Closing the AI Gap for Frontline Workers: 4 Moves for People Leaders

AI - Artificial Intelligence, Company Culture, Employee Engagement , Employee Experience, Employee Trust

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 The people closest to your customers and your operations should be among the most confident AI users in your organisation. Right now, they are often the least.

Across many organisations, frontline workers use AI less often than senior leaders do, according to data from Great Place To Work. Canada shows the same pattern. A 2026 Statistics Canada study found that 44% of workers in jobs that usually require a bachelor’s degree had used generative AI at work in the previous year, compared with only 10% of workers in jobs that usually require a high school diploma or less.

That gap should not come as a surprise, and it says little about ability or willingness. It says a great deal about how frontline work is designed.

Why frontline workers are slower to adopt AI

Several conditions set frontline roles apart from office roles when a new technology arrives:

• Deskless work: Most AI tools arrive through a laptop or a chat window. For someone on a production line, in a hospital unit or behind a retail counter, stopping to use one interrupts the job instead of supporting it.
• Surveillance concerns: Frontline teams are quicker to wonder whether AI will be used to watch them. Even well-intended tools can misfire. Picture a delivery driver whose in-vehicle AI coach starts critiquing their driving mid-route. The idea has merit, but the experience is embarrassing, because nobody designed it with the driver in mind.
• Little time to learn: Shift schedules, commutes and on-site demands leave almost no room for upskilling during the working day.

Uncertainty compounds these barriers. In an Angus Reid Institute survey, blue-collar workers were the group most likely to say they could not predict what effect AI would have on their work at all (28%). Uncertainty like that rarely turns into enthusiasm without help.

What leaders get wrong about AI in the workplace

Many organisations still picture AI in the workplace as a chatbot. That picture is far too small. Much of the AI reshaping frontline work operates as infrastructure that people never interact with directly: systems that balance the electrical grid, make food harvesting more efficient, help vehicles navigate traffic and flag equipment faults before a breakdown. The best technology is often the kind nobody notices.

In frontline settings, this is sometimes described as ambient AI. Think of the sensors already built into factories, warehouses and job sites, working alongside people rather than through a screen. Large language models are only one small part of the story.

It is equally mistaken to assume frontline workers lack technical skill. As physical and digital work continue to blend, frontline roles are on track to become some of the most technical in the economy. That makes AI literacy an urgent priority. Working with these systems will soon be a baseline expectation in warehousing, manufacturing and logistics, and workers who are not supported through reskilling risk being left behind.

Where should automation stop?

Most AI rollouts are framed around efficiency, and that framing is quietly eroding trust on the frontline. The same Angus Reid Institute research found that nearly three in ten employed Canadians are at least somewhat worried AI could replace them.

What usually goes unexplained is the purpose of efficiency. Done well, it lowers the cost of delivering a product or service so that more people can access it, whether that is food, education or healthcare. When leaders spell out that purpose, including how the gains will benefit employees, frontline teams have a reason to lean in rather than brace for impact.

Not everything should be optimised, either. A coffee shop is a useful example. Letting customers order ahead makes sense, but the exchange with the barista is part of why people come in. Every organisation has a line like this, where human involvement is worth more than the minutes it costs. Some work, such as parts of drug discovery, benefits from being automated as fully as possible. Other experiences, like a memorable restaurant meal, do not need to become any faster. Finding that line in your own operations is a conversation worth having with the people who do the work every day.

Why engaging frontline workers with AI pays off

How your AI transformation unfolds has real consequences for performance. Great Place To Work found that employees who use AI at least monthly were:

• More likely to give extra effort
• More likely to adapt quickly to change
• More likely to want to stay with their organisation

Leaving frontline teams out of that shift means leaving those gains on the table.

4 moves to close the AI gap for frontline workers

1. Listen closer to the frontline. Frontline voices are too often missing from decisions about where and how AI gets deployed. Organisations that have outperformed on quality and innovation over time tend to share one habit: they listen at the exact point where work gets stuck, such as the spot on an assembly line where friction builds. Listening methods that genuinely reach deskless teams, including mobile-friendly surveys and regular conversations on site, surface the use cases that matter most.

2. Aim higher than incremental gains. Many people treat AI as a way to write a slightly better email. A more useful question for leaders is how AI could fundamentally change the way the business runs. Use AI tools to stress-test your processes and propose bolder redesigns, then involve frontline teams in judging which ideas actually hold up in practice.

3. Be transparent about how AI is used. Worries about employee monitoring are among the biggest barriers to frontline adoption, and ambient AI raises the stakes further. Be explicit about what data is collected, what it is used for and what it will never be used for. Trust grows when workers can see that AI is there to support them, not to watch them.

4. Measure what matters on the frontline. Hours or minutes saved is the wrong yardstick for frontline AI. Track workplace safety, worker confidence and the quality of the customer experience instead. When success is measured in terms frontline workers care about, adoption tends to follow.

Closing the gap starts with trust

Understanding how your people experience AI starts with asking them. The Trust Index™ Survey shows where trust is strong and where it needs attention across every part of your workforce, including front line workers who are often the hardest to reach. Research behind the Great Place To Work Effect shows that high-trust cultures are the ones that turn change into lasting business results.

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This article is an adaptation of the original Great Place To Work®, written by Ted Kitterman, Content Manager.

 

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People Also Asked

How can AI be used in the workplace?
Beyond chat tools, AI supports scheduling, quality checks, safety monitoring, predictive maintenance and customer service. For frontline teams, the most useful applications are often built into the equipment and systems people already use, so they help without adding steps to the job.

Is AI surveillance in the workplace a concern for employees?
Yes, especially for frontline teams, who are more likely to worry that AI will be used to track their performance. Clear communication about what data is collected, why, and what it will never be used for is the most reliable way to address that concern.

What should an AI in the workplace policy include?
A strong policy sets out which tools are approved, how employee data is handled, where human judgement remains required, and how people can raise concerns. It works best when it is written in plain language and shared with every employee, not only office staff.

How can organisations train frontline workers on AI?
Build learning into the working day rather than adding it on top. Short, mobile-friendly sessions, on-shift practice with real tools, and peer champions from within frontline teams make AI training accessible to people who do not sit at a desk.

What are the pros and cons of AI in the workplace?
AI can improve safety, reduce repetitive work and help teams adapt faster. The risks include eroded trust, unclear accountability and uneven access to tools and training. Organisations that involve employees in rollout decisions tend to capture more of the benefits.

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