Big Lots workers face a retail future shaped by AI skills, not titles
Big Lots's bankruptcy history makes AI feel immediate: the next retail reset is about scheduling, customer handling, and digital fluency, not job titles.
On Sept. 9, 2024, Big Lots entered Chapter 11 and sold the business to Nexus Capital Management as part of the restructuring. Store-closure plans reached 344 locations and later 963 stores, so any new automation debate lands on top of a company that has already been forced to rethink labor from the ground up.
Big Lots enters the AI conversation from a hard reset
Big Lots was considering a bankruptcy filing on Aug. 28, 2024, as sales declined, and by Sept. 6 it was preparing a bankruptcy filing with plans to sell stores. Kroll Restructuring Administration’s case page lists Former BL Stores, Inc., formerly Big Lots, as having initiated voluntary Chapter 11 proceedings on Sept. 9.
Big Lots filed for bankruptcy protection and promised to keep offering “extreme bargains.” In early September 2024, the company put 344 locations on an initial store-closing list, and a Sept. 11 filing updated the list to 344 locations across 41 states. By Dec. 19, 2024, Big Lots was preparing to close all of its locations and begin going-out-of-business sales. On Dec. 20, Big Lots planned to close all stores. After a sale to save the bankrupt retailer fell through, it was preparing to close its remaining 963 locations. On Jan. 1, 2025, Big Lots was approved for a last-minute sale of 200 to 400 stores.
Macrotrends lists Big Lots’ annual employee count at 30,300 in 2024, down from 32,200 in 2023 and 36,200 in 2022.
Where AI is most likely to touch the work first
BDO’s analysis of work in the age of AI centers on a redesign issue, not just a replacement tool. It is not about automating every task that currently exists. It shifts routine work to software so people can spend more time on the parts of retail that require judgment, speed, and human repair.
At Big Lots, the first likely uses are practical. AI can improve demand forecasting so stores order closer to what customers will actually buy. It can help scheduling software match labor to traffic more accurately, which matters in a chain where weekends, truck days, and seasonal promos all change the shape of the shift. It can also sit behind chat tools, internal knowledge bases, and self-service HR systems that answer basic questions faster than a manager can.
The work that software is best suited to take over is the repetitive part of the job. That includes routine policy lookups, standard schedule changes, basic report pulling, and some of the forecasting and replenishment math that planners now do manually. The work that is more likely to be augmented, rather than removed, includes promotion planning, inventory decisions, and labor allocation, where the machine can surface patterns but still needs a person to make the call.
What stays human is the part of the job that breaks the script. Customer recovery, out-of-stock substitutions, markdown judgment, merchandising gaps, and store-level exception handling all depend on context that software cannot fully see. In support-center roles, the same logic applies: the repetitive questions may move to a chatbot or knowledge base, but the escalations, the exceptions, and the cross-functional decisions still need people who understand how stores actually work.
The skills that will travel across titles
That is why Big Lots workers should think in terms of skills, not job titles. A cashier, sales associate, department lead, or support-center employee who can read a dashboard, spot a problem early, and make a quick decision will be more valuable than someone who only knows a single scripted task.
The skills worth building now are clear:
- Problem-solving, especially when the store is short on product, short on labor, or dealing with a customer issue that does not fit the script.
- Customer handling, including de-escalating complaints, explaining alternatives, and keeping a sale alive when inventory is thin.
- Scheduling judgment, which means understanding traffic patterns, weekends, holidays, and the practical reality of who needs to be where and when.
- Digital tool fluency, from handheld devices and scheduling dashboards to self-service HR systems and internal knowledge tools.
For workers thinking about promotion, the next step up is likely to require more than speed at a register or familiarity with a department. Managers who can interpret data, coach the team, and adjust execution quickly will stand out.
Retail is already signaling the direction
The broader retail market is moving in the same direction. UKG’s 2025 Retail Workforce Report surveyed 541 U.S. retail executives and managers and examined staffing, employee sentiment, and the integration of AI. Walmart unveiled new AI-powered tools on June 24, 2025, to empower 1.5 million associates.
TimeForge’s retail scheduling page and McKinsey’s retail scheduling page point the same way: AI integration is emerging in workforce scheduling for retail operations, and AI-driven schedule optimizers can reduce downtime, improve productivity, and minimize headaches. Kearney and NRF materials also frame AI as something that can reshape frontline roles and support skills-first hiring.
The pressure is not just inside retail. A Programs.com tracker published on July 9, 2026, counted more than 165,000 employees affected by companies announcing AI-driven layoffs.
This article was produced by Prism’s automated news system from verified source data, official records, and press releases, then run through automated quality and moderation checks before publishing. The system is built and supervised by the people who set the standards it runs under. Read our full AI policy.
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