) of workers have taken AI learning into their own hands through personal experimentation. One thing that will help employees go from thinking AI can help to knowing AI can help is if an employer focuses providing those guardrails around experimentation and also setting KPIs around AI usage.
“A big aspect that’s often overlooked is understanding at the onset how you’re going to measure success and develop KPIs and metrics,” said Hinds. “If you commit to measuring employee sentiment around the technology, that’s more than the vast majority of organizations are doing right now.”
Employers need to start somewhere
But even that might not go far enough. Atlassian’s latest State of Teams Report found that despite 63% of knowledge workers and 79% of executives acknowledging the importance of AI, only 50% use it weekly. Jamil Valliani, Atlassian’s head of AI product, says this doesn’t surprise him at all, largely because of that lingering feeling of leaping into the unknown of something that might just still be a buzzword to a lot of employees.
“It’s just going to take some time and experience where people see AI as a compliment to their jobs, helping them everyday in their work, removing the mundane tasks to build that trust and remove that nervousness,” said Valliani
The education aspect that Hinds’ touched on through Asana’s 5C’s is one that Valliani agrees is extremely important for this group of individuals.
“Approaching AI without a coherent strategy is like navigating without a map,” said Valliani. “A lot of organizations don’t have that coherent strategy yet. To effectively implement AI and drive adoption across the board, organizations can develop a clear strategic plan that aligns AI initiatives with broader business objectives.”
At Atlassian, they have early adopter teams, teams that might stand the most to benefit and have shown the most openness. “They start learning and that adoption can spread like wildfire,” said Valliani.
“It’s important for every organization to start trying,” said Valliani.