Lowe’s is one of the largest home improvement retailers in the world, operating more than 1,700 stores across the U.S. with over 250,000 associates supporting professionals, DIY customers, and large-scale contractors. As a Fortune 50 enterprise, the company’s digital transformation touches everything from supply chain operations and merchandising to in-store execution and customer experience.

The final chapter of this three-part conversation between Chandhu Nair, Senior Vice President, Data, Artificial Intelligence and Innovation at Lowe’s, and Rohit Choudhary, CEO of Acceldata, turns to the leadership mindset shift required for non-deterministic AI, the rise of multimodal retail experiences, culture transformation, and how Lowe’s decides what to build versus what to buy.

Part 1 explored what it means to lead data transformation at scale and why the future of enterprise AI depends on mastering structured, unstructured, and uncaptured data.

Part 2 unpacked Lowe’s multi-year modernization journey, its hybrid infrastructure, and the strategic discipline behind prioritizing high-value AI use cases.

“It’s 30% tech and 70% change management”

Nair opens the conversation by acknowledging that his personal leadership playbook has fundamentally shifted as AI entered the enterprise in a non-deterministic form. “The biggest shift is realizing that it’s 30% technology and 70% change management.”

Rather than treating AI as a purely technical rollout, Nair emphasizes the importance of business operators as co-owners of transformation.

“Do I have the right business operations leader partner who can drive that change alongside the technology teams? How do we bring those change agents into the same equation and move in the same direction? That became critical.”

This mindset led to a change in how Lowe’s experiments, pilots, and scales AI. “With non-deterministic technology, the only way forward is to put it in the field, co-create with the operators, get feedback, and continuously iterate,” Nair elaborates. “You also have to set the right expectations upfront. It might be 60% accurate in the beginning, and that has to be acceptable.”

Nair shares how real-world store behavior shapes Lowe’s AI priorities. “If you are rolling out in-store technology, you’d better walk the stores with your operators,” he says. “You have to see how it actually works for them.”

During the early rollout of the Lowe’s in-store Mylow Companion, Nair’s team discovered something they had not anticipated. “We found that almost 50% of associates were speaking to the device instead of typing, because if you have a customer in front of you, you don’t want to look down and type,” he says. “We quickly pivoted and moved voice to the front of the roadmap since it was a massive adoption driver.”

The lesson was clear. AI roadmaps cannot be designed solely from conference rooms or dashboards. They must be shaped by store floors, associate behavior, and live customer interactions.

How multimodality is redefining the home improvement journey

What excites Nair most today is not just conversational AI, but the full rise of multimodal experiences across voice, images, spatial data, and video.

“In a home improvement store, a lot of customers come in with a picture of something in their house or a paint can with dried color on it,” he explains. “Instead of trying to describe it or type it, imagine taking a picture and letting the Companion identify it for you. That is what we are working toward.”

For DIY customers in particular, Nair describes the deeply fragmented nature of today’s journey.

“You watch a YouTube video, read instructions, look at pictures, walk the store, ask for help, then finally try to figure out what you need,” he says. “That entire journey is multimodal by default. Voice, images, videos. AI can now start bringing that together.”

From visualization to spatial AI

Nair believes visualization will ultimately define the next phase of retail AI. “Fulfilling dreams starts with being able to visualize the kitchen you saw online or at a friend’s house and bringing that to life in your own space within your budget,” he elaborates.

That is where emerging spatial and visualization technologies become critical. Nair points to Lowe’s early work with Apple Vision Pro as a glimpse of what is coming next.

“These are still nascent technologies, but the promise is massive,” he notes. “If a customer is making a big-ticket investment with us, we’d better give them the best visualization possible so what gets built matches exactly what they imagined.”

How Lowe’s built a culture of constant change

According to Nair, none of this transformation would be possible without a deep culture reset across the enterprise.

“Culture starts with leadership setting the tone,” he states. “At Lowe’s, from our CEO to our board and executive leadership team, the message is very simple. How do we improve the experience for all 250,000 associates and every customer? If you keep it that simple, it becomes powerful.”

The next layer is operational.

“You need the right change agents embedded inside core functions — people who drive agile adoption and continuously feed the feedback loop so technology and roadmaps stay aligned to business reality,” he says.

Then comes literacy at scale. “It is AI for all,” Nair shares. “You find everybody from the spectrum of apprehension, optimism, or somewhere in the middle. But you have to introduce awareness and literacy programs to help them with this technology and bring them along this journey.”

At Lowe’s, this commitment takes the form of structured learning through Lowe’s University and external partnerships. The organization created training programs not just for technologists, but also for non-technical teams. “If you want real co-creation, both sides have to operate on the same playing field,” says Nair.

Why agentic AI is the next enterprise turning point

While generative AI has dominated enterprise attention, Nair sees agentic AI as the next major unlock. “Agentic AI has the potential to go far beyond conversations and truly unlock enterprise value creation,” he says. “But to make that real, you have to educate people on how to use it, what the guardrails are, and how it integrates into real workflows.”

Here again, the theme returns to people over platforms.

“It always starts with people, process, and literacy programs all the way from leadership to store teams,” Nair said.

The build vs. buy philosophy

As platform shifts accelerate, Nair acknowledges that deciding when to build and when to partner has only become more complex. But Lowe’s operates under a clear guiding principle.

“If it is differentiating for us, we build. If it is commoditized, we partner,” he shares.

That logic extends directly into AI. “We are not in the business of building large language models. That race is being run by companies investing billions. Our focus is on partnering with the right ecosystem to unlock experiences for customers and associates,” Nair says.

At the same time, Lowe’s treats its data and specialized intelligence very differently. “When it comes to our core data and the intelligence built on top of it, that is absolutely our differentiation. That is where we build and where we invest in hiring the right talent.”

This hybrid model allows Lowe’s to move quickly without surrendering control over the intelligence that defines its competitive edge.

CDO Magazine appreciates Chandhu Nair for sharing his insights with our global community.