Home Depot’s Fran Bell and Angie Brown build AI across stores, tech, and delivery

Home Depot’s AI push is no longer confined to experiments. Over the past few years, the home-improvement retailer has been rebuilding parts of its business with artificial intelligence aimed at making shopping easier for customers and boosting efficiency for workers. The twist is that this expansion is happening alongside a leadership refresh in the technology function, with the company putting major responsibility for AI strategy, infrastructure, and customer experience into a changed C-suite.

In April, Franziska “Fran” Bell became Home Depot’s chief technology officer, after previously serving as chief data, AI, and analytics officer at Ford Motor. Eleven months earlier, Angie Brown, a 27-year Home Depot veteran, became chief information officer. Add Jordan Broggi, who became executive vice president of customer experience and the online channel in June 2024, and you get a tech leadership lineup tasked with connecting AI to the realities of physical stores, contractors, and delivery operations. The “why” is practical, not buzzword-y: Brown says the AI investments need to tie to three core priorities, including supporting merchandising inside physical stores, cultivating an interconnected retail ecosystem across digital channels, and growing business with contractors and builders who typically spend more than DIY shoppers.

The AI programs under this leadership span both the front end and the back end. One of the flagship shopper tools is an AI assistant called Magic Apron, which debuted in March 2025 and is powered by generative AI trained on Home Depot product data and contextualized for use cases. But Magic Apron came with a real lesson early in its lifecycle: when Home Depot launched it, Broggi said, “the consumers loved it and the pros hated it.” The problem, according to the company, was that the web-based Magic Apron system was asking “pros” questions that were too simplistic. In response, Home Depot pulled the pro version offline and is fine-tuning the large language models for a better experience for that group of shoppers.

Magic Apron isn’t only for customers. It can also field questions from employees, and Brown says Home Depot is rolling out additional functionality to their smartphones. She also points to a future upgrade that will make the tool multilingual. Underneath the product details is a governance mindset: Brown says she does not approach AI with a restrictive mindset about reducing the number of use cases. She rhetorically asks, “Am I going to limit the number of use cases that can leverage AI to solve a problem?” and says, “I don’t want to. If AI can help solve those problems that we have already identified from a business perspective, I’m not going to hold them back.” In other words, the company is trying to connect AI capability to identified business problems rather than cherry-picking only a few large bets.

Home Depot’s AI work also reaches customer service and delivery reliability. The article highlights a customer service AI system built with Google Cloud that was recently tested in 50 stores. During the pilot program, the voice agents proved they could understand what a customer was calling about in 10 seconds. Meanwhile, another internal effort, known as “order intelligence,” looks backward at millions of data points from past deliveries to assess a risk score. That score can incorporate practical issues like whether a property may require a gate code, or whether a site sits on a winding, narrow path where a 22-foot delivery truck is better than a 36-foot truck. The system can then proactively reach out to customers about potential problems and provide more accurate delivery times. Broggi makes the customer framing explicit: customers do not need to care that generative AI is working in the background. “They just want their stuff delivered on time, complete, undamaged, and with clear communication,” he added.

This operational focus is happening during a tough macro backdrop that matters for retail AI because budgets and demand are cyclical. Home Depot, ranked No. 25 on the Fortune 500, has shown resilient sales even with a muted economy. The company is navigating inflation fears from the war in Iran that have dampened consumer sentiment. Last month, Home Depot reported net sales grew 4.8% in the fiscal first-quarter from year-ago levels, even though it acknowledged homeowners were delaying larger projects due to worries about higher gas prices, layoffs, and other economic uncertainties. The challenges are heightened for the spring market, traditionally the busiest for housing. And the housing market weakness is tied to stubbornly high interest rates and rising building material expenses. For retailers and technology leaders, that context matters because AI must justify itself in efficiency gains and better conversion when customers are more cautious.

On the leadership and operating model side, the article describes a division of responsibilities among the top technologists. Brown has oversight of the company’s technology strategy, infrastructure, cybersecurity, and software development. Broggi oversees Home Depot’s $25 billion e-commerce business, merchandising, and customer experience for digital channels. Bell steers product management, data, and AI. Broggi’s responsibilities also include strategic bets aimed at how shopping may shift when consumers spend more time inside AI chatbots. The company is developing a generative engine optimization strategy, known as GEO, as consumers increasingly shop on AI chatbots like Google’s Gemini, OpenAI’s ChatGPT, and Claude. Home Depot allows shoppers to browse for its goods on ChatGPT and supports Google’s Universal Commerce Protocol, which advocates for a common language to support agentic commerce.

But the hard part is not just building AI experiences. It is defining the retail strategy for those platforms. Broggi says, thus far, the retail strategy for the AI shopping platforms has not been clearly defined, and he notes that AI companies developing the platforms have changed priorities a couple of times. He says they have “got to try to figure out how they want to go to market.” For boards, founders, and tech executives watching Home Depot, the second-order takeaway is that AI deployment is becoming a moving target: leadership alignment, platform volatility, and continuous tuning (like fixing Magic Apron for pros) are turning into the new normal for retail transformation.