Every retail conference session these days seems to open with the same slide: some statistic about how much money AI is going to unlock for the industry. It’s easy to tune out. Running specialty retailers have built their businesses on something AI can’t replicate – a good fitter watching someone’s gait, asking the right questions, building trust one customer at a time.
But dismissing AI as hype misses what’s actually happening on the ground. The technology has moved past chatbots that mostly frustrate customers. What’s emerging now is a set of tools that help your people do their jobs better, not tools that try to replace them. For running specialty retailers, the opportunity isn’t in some abstract AI strategy. It’s in a handful of practical applications that touch inventory, marketing, training, and the sales floor itself.
There’s no replacing the human touch. Empowering employees with AI tools frees more time for human interactions. Building out AI tools with a human-in-the-loop mindset frees your team to spend their time on the most important things, offloading repetitive tasks to technologies optimized for those activities. Here are six areas on which all run specialty retailers should be focusing.
1. Let AI Handle the Busywork Behind the Counter
Every store has a stack of tasks that pull associates away from customers – writing product descriptions, answering the same email questions, summarizing what a shipment of returns says about fit issues. This is the lowest-risk, highest-value place to start with AI and it’s where most independent retailers should begin.
Ways to put AI to work behind the scenes:
• Use generative AI tools to draft product descriptions, social captions and email copy, then have a human edit for “voice” before it goes out.
• Feed AI your customer reviews and return notes to surface patterns – which models run narrow, which products customers love for long runs and where sizing complaints cluster.
• Use AI to summarize daily sales and traffic data into a short morning briefing your team can actually read before opening.
None of this requires enterprise software or a technology budget. Most of it can start with tools you already have access to, used with some discipline about what you feed in and what you check before it goes out the door.
2. Give Your Sales Associates a Copilot, Not a Replacement
The fastest-growing category of retail AI right now isn’t customer-facing chatbots. Its tools built for the people standing on the floor. Associate copilots pull customer purchase history, inventory position and product details into one place so a fitter can answer a question in seconds instead of walking to the back room.
What this looks like in a running store:
• An associate can pull up a customer’s past purchases and gait-notes before a return visit, so the conversation picks up where it left off.
• Real-time inventory lookups mean nobody has to guess whether a size is in stock at another location, if another location exists.
• AI-assisted product knowledge tools help newer staff answer technical questions about stack height, drop and stability features without months of ramp-up time.
The retailers enjoying the best results treat these tools as training wheels for newer associates and a time-saver for veteran ones.
3. Bring AI-Powered Fit Tools Into the Conversation, Not Around It
AI fit-finders have gotten genuinely useful. Brands like Nike and New Balance have invested heavily in tools that translate a customer’s size in one model to a recommendation in another and some use foot-scanning technology to model volume and arch shape. The mistake I see is treating these tools as a replacement for the fitting process instead of a way to make it faster.
How to use fit technology properly:
• Use a scan or sizing tool as the starting point for a fitting, not the final word. Let your associate’s eyes and the customer’s feelings confirm it.
• Train staff to explain what the tool is doing, so customers understand why a recommendation makes sense rather than just trusting a screen.
• Use the data these tools generate over time to spot patterns in what your local customer-base actually needs.
Customers still want a person to tell them a shoe is right for them. AI can help that person work faster and be more accurate. It doesn’t make them less necessary.
4. Use AI to Get Smarter About Inventory and Demand
Operating a specialty store is a tough inventory business – narrow margins, seasonal demand and dozens of models across half a dozen brands, each with its own sizing and color runs. AI-driven demand forecasting, once available only to large chains, is now accessible to smaller retailers through point-of-sale and inventory platforms that have built-in predictive tools.
Ways to apply this on a smaller scale:
• Let AI flag which sizes and models are trending toward a stockout before it happens, instead of finding out at the register.
• Use sell-through data to inform what you reorder for race season, rather than relying purely on last year’s numbers.
• Apply AI-assisted markdown timing to move end-of-season inventory before it becomes dead stock.
This is one of the areas where AI has the clearest, most measurable payoff. It directly affects cash flow and working capital, which matters enormously for independent retailers operating on thin margins.
5. Personalize Without Losing the Local Voice
AI-powered marketing tools can now predict which past customers are due for a new pair of shoes based on typical mileage. Tailor email content to what someone actually buys and time promotions around race calendars. The risk is that this starts to feel like every other big-box retailer’s inbox. Here’s how to keep it feeling like your shop:
• Use AI to identify who to reach – customers overdue for a shoe replacement or those who bought a debut pair of trail shoes and might be ready for more gear.
• Keep the actual message written or reviewed by someone who knows your community, not fully automated.
• Use AI to test subject lines and send times, but keep event invitations, group run reminders and local partnerships handled by a real person.
The stores winning with AI marketing are the ones using it to work smarter (and faster), not to sound like everyone else.
6. Always Keep a Human in the Loop
Every AI vendor pitch will tell you their tool is ready to operate on autopilot. Resist that. The most effective retailers deploying AI right now are the ones who keep a person reviewing what the technology recommends before it reaches a customer, whether that’s a marketing message, a reorder quantity or a fit recommendation.
A few guardrails worth setting from Day One:
• Require approval before any AI-generated customer message goes out.
• Don’t let AI make final pricing or markdown decisions without a manager’s sign-off.
• Train your team on what the tools are good at and where they still get it wrong, so nobody defers to a screen out of habit.
AI is a tool for surfacing information and saving time. The judgment still belongs to your team.
Some Final Thoughts
Running specialty retail has always depended on trust – a customer trusting your associate’s advice, your store’s fit and your community’s word of mouth. None of that changes with AI. What changes is how much of the busywork around that relationship your team has to carry alone.
Start small. Pick one or two of the areas above. Inventory forecasting and behind-the-scenes content generation are usually the easiest entry points. Give your team time to get comfortable before layering on more.
The retailers who get the most out of AI over the next few years won’t be the ones who adopt the most tools. They’ll be the ones who use AI to free up their people to do more of what actually sells running shoes — paying attention to the person standing in front of them.
about the author
Eric S. Youngstrom is the founder and CEO of Onramp Funds, an innovative fintech that supports the growth of SMB eCommerce businesses. Eric leads a team steeped in eCommerce experience, providing financing and other resources empowering online merchants to grow and scale their businesses.
