Transforming C-store Labor Practices With AI
Despite economic challenges impacting consumer demand, convenience stores are enjoying a demonstrable surge of growth. C-store foot traffic was up at the close of 2024, with monthly visits passing the pre-pandemic baseline by 15.5% in November. Meanwhile, major chains are expanding, and others are consolidating to form stronger businesses. At a time when the definition of "convenience" has shifted from corner stores to online shopping, all this action has c-store leaders rightfully energized.
As the c-store sector grows, so will the need for skilled hourly workers. To address increased staffing demands, c-store leaders will have to appeal to promising candidates while still supporting and investing in their current employees. This means listening to employees' biggest concerns and realigning workforce management (WFM) practices to remediate them, ideally through a combination of revised strategy and improved technology.
[Read more: Retailers Access Operations Toolbox to Improve Store-Level Execution]
Thanks to recent developments in artificial intelligence (AI), this process is more streamlined and impactful than ever. Today's c-store leaders can employ AI tools to transform their labor management practices and help ensure a thriving workforce.
Here are four use cases to consider:
1. Improve Training, Feedback & Rewards
AI can play a pivotal role in the employee development lifecycle, from training and onboarding, to ongoing feedback, to rewarding strong performance. This last point is especially pertinent to talent acquisition and retention: Legion data shows 65% of hourly workers say they need better recognition and rewards for their hard work. In some cases, this would even persuade them to leave their current job for a new one. C-stores that skimp on recognition will risk losing their best employees — and likely struggle to rebuild their workforce.
Often, the biggest barrier to proper recognition in the workplace isn't that managers don't want to give it; it's that they don't have time to. Fortunately, AI can give them some of that time back. AI tools that automate time-consuming administrative tasks, such as creating and managing schedules, return valuable time to managers — time they can redirect into employee training and development. AI also helps with recognition itself, as managers can use generative AI tools to draft messages giving praise and kudos.
Additionally, AI tools can recommend personalized incentives and rewards based on an employee's performance, ensuring that recognition is timely, visible and proportional. This proactive approach to feedback boosts morale, strengthens employee confidence and motivates them to continue improving.
2. Enable Flexible Scheduling
Hourly workers have repeatedly expressed their desire for flexibility. While frontline c-store employees may not be able to work from home like their peers in office jobs, hourly workers expect — and deserve — a flexible employee experience that allows them to balance their jobs with their personal lives and responsibilities. In fact, a Randstad study found that 73% of employees consider work-life balance a key factor in job selection, ranking it second only to salary, making it crucial to employee recruitment and retention efforts.
The good news? The shift-based, often 24/7 nature of the c-store workplace makes it inherently conducive to flexibility. C-store leaders can harness this potential across multiple WFM functions — and then enhance it further with AI. This might look like:
- Optimizing scheduling practices: AI-driven WFM tools use historical sales data and real-time store conditions to predict peak hours and adjust employee schedules accordingly. This ensures the right number of workers are scheduled during busy times, decreases labor costs during slow periods, and helps to boost productivity, efficiency and customer satisfaction. It also ensures businesses have the necessary schedules to achieve revenue and customer-service goals.
- Offering shift-swapping and the ability to easily pick up open shifts options: Employees should be able to request and negotiate shift swaps or pick up open shifts with ease. AI-powered tools can apply their requests and update schedules instantly, giving employees the flexibility they expect (and deserve) from their employer.
- Automatically balancing labor needs with employee preferences: AI-powered scheduling tools generate schedules that adhere to various parameters and changes, allowing them to match projected demand with employee preferences and skills. By using objective data to generate schedules, rather than manager discretion and gut feelings, these tools help to reduce conflicts — both scheduling and interpersonal — further promoting employee satisfaction.
3. Keep Up With Dynamic Demand
Convenience stores are uniquely prone to demand fluctuations given their proximity to major roadways and busy city centers. Events, traffic accidents, weather patterns, shifts in product demand and even gas prices can make it challenging for store managers to predict demand based on intuition alone. But while AI can't predict every rainy day and traffic jam, AI-driven demand forecasting can identify patterns in key demand influencers to provide more accurate outlooks, helping managers optimize for efficiency.
AI will analyze historical sales data to identify peak hours, seasonal trends and real-time changes, ensuring staffing needs align with anticipated demand. Ideally, these AI models will retrain on refreshed data at least once a week to promote accurate forecasting. An AI-driven WFM tool can then apply forecasted demand to situations where unforeseen changes occur and adapt labor plans in real-time. Agile, efficient responses to demand changes will make employees feel more prepared — and make their employers more competitive.
4. Increase Efficiency on the Job
With 72% of companies worldwide embracing AI to improve efficiency, c-stores that haven't made the switch have to play catchup. AI helps to fill operational gaps and increase efficiency for employees in c-stores. Automating the organization and prioritization of daily workloads allows employees to shift their focus to high-value tasks, such as attending to customers, collaborating with teammates and restocking items in high demand.
AI also can improve communication, which is key for efficiency in any business. When integrated into a WFM tool, AI can automate alerts about schedule changes and shift requests, ensuring that employees receive updates in real-time. They won't miss a beat, which means they likely won't miss a shift either.
By streamlining communication and automating routine tasks, AI enables c-stores to optimize labor operations, ensuring smoother workflows, increased productivity and a more satisfied workforce, all of which will be critical to staying competitive in this period of rapid industry growth.
Michael Spataro is senior vice president of partnerships and employee value solutions at Legion Technologies. He has 30-plus years of retail WFM, store operations and technology experience. He spent 16 years leading the Retail and Hospitality Services Practice Group at Kronos. His passion for retail WFM is rooted in the 10 years he was director of store technologies at Gap Inc. Previously, Spataro led the Kronos Services Group at Axium.
Editor's note: The opinions expressed in this column are the author's and do not necessarily reflect the views of Convenience Store News.