There’s no doubt about it: When it comes to the workplace, AI is here to stay. But ever-increasing adoption of the technology isn’t necessarily a done deal. That’s because people still have a number of concerns about it. To extract maximum business value from this technology, organizations have to understand what’s stopping people from fully embracing AI, and then devise smart strategies for overcoming those barriers.
Our study findings indicate that the biggest barriers to adoption and use of AI in the workplace are a preference for human interaction and concerns about security and privacy. Here, we take a closer look at each of these.
When we drilled down on security, 71% of respondents said they were “at least sometimes concerned” that there will be more data-security breaches at their workplace owing to use of AI, and 38% said they were “very concerned” or “always concerned” about such breaches. Security concerns were called out as particularly high barriers to AI adoption by respondents in China (48%) and India (44%), compared with the U.S. and Brazil (both at 30%) and the UK (26%).
Such concern isn’t surprising, particularly given that the collection of data on employees and customers tops the list of ways in which AI is being used in organizations. Nevertheless, these worries can erode interest in and willingness to use AI tools if organizations neglect to address them.
In our respondent pool overall, 30% said that concerns about privacy prevent them from using AI at work. Such worries are particularly high in India and China (46% and 44%, respectively), compared with Japan (29%) and the UK (24%).
The majority of the study participants (70%) expressed at least some degree of worry about the use of AI to collect data on their work activities, with 35% saying they’re “very concerned” or “always concerned” about this particular use of the technology. They pointed out that if they could be assured of greater data security and privacy, they’d feel more comfortable trusting a recommendation from AI. Respect for personal data is clearly a top priority, with 80% of our entire respondent pool saying their company should ask for permission before gathering data on them while using AI technology.
The majority (76%) of our study participants overall (and 81% of the HR leaders in our respondent pool) said they find it challenging to keep up with the pace of technological changes at work. So it’s not surprising that the employees we surveyed want a simplified experience with AI. Some (34%) identified a better user interface as a great way to get them to use AI more. Others (30%) said they wanted best-practice training in AI. And still others (30%) expressed a desire for an experience that’s personalized to their behavior.
Interest in a simplified and more personalized experience with AI is particularly noticeable among the younger generations. For instance:
38% of the millennials, 33% of the Generation X respondents, and 31% of Generation Z respondents emphasized the importance of a better user interface, versus 26% of the baby boomers.
Regarding best-practice training in AI, interest was especially high among millennials (33%) and Generation Z’ers (31%), with Generation X’ers coming in at a close 29% but baby boomers at 20%.
Generation Z’ers and millennials showed the highest interest in AI user experiences tailored to their behavior (each at 33%), while members of Generation X came in at 27% on this, and the baby boomers at just 19%.
This year’s survey data shows that China and India, followed by the UAE and Brazil, are leading the way with AI adoption, compared with the other countries represented in the study—the US, UK, France, Australia/NZ, Singapore, and Japan. For instance, respondents from the four frontrunner countries report the highest adoption of AI across a varied list of use cases.
Perhaps not surprisingly, respondents from the countries reporting the most progress with adoption of AI also say they are the most excited and positive about the opportunities AI presents.
*Percentages have been rounded to the nearest whole number.