How a Small Investment in AI Can Reduce Retail Employee Turnover.
The first of a series. A five-minute read.
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Artificial intelligence in retail? Everyone’s doing it. You are, too.
Software vendors have integrated machine and deep learning and generative AI into their enterprise apps. Marketing and IT staffers (and others) are accessing large language models for content and code. Co-Pilot and Gemini are on every device. If you’re sending text messages or e-mail, you’re using AI natural language understanding and generation. No doubt somewhere in the company there are pilot projects (both official and furtive).
We’re all doing it.
But we may not be doing it well.
The issue is not the doing but the approach.
Too often, it’s confused. Scattershot, a bit here and a bit there, akin to a cat convention. Or siloed and minimized, defined as an IT thing.
What's needed: cross-organization commitment, involvement, and cohesion. And strategic clarity -- a focus on where and how competitive advantage is won or lost.
A business plan for this new era of AI-powered retail. A plan that applies the capabilities of artificial intelligence to speed workflows and augment the power of humans.
Let’s walk through an example.
PAIN POINT: STORE ASSOCIATE TURNOVER.
According to the U.S. Bureau of Labor Statistics, roughly 60% of all U.S. retail employees quit or were fired in calendar year 2024. A 2022 Korn Ferry survey (perhaps tilted by the recent pandemic) found an annual turnover of 75.8% of retail hourly-wage workers, a number that climbed to 85% of part-time hourly-wage employees.
Equally concerning – as measured by loss of productivity, organizational wisdom, and the next generation of leadership – were the turnover numbers for store management. Per the Korn Ferry study, 17.7% of store managers (nearly one in five) left within the year, and 29.2% of assistant store managers walked out the door.
WHERE AND HOW DEEPLY THIS PAIN HURT THE BUSINESS.
Honeycomb partner and former industry CFO Don Bassell lists these quantifiable pains, felt ultimately in income statement top- and mid-lines:
· The cost of termination, realized in HR and store management time and expense, and the cost (in some situations) of legal advice and action.
· The cost of hiring, realized in HR and store management time, and the opportunity cost (especially borne by store managers) of other responsibilities.
· The cost of training, realized in HR, store management, and store employee time that must be used while a newly-hired employee is in training – time that often runs into overtime.
· A loss of employee productivity for several months, realized in basic tasks done more slowly than average, and complex tasks not done at all.
· A decline in store revenue due to lower operational productivity
· A negative effect on customer retention and new customer acquisition
· And a loss of operational knowledge and wisdom – never to be recovered.
Ouch.
WHAT CAN WE DO?
Start not by looking at technology, but at business processes, human behavior, and how outcomes can be improved.
The research shows that when store associate success is accelerated – i.e., they’re better, faster, more confident, and sooner – associate engagement goes up. And when engagement goes up, there’s greater commitment to the job, higher daily productivity, better-than-expected customer interaction, and a greater willingness to stay and grow with the firm.
All which pays on the top line and the bottom line.
How do we accelerate success? Perhaps we make it easier and faster for training information (still, often, in three-ring binders) to be absorbed and turned into action.
Perhaps we take all that what-to-do and how-to-do information and put it in an associate’s ear, available at the click of a button or even at a whisper.
WHAT CAPABILITIES OF ARTIFICIAL INTELLIGENCE ARE MOST RELEVANT HERE?
o The ability to ingest, summarize, and provide ever-more precise answers from vast amounts of unstructured data. Here, we bring employee policy manuals, how-to-fix-it documents, and descriptions of best practices to generative AI tools. And do so within your corporate firewall.
o The ability to understand natural language queries and deliver natural language responses – be they written or acoustic, and in dozens of languages. These are the tools of natural language understanding, processing, and generation – honed through the years in voice assistants such as Amazon’s Alexa and Apple’s Siri.
By the way: the 2025 Tech Trends Report from the Future Today Strategy Group (FTSG) urges enterprise leaders to shift quickly to conversational, natural language interfaces. A traditional interface – mouses, clicks, links – will soon be the CX equivalent of a flip phone.
WHAT IF WE?
o First worked directly with store ops, store managers, and selected store staff to determine where, when, how, and for whom this will be of most value – and drafted a set of working hypotheses to test against.
o Loaded all of today’s employee instruction manuals and training videos into a private generative AI search-and-summation tool – one that kept your data inside the firewall, as it should be.
o Spent a bit of time (hours, not weeks) with new hires and veterans building a 1.0 repository of frequently asked employee questions -- especially the “how do I do this?” queries.
o Fed into the tool daily announcements and reminders
o Enabled a modern, natural language interface for your employees, in their language of fluency – so they could ask questions and hear responses, in real time.
o Provided employees with an inexpensive talk-and-listen wearable.
Start with a lab-based tech trial. And then to a store for a production pilot. Measuring and revising all the time. Easy to use? Save time? Better retention? Better performance, and sooner?
In phase next, we could feed into the tool simple scripts describing current promotions and specials, and allow the tool to access current product pricing-promotion-availability by channel. In phase next-next, we could integrate task management and employee benefit knowledge (paydays, insurance, vacation days, scheduling) into this operational wizard.
IMMEDIATE OUTCOMES
o Answers in seconds. Accelerated success. Happier customers. And with it, increased engagement and in time, employee retention.
o An empowered employee, with an experienced trainer (in the language of choice) in the ear, able to ask (and hear) answers.
o How-to questions answered in moments.
o A sharp reduction in deer-in-headlights pauses, or slow walks to supervisors (which pulls supervisors from their tasks, thus multiplying the loss of productivity
WHO NEEDS TO BE INVOLVED?
Store operations. Store management and staff, including new hires. HR. Information Technology. Revenue and Marketing officers.
THE INVESTMENT
Buy or build? This is mostly buy. It includes:
o A commitment to reduce the pains of employee turnover – a commitment measured in time and thought invested by multiple stakeholders.
o Partnership with proven generative and NLU-NLG-NLP AI specialists and integrators
o Subscription and licenses to a private generative AI search-and-summation tool
o Testing and purchase of wearables best suited for floor associates – and processes, places for care and recharging
o Development of the solution data base – which could require 1) updating all corporate training and policy content, 2) incorporation of what-to-do, how-to-do and how-to-fix content from hardware and systems vendors, ranging from POS to fixtures to freezers, and 3) integration into product, pricing, and inventory data bases
o Change management advisory services for store ops and staffers
o And, a small additional expense in waste- and trash-management for the hauling away hundreds of three-ring binders and cardboard boxes of printed policy manuals.
IS ANY RETAILER DOING THIS NOW?
Yes. In a panel presentation at the mid-January National Retail Federation Big Show, Shirley Gao, Chief Digital and Information Officer at PacSun, and Mirko Saul, SVP and Head of Innovation, Schwarz Digital GmbH & Co., both spoke to their firm’s development and implementation of real-time AI-powered advisors for floor associates.
WHAT’S NEXT
Let’s connect.
Honeycomb Retail AI is an independent think tank of industry veterans – individuals with CEO, CFO, CIO, CMO (marketing and merchandising) and CPG and technology partner experience. We’ve been through retail’s many disruptions – and we consider artificial intelligence to be the next big one.
Over the past year we’ve developed a detailed study of AI’s value across nearly 250 common retail workflows. The concept outlined above is but one of nearly a dozen ideas we've uncovered for increased employee engagement and retention.)
All this has led us to a unique understanding of where, how, and when AI will create value.
Our value to you? Think of us as educators. A calm, well-versed, senior presence for quiet conversation, workshops, and executive advice.
When we walk away, you’ll share a vocabulary, know AI’s capabilities and be ready to face AI’s dependencies in data, infrastructure, and governance. You’ll know where AI’s being used – both in your organization and across the industry. You’ll know in detail how, where, and how soon AI will pay – or not. And you’ll know where and how to implement AI tools so that your investments create compounding, exponential value.
To help you take additional steps, we partner with great firms such as IHL Group, the global retail research and advisory firm, and Retail Technology Consulting. IHL, for instance, will work with you at a project, department, or organizational levels, helping you crawl, walk, and then spring with an AI-empowered business strategy.
Send us a note at hello@honeycombretail.ai to receive our whitepaper and begin the conversation.
Honeycomb Retail AI is an independent retail industry think tank. Its members share intellectual property ownership of specific artifacts created by think tank members for Honeycomb Retail AI use.
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