July 03, 2025 - Artificial intelligence (AI) is rapidly transforming the retail landscape, with employers eagerly embracing AI tools to streamline and optimize nearly every facet of their operations. While adopting AI programs may provide significant benefits, retailers must consider how these changes could cause a shift in managerial duties that could impact store managers' exemption status.
Understanding this impact requires an awareness of the criteria that distinguish salaried exempt employees from hourly nonexempt ones. For example, factors such as the importance of tasks performed, level of responsibility, use of discretion and independent judgment, and amount of time spent on specific activities can all be relevant to this determination. A full description of the criteria can be found in 29 C.F.R. part 541.
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In this article, we discuss considerations for retailers implementing AI, particularly in relation to the evolving role of store managers. Traditionally, store managers have overseen key aspects of workforce management, such as employee selection, labor forecasting and scheduling, timekeeping, and performance management. However, in certain retail environments, AI tools are being implemented with the capability to perform many of these functions.
Below, we review areas of workforce management where the implementation of AI may influence the role of store managers and, in turn, impact their exemption status.
Employee selection: AI is increasingly being leveraged in the employee selection process. AI programs can scan resumes to identify applicants with specific characteristics (e.g., education, experience) that align with job descriptions or filter out applicants who lack these qualifications. Additionally, AI can be used to administer and evaluate pre-employment assessments. For example, assessments can evaluate applicant compatibility, through job simulations and realistic previews, and applicant competencies, such as customer service and task prioritization.
Even with the growing use of AI in employee selection, most retailers still rely on in-person job interviews and the store manager's opinion as the final hurdle in the hiring process. That said, the role of AI in selection has been the subject of legal debate and litigation, particularly the extent to which employers rely on it to make decisions regarding candidates. Although recent efforts have been made to control the nature of AI's involvement in these activities, the outcomes have yet to be determined.
Labor forecasting and scheduling: Developing and managing an effective employee schedule that stays within a given labor budget requires consideration of multiple variables such as staff availability, anticipated customer flow, vendor and product deliveries, seasonal trends, projected weather events, and local community events. AI solutions can rapidly integrate vast amounts of data from a wide range of sources and generate optimal schedules.
Some AI programs can automatically adjust for unexpected changes, such as employee callouts, and minimize labor costs by avoiding unnecessary overtime. Still, in our experience, even schedules that are generated using such software may require significant modification from a manager before they can be finalized.
Timekeeping: AI is increasingly being used to manage employee timekeeping behavior. AI programs can track and analyze timeclock punches, flagging missed or late entries and ensuring compliance with meal and rest break requirements. For example, an AI system may alert a store manager in real time if an employee's work hours begin to extend beyond their scheduled shift or if a required break has not been taken, allowing for immediate intervention before compliance violations occur.
AI tools can also identify trends and outliers in attendance data, helping store managers spot employee patterns such as recurring tardiness or absenteeism. Even with AI advances, employees will likely require instruction on how to use these programs, and some oversight will likely be required.
In addition, advances in biometric and facial recognition technology have changed traditional "timeclock" practices. These tools replace or supplement older systems like swipe cards and punch clocks by verifying employee identity using unique physical characteristics, such as fingerprints or facial features. This reduces time-theft practices like "buddy punching" and simplifies the clock-in process, while integrating seamlessly with scheduling and payroll systems. However, it is worth noting that some jurisdictions may have privacy restrictions on the use of biometrics, which could prevent these systems from being fully adopted.
Performance management: Performance management in a retail environment has historically relied on store managers observing employees to assess customer interactions, evaluate productivity, and monitor safety protocols. AI programs have transformed performance management and can be used to determine whether employees greet customers, attempt upsells, or maintain a positive tone during communications. Similarly, productivity can be measured using AI data from point-of-sale systems or task-tracking software, providing live dashboards that quantify an employee's output over a given period.
AI tools can also support workplace safety and compliance, which can be a performance metric in some environments. Video analytics with AI can detect violations of safety protocols, such as running, improper lifting, or failure to wear personal protective equipment. While AI programs can quickly quantify job performance metrics, store manager oversight may still be important for interpreting the data and translating it into effective feedback and coaching.
Although each AI capability described above undoubtedly offers clear benefits to employers, its use may create confusion around the classification of store managers. Specifically, applications of AI programs may impact how a store manager spends their time (e.g., dedicating less time to tasks such as scheduling, reviewing punches, and evaluating productivity) and the level of discretion store managers exercise.
And, as noted previously, the amount of time a store manager spends performing exempt work can be a relevant factor in determining a job's exemption status. Similarly, the store manager's involvement in making decisions and exercising independent judgment and discretion can be a factor.
Our on-the-ground experience suggests that AI's impact on the store manager role may vary not only between employers, but also from manager to manager. For example, some store managers may quickly rubber stamp an AI-generated work schedule, while others may take time to adjust it based on their personal knowledge of employees and store operations. Similarly, some store managers may simply review performance metrics, while others may leverage these metrics to identify coaching opportunities or develop strategies to improve store performance.
As retailers implement AI solutions, they should remain mindful of how these programs may shift the work store managers perform and how such changes could inadvertently affect their exemption status. We recommend that employers routinely audit the exemption status of their store managers, a practice that will become even more critical as AI rapidly transforms the retail landscape and the work store managers perform.
Lastly, while this article focuses on the implementation of AI as it relates to workforce management, it should be noted that AI touches nearly all facets of retail operations and can therefore impact store manager duties and responsibilities in ways that go beyond what is addressed here.
This article does not offer legal opinions regarding the classification of responsibilities, work tasks, or employees/managers. The views expressed herein are those of the authors and not BRG or its other employees and affiliates.
Opinions expressed are those of the author. They do not reflect the views of Reuters News, which, under the Trust Principles, is committed to integrity, independence, and freedom from bias. Westlaw Today is owned by Thomson Reuters and operates independently of Reuters News.
Elizabeth Arnold serves as a director and testifying expert in the labor and employment practice of BRG, a management consulting firm. She specializes in evaluating work activity within the context of wage and hour law compliance. She is based in Emeryville, California, and can be reached at earnold@thinkbrg.com.
Samantha Stelman serves as an associate director in BRG‘s labor and employment practice. She is an industrial-organizational (I/O) psychologist and specializes in survey design, research methodology, and job analysis. She is based in Emeryville, California, and can be reached at sstelman@thinkbrg.com.
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