Artificial intelligence is moving quickly, but for many self-storage operators the most important questions are still very practical. Where does AI actually help? What is realistic today? And how do you start using it without creating more confusion, risk, or busywork?
To help answer those questions, we spoke with Ben Mikiten, Senior AI Enablement Manager at Storable. Ben works across the company helping teams find practical ways to use AI in their day-to-day work, from training and governance to workflow design and hands-on problem solving. What follows is our conversation about what good AI adoption looks like, where operators can find early wins, and why starting small matters.
What does your role at Storable involve, and what does a typical day look like?
I lead AI Enablement at Storable — a small team responsible for helping every department across the company find practical ways to use AI in their actual work. My role spans training, strategy, governance, and hands-on support.
A typical day is a mix of three things: coaching sessions where I sit with someone from accounting or client success and help them solve a real problem with AI; strategic work like designing workshops, building governance frameworks, or reporting adoption metrics to leadership; and building. I use AI tools extensively myself, both to model what good adoption looks like and to create internal platforms that make the whole program run smoother. No two days look the same because I’m serving 40+ teams at very different starting points.
How is the adoption of AI tools changing the way Storable works internally? Can you share a few examples, and explain how those changes ultimately benefit customers?
The short version: people are doing in minutes what used to take hours, and the quality is often better because the tedious parts aren’t being rushed anymore.
A few concrete examples: One person on our implementations team built a suite of automations that absorbed 37% more setup volume without adding headcount. Customers get onboarded faster. A team in client success built agents that eliminated 60-80 hours of weekly manual work across their group. That time goes back into proactive customer outreach instead of data entry. Our finance team automated a report that used to take hours of manual consolidation, now leadership gets fresher data to make better decisions with.
The pattern is the same: AI handles the repetitive cognitive work, humans spend more time on judgment and relationships. As a result, customers experience faster responses, fewer errors, and people who actually have time to help them.
How should self-storage operators think about rolling out AI in their organizations today? What can AI realistically help them do?
Start with what’s already annoying.
Every organization has work that’s repetitive, high-volume, and low-judgment: answering the same customer questions, pulling together reports, writing follow-up emails, summarizing calls. AI is excellent at that stuff today. It’s not science fiction; it’s a really good intern that never gets tired.
For self-storage operators specifically, I’d think about: customer communication (drafting responses, summarizing interactions), operational documentation (turning tribal knowledge into actual procedures), financial reporting (consolidating data from multiple properties), and marketing (generating listing descriptions, seasonal campaigns, social content).
The key framing: AI doesn’t replace your experienced operators. It removes the friction that prevents them from doing their best work.
You probably hear a mix of healthy skepticism and misplaced fear when it comes to AI. How do you tell the difference, and how cautious should operators be?
Healthy skepticism sounds like: “How do I know this output is accurate?” or “What happens if it makes a mistake with customer data?” Those are exactly the right questions — they lead to good guardrails.
Misplaced fear sounds like: “AI is going to replace all my employees” or “I can’t use it because it might get something wrong.” The first misunderstands what AI does well (augmentation, not replacement). The second applies a standard of perfection that humans don’t meet either.
My advice: be cautious about letting AI make final decisions with real consequences. Always keep a human checking anything customer-facing or financially significant. But don’t be so cautious that you never start. The risk of waiting is real too. Your competitors are already experimenting, and the compound advantage of starting earlier is significant.
What are you most excited about when you think about Storable’s use of AI over the next year?
I’m most excited about the compounding effect. Right now, we have individual people doing impressive things. Over the next year, that becomes organizational. Teams will have documented, optimized workflows. New hires will onboard into AI-augmented processes from day one. The distance between “idea” and “working solution” will keep shrinking.
Specifically: I’m excited about AI moving from a tool people use occasionally into the background infrastructure of how work happens — not as a big transformation project, but as the new normal. When someone joins Storable and AI-assisted workflows are just how things work here, that’s when we’ve won.
For an operator who is curious but has not really started yet, what would a smart first 90 days look like?
Days 1-30: Learn by doing, personally. Pick one tool — ChatGPT, Claude, Gemini, whatever — and use it every day for 30 days. Don’t try to transform your business yet. Just use it for your own work: drafting emails, summarizing documents, brainstorming marketing copy, asking questions about your lease agreements. Build intuition for what it’s good at and where it falls short.
Days 31-60: Find your first workflow. Identify one repetitive process that eats time across your team — maybe it’s responding to online inquiries, generating move-in paperwork, or compiling weekly occupancy reports. Map out how it works today, then experiment with AI handling pieces of it. Keep a human in the loop.
Days 61-90: Expand with guardrails. Take what worked and make it repeatable. Document the process so others can use it. Set clear rules about what AI handles vs. what humans review. Start the next workflow. Congratulations — you now have an AI adoption program.
The through-line: start with yourself, expand to one process, then systematize. Don’t try to boil the ocean.
Putting AI in motion
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