One of the more practical AI business cases in retail right now is coming from Lowe's, and it matters because the company is not framing AI as a novelty feature. It is using one assistant system, Mylow, to improve customer conversion, strengthen associate product knowledge, and push routine work out of the way of sales. In late May 2026, reports on Lowe's first-quarter comments said customers using Mylow were converting at roughly 3x the rate of non-users, the tool was handling more than 1 million inquiries per month, and in-store satisfaction had improved by about 2 percentage points.
Those numbers build on an earlier update from February 26, 2026, when Lowe's CEO Marvin Ellison said Mylow had already doubled online conversion rates since rollout, helped break product-knowledge bottlenecks on the sales floor, and improved service in bilingual environments through Spanish-language support. He also said internal teams in merchandising and technology were using AI to free time for more strategic work, with tech teams seeing double-digit productivity gains.
That combination makes this more useful than a typical AI retail demo. Lowe's is not claiming that a chatbot made the business magically smarter. It is showing that AI becomes commercially relevant when it sits directly inside the buying workflow: helping customers find what they need, helping associates answer harder product questions, and reducing the friction that usually separates online browsing from store conversion.
The strongest retail AI systems do not just answer questions. They remove hesitation at the exact moment a customer or associate would otherwise stall.
What Lowe's Actually Built
Lowe's has been building this in layers rather than in one big reveal. In May 2025, the company rolled out Mylow Companion across more than 1,700 stores. The tool gives associates AI-generated answers about products, inventory, and home-improvement guidance through the handheld devices they already use. The company positioned it as a way for workers with very different experience levels to deliver more expert answers without waiting for a specialist.
Alongside that store tool, Lowe's also launched the customer-facing Mylow shopping assistant. The structure matters. Many retail AI efforts stop at the customer-facing layer and ignore the employees who actually have to complete the sale, answer follow-up questions, or handle uncertainty around fit, inventory, and repair. Lowe's built both sides: customer assistant for buying guidance, associate assistant for confidence and response speed.
That gives the system a much better shot at changing behavior. Home improvement is a category where product complexity is real. Customers are not just choosing between two identical T-shirts. They are trying to diagnose why an oven will not heat, what kind of sealant works outdoors, or which tool matches a specific repair. If AI can answer that faster and more accurately, conversion should improve because uncertainty falls.
Ellison's comments suggest that is exactly the point. He described new hires as often lacking confidence in specialized product knowledge and said Mylow fills that gap. That makes this an adoption story about capability distribution. Instead of waiting for every employee to accumulate the same hard-won expertise, the company is making a useful slice of that knowledge available at the moment of interaction.
Why This Looks Like a Strong Business Case
The first reason is that the metrics tie directly to commerce. 3x conversion is not a soft engagement number. It points at the part of AI adoption that boards actually care about: whether the tool changes buying behavior. Even the earlier 2x conversion figure from February was already meaningful. The later May reporting suggests the commercial effect may be strengthening as usage scales and the system improves.
The second reason is that the gains show up across both digital and physical retail. Many AI stories in commerce are trapped online. Lowe's case is broader. The same AI layer is reportedly helping customers online, helping associates in stores, and improving in-store satisfaction. That is more important than it looks. Retail economics are shaped by channel handoffs, not by one isolated interface. A customer often starts online and finishes in person, or begins in store and confirms later through digital research. Lowe's is applying AI across that boundary instead of on one side of it.
The third reason is that the use case is attached to a real source of friction. Product knowledge is a genuine operational bottleneck in home improvement retail. When staff are unsure, customers lose confidence and purchases slow down. AI is being used here not for generic marketing copy or vague personalization, but to address the exact moment where uncertainty blocks a sale or lowers service quality.
The fourth reason is that Lowe's is describing broader operational spillover. Ellison said merchandising teams are being freed from routine work so they can focus on more strategic problems, and tech teams are using AI in software development and code review with double-digit productivity gains. That matters because the strongest business cases tend to spread. Once a company trusts AI in one workflow and builds the controls around it, adjacent workflows become easier to redesign.
What Other Companies Should Copy
Most companies will not copy Lowe's exact stack, but they should copy the operating logic.
- Put AI at the point of hesitation. The best gains appear where customers or employees get stuck, not where the organization merely wants a smarter interface.
- Support both the customer and the employee. If the assistant helps only one side of the interaction, the workflow still breaks in the handoff.
- Target high-friction knowledge work. Product complexity, policy nuance, or diagnosis-heavy buying journeys are much better AI targets than generic FAQ automation.
- Measure business outcomes, not adoption theater. Conversion, satisfaction, and time returned to teams are more useful than prompt counts or internal hype.
- Reuse the system across functions. Once the assistant layer proves useful in commerce, the same pattern can extend into merchandising, engineering, and support.
This matters well beyond retail. Any business with a complicated buying journey can borrow the pattern. Insurance, healthcare services, banking, industrial distribution, and B2B software all face the same core problem: customers and front-line staff hit moments of uncertainty that slow revenue. AI becomes useful when it reduces that friction in real time.
The Caveats
The biggest caution is that these numbers are still company-reported through executive commentary and media coverage rather than an independent audit. We do not get a full ROI bridge showing how much gross margin or incremental revenue came from the higher conversion rates. We also do not know how the May 3x conversion figure was measured relative to the February 2x disclosure, or how usage varies by category, store type, or customer segment.
There is also a category effect. Home improvement is unusually well suited to this kind of assistant because customer questions are frequent, practical, and tightly connected to purchase decisions. A simpler retail category may not produce the same lift. The lesson is not that every company should copy Lowe's headline number. It is that AI works best when the workflow contains real knowledge friction and a visible commercial decision on the other side of it.
The Business Takeaway
Lowe's is a strong 2026 AI business case because it shows that retail AI pays off when the assistant is attached to a concrete operating bottleneck: product knowledge, buying confidence, and answer speed. The tool is not sitting on the side as a novelty layer. It is helping people move from question to purchase more efficiently.
If you are building your own AI adoption case, the lesson is straightforward. Find the place where uncertainty slows conversion or service, where employees repeatedly answer the same difficult questions, and where faster confidence changes the business outcome. Put AI there first. That is where it starts behaving like operating leverage instead of software theater.
Sources & Further Reading
- Business Insider: Lowe's CEO says its AI assistant is fixing some major headaches — February 26, 2026 reporting on Mylow's doubled conversion rate since rollout, 2-point in-store satisfaction lift, Spanish-language support, and double-digit productivity gains for tech teams
- The U.S. Sun: Lowe's customers say hello to new way of shopping as DIY giant launches "unique" tool — May 28, 2026 reporting on first-quarter comments that Mylow handles more than 1 million inquiries per month, drives 3x conversion for users, and contributes to a 2% satisfaction increase
- Houston Chronicle: Lowe's rolls out new AI tool to help answer customers' questions in stores — May 9, 2025 coverage of the Mylow Companion rollout across 1,700+ stores and Lowe's collaboration with OpenAI for associate product and inventory guidance