AI at the frontline: still a work in progress

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While much of the emphasis of artificial intelligence and agentic AI has been on information workers, it’s important to remember that information workers, mangers, or professionals, whatever you want to call them, are only about 44% of the total workforce, according to estimates from the US Bureau of Labor Statistics. The rest are frontline workers – ranging from sales to production and distribution.

In terms of reaching frontline workers with the promises of AI, things are rather chaotic. That’s the conclusion of new survey of 5,693 frontline workers and managers out of Dayforce, which finds that frontline productivity suffers due to disconnected information and workflows.

“Most organizations are investing heavily in AI for corporate workers while leaving frontline hardworking employees, the people actually running production lines, warehouses, and customer service department largely unprepared,” said Caleb Prosper, CEO and founder of Gemena Tech. "The tools reach them last, training is minimal, and management change is an afterthought.

"AI adoption is still in the early stages for frontline workers," agreed Naeem Bari, co-founder and chief product officer at Linxup, a GPS fleet tracking and safety technology company. “Right now, the companies using AI are doing it at the office and management level. Field service operations are using AI in the back office to maximize job productivity, minimize windshield time for their techs, identify risks in the fleet, and automatically flag employee coaching opportunities to keep their employees and assets safe. Even AI dash cameras, which are already common in many vehicles, are used to report data back to management, not the driver, for analysis and coaching.”

Calling it “the frontline reality organizations weren’t built for,” the Dayforce report’s authors state that the transformations essential to remain competitive – AI or digital capabilities – tend to get stuck. Tellingly, only 29% of executives and
managers in the frontline organizations surveyed said their organization has “meaningfully evaluated” AI for frontline work. “That leaves many organizations still early in understanding where AI can help frontline teams and where it could introduce new risks.” Just 6% said transformation is well integrated into how daily work gets done.

Industry leaders agree that AI capabilities have yet to fully translate to the frontline. “The challenge isn’t whether frontline workers are being intentionally left behind with AI; it’s whether companies are moving as quickly on workforce enablement as they are on technology adoption,” said Rebecca Wilson, senior vice president of human resources at Kenco, a third-party logistics provider. “Frontline employees need practical training and AI tools that solve real operational challenges.”

AI may raise expectations for faster, better workforce decisions, "but it doesn’t remove the underlying problem,” according to the Dayforce report. “Frontline work depends on decisions that happen together in real time, while the systems behind them often remain separate. Many organizations still manage time, pay, staffing, skills, and employee development in separate systems. But for frontline managers,
those decisions collide in the moment. A schedule change can affect labor costs, compliance, coverage, employee experience, productivity, and service quality all at once."

In addition, more than three-quarters of frontline managers, 77%, said their systems "do not provide clear guidance at times when operational issues arise. Organizations are trying to drive change through systems and processes that weren’t built to work together."

It’s also a matter of preparing frontline workers with the proper levels of training and awareness. “Most organizations aren’t doing enough to prepare their workers for AI,” said Maura Howley, senior vice president of employee and customer experience at Ipsos. A majority of employees in a recent Ipsos study “either lack access to AI tools or rarely use them, compared to a much higher adoption rate among managers and executives.”

Kenco’s approach has been to offer company-wide AI training and AI tools “that support warehouse-specific activities such as WMS navigation and wave planning,” said Wilson. “Make AI accessible, practical and embedded in daily work so employees see it as a tool that enhances productivity and problem-solving.”

Managers need to work to “embed AI into everyday workflow, create role-specific, rather than generalized, training, and invest in change management," Howley advised. This starts with building trust. "Communicate clearly with employees, invite them into the process of identifying where and how AI would be most beneficial, routinely collect feedback, and offer continuous support.”

Show frontline workers “how AI removes obstacles or friction from their daily tasks, not how it serves corporate efficiency goals,” said Prosper. "Pilot programs with genuine input from employees, clearly communicate about job security, and role specific training will determine whether AI becomes an asset or a liability that causes anxiety in an organization.”