Artificial Intelligence is getting harder for self-storage operators to ignore. But for many owners, the biggest question is not whether AI can be useful, but how to make sure it is used safely.
To help answer that, we turned to Luke Lenzen, VP, Technology at Storable, to address the fears many operators have about jumping headlong into the AI revolution. He takes a practical and grounded approach to implementing this new technology, noting that safe adoption is about putting proper guardrails in place around how tools are used, what data they can access, and where human review still matters.
What follows is a Q&A built around the most common safety and security concerns self-storage operators have today.
For a skeptical self-storage owner, what does it actually mean to adopt AI safely — and what should they not be afraid of?
Luke: Adopting AI safely does not mean handing control of your business to a black box. It means treating AI like any other business system: start with a defined use case, set clear permissions, keep human review where it matters, and understand what data is going in and what kind of output is coming back. Owners should not be afraid of AI “thinking for itself” or suddenly acting on its own. The more realistic risks are familiar ones: poor setup, weak vendor controls, bad data handling, or people trusting output without checking it. Safe adoption comes from discipline, not fear.
When an operator turns on an AI-powered tool, what controls can they put in place so it cannot do something harmful or out of bounds?
Luke: The best controls look a lot like the controls good operators already use elsewhere. Limit access. Define approved uses. Keep a human in the loop for sensitive tasks. An AI tool should not be able to send money, change contracts, alter tenant accounts, or publish customer-facing content without the right review and permissions. A smart starting point is role-based access, approved workflows for common tasks, logging where possible, and a clear line between assistive use cases and decision-making use cases. In general, AI can help draft, summarize, and surface information, but people should approve anything with financial, legal, operational, or reputational impact.
Tenant data feels like a potential risk. How can operators make sure AI tools are not putting sensitive information or the business itself in danger?
Luke: That concern is valid, and it should be one of the first conversations you have with any AI vendor. Operators need to know what data the tool can see, where that data is stored, whether it is encrypted, whether it is used to train broader models, and how long it is retained. In most cases, sensitive tenant, payment, identity, and internal business data should only be used in systems with clear contractual protections and strong administrative controls. The safest path is usually the simplest one: minimize exposure, share only what is necessary, work with vendors that make strong privacy commitments, and avoid free or consumer-grade AI tools for workflows involving customer information.
Phishing and scams are getting more sophisticated with AI. What should storage teams watch for?
Luke: AI is making scams more believable, but not fundamentally different. Teams should expect better-written phishing emails, more convincing fake invoices, more polished impersonation attempts, and even voice or message fraud that feels more legitimate than older scams. The red flag is no longer sloppy grammar. It is urgency paired with plausibility. A simple playbook still works well: slow down, verify through a second channel, never trust payment or credential requests based on email alone, and escalate anything unusual even if it looks right. For smaller teams especially, the most valuable habit is pausing before you click, pay, or share and verifying first.
Most storage businesses do not have large IT teams. How can smaller operators build an AI-aware culture without making security feel overwhelming?
Luke: Smaller operators do not need a formal governance department to be responsible. What they need is a simple operating model: approved tools, clear boundaries, and practical staff guidance. That can start with a short policy explaining what AI can be used for, what data should never be entered, and when human review is required. From there, lightweight training around real scenarios can go a long way, whether that is drafting marketing copy, summarizing internal notes, or recognizing suspicious emails. The goal is not to make teams afraid of AI. It is to make them comfortable using it thoughtfully.
For owners who are still hesitant, what is the risk of waiting on AI versus adopting it carefully with safeguards in place?
Luke: There is very little downside to being cautious, but there is real downside to standing still for too long. Operators who wait may fall behind in efficiency, customer responsiveness, staff productivity, and their ability to make sense of growing amounts of business data. At the same time, rushing in without controls is also a mistake. The better posture is to move carefully with narrow use cases, clear guardrails, and trusted vendors. The long-term risk is not AI itself. It is letting competitors learn how to use it responsibly while you are still deciding whether to engage at all.
Final Thoughts
For self-storage operators, safe AI adoption does not have to start with a giant leap. It can start with a few well-bounded use cases, better vendor questions, and a clear understanding of where human judgment still belongs. That is often enough to reduce risk while still moving forward.
If you want to see how AI can support everyday workflows in self-storage, explore Storable’s approach to AI here.
