As AI adoption becomes more widespread, many fear that it’s taking jobs away. Certainly, some roles are changing and new ones are emerging. But there’s a bigger, often overlooked, story here: the significant role AI can play in enhancing employees’ work lives.
Across nearly every industry that depends heavily on hourly workers—airlines and hospitals, retailers and quick-serve restaurants, call centers and trucking companies—AI, and GenAI in particular, can make life on the job easier for employees, frontline workers and managers alike. Its benefits are wide-ranging: from accommodating scheduling preferences to providing instant training and troubleshooting; from simplifying time-sinking tasks and reducing interventions to delivering operational intelligence in real time. In the post-pandemic era, when workforce management has become ever more challenging, such benefits cannot be taken lightly.
By understanding AI’s many enabling functions, companies can more easily transform resistance into receptiveness. Below, we examine some of the highest-impact applications, including four real-world use cases we’ve developed as part of Frontline Ops AI by BCG X, an AI-powered tool that addresses pain points across the entire workforce management journey.
Reducing Complexity to Fix Employee Pain Points
Today’s workplace is growing increasingly complex: employees must be conversant in more processes and more (and more frequently changing) product offerings than ever before. They receive less upfront training and less company support. Local managers cope with more frequent turnover and compliance requirements; they, too, are expected to do more with less.
Research has repeatedly shown a strong correlation between employee satisfaction and performance and retention. A recent BCG Henderson Institute survey of more than 1,000 employees revealed that joy in the workplace cuts attrition by half. So it’s incumbent on companies to alleviate these mounting employee pressures.
From the complexities of scheduling to troubleshooting equipment failures on the spot or getting a fast answer to a pressing labor law issue, AI can be an indispensable tool for employees. Its ability to instantly sift through disparate enterprise systems to extract relevant information and translate it into plain language lets individuals solve problems on their own. With less frustration and greater efficiency, employees enjoy more autonomy and perform their jobs better. In that way, AI can balance customer experience, labor productivity, and employee satisfaction. (See Exhibit 1.)
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Simplifying Scheduling
Scheduling may well be the most complex, challenging, and headache-inducing activity for shift workers and their managers. Traditionally, schedules are created by central teams, usually three weeks in advance and with little explanation. Machine learning and GenAI transform this process by incorporating business rules and employee preferences and then refining the process over time. Frontline Ops AI, for instance, helps field managers assign employees across shifts, ensuring that schedules align customer demand times with employees’ availability and personal preferences (entered via an intuitive mobile app). (See Exhibit 2.)
In addition to simplifying schedule development, GenAI provides managers with insights that can help them improve and refine the process over time. Using plain language, GenAI creates documentation that explains step by step the rationale underlying the schedules it creates—something previously not feasible. Managers can now identify anomalies, make discretionary edits, and even use the output as a springboard for conversations with workers. They can feed edits and changes back into the tool to continuously improve schedules over time.
Adjusting for callouts is another time-consuming (and disruptive) task for managers, between crunching all the variables and evaluating their downstream effects. The AI tool can rapidly produce a set of options, which the manager can then fine-tune.
Consider the impact these scheduling solutions can have on workforce issues that have plagued the health care industry in recent years. Strikes and chronic worker shortages have fueled employee burnout, triggering absenteeism and turnover—which, in turn, exacerbate understaffing, creating a vicious cycle.
At one of the nation’s largest hospital systems, widespread dissatisfaction with managers on the part of medical employees has contributed to high attrition rates. Moreover, the factors driving attrition have varied by tenure. Less experienced employees seek upward job mobility; they also suffer more burnout and want more scheduling flexibility. Seasoned employees want more respect and recognition. Yet managers have had little control over many of the underlying problems. Typically, they supervise dozens of workers each, receive minimal training when promoted, and have few feedback mechanisms for seeking solutions at the corporate level.
We proposed demand-based scheduling. This entails improving patient volume forecasting and then customizing an AI schedule tool to optimize schedules for both patient inflow and employee preferences. Simply by reducing the company’s reliance on temporary medical employees, the solution is projected to deliver savings of between $125 million and $150 million.
We also recommended the AI-driven intelligent roster management tool we developed, which balances shift loads based on employee experience, preferences, and dynamic capacity management. Addressing clinicians’ preferences can boost their engagement and productivity—and by cutting attrition rates 30%, the savings on training, onboarding, and recruitment could amount to around $150 million.
Providing Instant, In-Flow Training
Increasingly, frontline employees are expected to learn more, faster—often while serving customers. As offerings expand and processes evolve, traditional training approaches become even less practical. Static manuals and apps located in different places and across different devices slow employees down, frustrating them and their customers.
At a quick-service restaurant, a virtual AI assistant we developed jointly with the company’s tech team and external tech partner is changing all that. The tool provides immediate access to recipes, procedures, and best practices, regardless of which company system holds the information. Employees don’t need to know where to go: they simply ask. They get the right answers while they work—instantly, in plain language on in-store iPads and in their format of choice. By doing their job better, employees gain confidence and create a more consistent customer experience.
Troubleshooting in Real Time (Without Escalating)
Whether it’s knowing when and how to escalate a customer issue or how to deal with an equipment problem, GenAI tools can help employees troubleshoot on the spot, without needing their manager’s intervention. Managers, for their part, are relieved of multiple interruptions in their workday, allowing them to focus on more strategic matters.
The AI assistant we developed for the quick-service restaurant described above helps employees resolve problems the moment they occur, whether it’s how to clean a piece of equipment, handle an exception, or diagnose a machine breakdown. They can get step-by-step guidance immediately, often through visual or animated instructions. In the future, the AI assistant will respond to problems by automatically initiating the next action, such as opening a trouble ticket and routing it to the appropriate system.
The results: fewer service interruptions, fewer unnecessary manager interventions, and less downtime for all.
In addition, the AI app’s foundational architecture is set up to help managers in several ways, such as by delivering task nudges and making suggestions. It can quickly address a callout by pulling up a list of potentially available employees and, in a single view on the same page, contact a substitute and get his or her response. It helps managers analyze their workforce management efforts by instantly providing critical metrics (such as Why is shift coverage low? and What’s our readiness score?) and alerting managers to risks, such as a peak service delay.
Curating Far-Flung Technical, Training, and Compliance Information
Training and compliance information is often dispersed across different company departments and systems. Tech training, owned by the IT team, may not be in every HR department’s files. Onboarding information for all levels may not be in HR systems at all locations. And the bigger the company, the tougher it generally is to find such information. GenAI effectively centralizes this information by scanning every repository to generate a comprehensive, up-to-date information set that gives employees answers quickly.
GenAI tools can offer powerful support to call center employees, whose job is inherently stressful. Providing fast service and accurate answers is vital, especially when the customer has already experienced a long wait. With high turnover, fast service is harder to achieve, and organizations risk steering customers wrong. The consequences can be significant for both customer and organization.
Consider the call center of a state agency offering tax law information to residents. The center receives more than one million calls each year and employs more than 100 reps, but 75% of them have less than a year’s experience. The average call lasts 15 minutes, half of which the rep spends combing through the state’s massive statute database for answers.
To help expedite matters, we developed a GenAI call center assistant that scours the database for the right information. The virtual assistant cut the average call length and customer hold times by 15% to 30%. By improving the quality of the first response by 5% to 20%, it reduced transfer rates by 20% to 30%. Employees were more effective, experienced less stress and frustration, and enjoyed greater job satisfaction. Turnover fell, in turn fueling better organizational performance and a better work environment.
From Knowledge to Action
On its own, GenAI is astonishingly good at assembling information. But the use cases described here reflect a broader point: GenAI delivers the greatest value for frontline labor when it is embedded into the systems that govern how work actually gets done.
When a company layers GenAI on top of existing processes, it is leaving employees to translate insights into action on their own. We take a different approach. By tightly integrating GenAI with operational data and analytics such as forecasting, optimization, and real-time performance monitoring, these solutions make work more transparent and humane—thus reducing friction for employees while improving organizational outcomes. GenAI becomes a decision support engine that helps employees navigate complexity and take action in the moment.
To those who think AI is primarily about replacing jobs to save costs, think again. Frontline workers remain essential to delivering great customer experiences. When organizations use GenAI to support—and not sideline—workers, they can spark higher engagement, better performance, and more resilient operations. In an era of chronic labor constraints, the ability to elevate the frontline workforce becomes more than just a people win; it becomes lasting competitive advantage.
