Article Insight Survey: Quantifying Employee Attitudes Toward AI-Powered Devices

To answer this question, Insight gathered data from 604 full-time employees across three generation categories. Most employees shared feelings of curiosity and excitement about AI-powered devices in the workplace — even as concerns about security and privacy remain high.

AI and generative AI solutions cover a broad range of unique categories. This survey focuses on AI-powered devices — i.e., electronic gadgets or machines built with artificial intelligence to perform tasks that usually require human intelligence — that will be widely available to businesses within the next 5 years.

The results tell a compelling story about an evolving workplace defined by both readiness and reticence as different generations learn to embrace one of the most transformative technologies of any generation.

As AI integration transitions from conceptual to practical, employees are adapting to generative AI in the workplace. Their feelings reflect a balanced perspective: eager to explore AI’s potential while being cautious of the challenges ahead.

• Curiosity leads (41%) as employees realize the potential of AI-powered devices for their daily tasks.
• Caution (35%) and excitement (31%) are also prevalent and show a balanced view of the significant opportunities AI could bring to the workplace.
• Sentiments of hopefulness about AI’s potential (31%) are mixed with a sense of skepticism (26%) and uncertainty (25%).
• Fewer employees report feeling anxious (13%), fearful (11%), confused (5%), or overwhelmed (3%) by generative AI at work.
• Gen Z are the most curious (50%) and excited (37%) to use generative AI at work, while the older generation of Gen X/Boomers/Seniors express the most caution (40%) and skepticism (32%).

As expected of watershed moments, employees believe implementing AI-powered devices will improve their daily work life but express concerns over whether this will result in job insecurity.

• Most employees (75%) believe AI-powered devices will help their employer stay competitive.
• A similar number (73%) expect them to improve their own productivity in the workplace.
• Two out of three (64%) believe these devices will change the critical skills required for their jobs. In the midpoint of their career, nearly three out of four (72%) Millennials see a greater need to adapt than their younger Gen Z (63%) and older Gen X/Boomer/Senior (56%) peers.
• Almost half (45%) worry that AI will eventually make what they do less relevant to their employer. Gen Z (46%) and Millennials (55%) are more apt to believe this compared to Gen X/Boomers (33%).

Although personal sentiments are net positive, the majority of employees (94%) have at least one large-scale concern about using AI-powered devices.

• Security risks (52%) and privacy violations (48%) top the list of macro concerns. Older workers (Gen X/Boomers/Seniors) express the most concern for these areas (security, 62%; privacy, 55%).
• Fears that AI may result in job loss are substantiated by the significant number of workers (43%) who worry their roles may become obsolete.
• Just as they were more inclined to believe skillsets would need to change, Millennials (49%) also feel the most anxiety about how AI will replace jobs.
• Other statistically significant concerns include an over-reliance on AI (39%), the potential for data bias or inaccuracies (37%) and lacking knowledge or understanding of AI technology (29%).
• Energy consumption was the least prevalent concern (14%), suggesting the environmental impact of AI-powered devices may not be immediately obvious to employees.

Overall, employees have fewer concerns about their own personal use of AI-powered devices at work than macro worries. Topping the list are voice assistants embedded in work devices that might eavesdrop on their conversations.

• AI-powered devices eavesdropping on private conversations topped the list of concerns among employees (40%).
• 1 in 3 employees (33%) worries that AI-powered devices will put their job and professional skills on the path to obsolescence.
• Slightly more than 1 in 4 employees (28%) are concerned about becoming overdependent on AI technology to do their jobs.
• Despite these concerns, fewer than 1 in 5 doubt their ability to learn and adapt to an AI-powered workplace.

Workers want to improve their ability to use AI-powered devices. Nearly half (49%) would like — and might expect — their employers to offer training to maximize the value of their applications.

• Most employees (79%) expect their employers to incorporate AI-powered devices to perform certain functions.
• Just short of half (49%) desire training on AI-powered devices; a similar amount (46%) want clear guidelines and policies for specific use cases.
• One-third (33%) hope their employer gives them the freedom to choose a device with or without AI powering it.
• Only a small fraction (13%) doubts their employer's AI readiness or ability to distribute AI-powered hardware at scale (11%).

Survey methodology

The research was conducted online in the United States from March 7 to 14, 2024, by The Harris Poll on behalf of Insight Enterprises among 604 U.S. adults ages 21+ who are employed full-time at a company with 1,000+ employees, including 201 Gen Z (ages 22-26), 202 Millennials (ages 27-42), and 201 Gen X/Boomers/Seniors (ages 43+). 

Data are weighted where necessary by number of employees to bring them into line with their actual proportions in the population.

Respondents for this survey were selected from among those who have agreed to participate in our surveys. The sampling precision of Harris online polls is measured by using a Bayesian credible interval. For this study, the sample data is accurate to within ±4.0 percentage points for the total sample and ±6.9 for each generation using a 95% confidence level. This credible interval will be wider among subsets of the surveyed population of interest.

All sample surveys and polls, whether or not they use probability sampling, are subject to other multiple sources of error which are most often not possible to quantify or estimate, including, but not limited to coverage error, error associated with nonresponse, error associated with question wording and response options, and post-survey weighting and adjustments.

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