Reinventing the Retail Wheel

The Challenge of Fragmented Experiences

CarMax, the largest used car retailer in the U.S., found itself at a crossroads as consumer expectations evolved toward digital-first experiences. Customers increasingly demanded seamless online journeys without sacrificing the ability to walk into a store when needed. Still, the company’s existing systems, workflows, and organizational structure were designed for a brick-and-mortar world.

Digital capabilities were added later, but not deeply integrated. Shamim Mohammad, EVP and Chief Information and Technology Officer, saw an urgent need for a full-scale digital transformation. The traditional approach to car appraisals required customers to visit a store and wait for a manual review process, forcing the company to rethink its current operations.

CarMax reinvented its operations with AI at the core to meet customers where they were, increase operational agility, and unlock growth through automation and data. Anchoring its transformation was an AI architecture that redefined appraisals, content generation, and customer interaction, resulting in an AI-powered customer experience that scales with speed, precision, and intelligence.

Shortcomings of Legacy Retail Operations

For decades, CarMax’s value proposition was built on trust and transparency: rigorous vehicle inspections, fixed pricing, and no-haggle offers. But as customers migrated online, the company’s underlying systems weren’t keeping up. CarMax’s processes were not optimized for a modern, digital-savvy customer base.

Customers had to bring their vehicles into a store for manual appraisals, leading to slow turnaround and poor customer convenience. The few existing online tools and processes were fragmented from those in-store, causing friction and loss of momentum in the buyer journey. The company’s success at scale exposed gaps in its ability to quickly introduce new features, automate content, or respond to shifting market dynamics. 

They needed a radical shift to stay competitive, rebuilding their culture and technology stack with AI and automation at the center. Mohammad recognized that incremental upgrades wouldn’t cut it. “If you want to disrupt, you have to disrupt. You cannot just try little things here and there. For us, we went all in,” he said.

Implementing AI-Driven Retail Transformation

CarMax’s reinvention began by restructuring its operating model. Instead of traditional IT-led projects, the company shifted to autonomous, product-led teams with end-to-end accountability, empowering employees to iterate rapidly, experiment, and own customer-facing experiences. These cross-functional units worked in sprints, testing features and releasing updates without waiting on centralized cycles. With this agility in place, CarMax deployed a suite of AI-powered capabilities designed to bridge the physical-digital divide.

Customers can now upload vehicle details via the CarMax app and receive real-time, AI-powered online appraisals. These machine learning models are trained on millions of past transactions, market prices, and vehicle histories. The company also invested in a cloud-based data estate, enabling scalable AI development and ensuring clean, structured data pipelines across business units.

CarMax also automated the generation of vehicle descriptions and customer review summaries, producing thousands of data-driven writeups to give shoppers clearer, more digestible information. AI-enabled systems now bridge the gap between CarMax’s digital and physical retail, ensuring the customer experience remains seamless and personalized, whether they begin their journey online, visit a store, or switch between both.

Shamim says, “I believe our approach is the best and most comprehensive in our industry because we have a 360-degree view of the customers through all channels. This equips the customers and our associates with the information they need, so if a customer contacts someone, the associate knows exactly what the customer has done.”

Implementation followed a modular, layered rollout. Core infrastructure, including data normalization and cloud migration, came first, followed by customer-facing intelligence. Over time, these models became embedded in daily operations, creating a closed loop of learning and iteration.

Measurable Impact and Results

CarMax’s investment in applied AI paid off quickly. The company unlocked speed, precision, and scale by integrating machine learning across its vehicle lifecycle and retail stack.

• Real-time appraisals: Quotes that once took days are now delivered in under two minutes. This has drastically reduced friction and improved quote conversion by enabling customers to act faster.
• Faster content creation: Generative AI shortened the time-to-market for inventory listings, ensuring descriptions were published as soon as vehicles were ready for sale.
• Agile product cycles: Autonomous teams could build, test, and release features in weeks instead of months, accelerating time-to-value and reducing cross-team dependencies.
• Scalable backend: With cloud-native infrastructure, the company now supports rapid experimentation, scalable personalization, and advanced MLMs without increasing technical debt.
• Unified customer journey: Appraisal history, saved searches, and service preferences now follow users across devices, creating a seamless experience regardless of entry point.

According to Shamim, CarMax has seen marked increases in appraisal volume and customer engagement, alongside NPS and digital conversion improvements. These improvements have optimized and redefined what car retail looks like.

Continuously Innovating and Improving

What makes CarMax’s transformation unique is its repeatability. AI wasn’t bolted on—it was built into the operating system. Feedback loops now power model refinement, while every customer interaction informs future product evolution.

Mohammad has developed a self-improving ecosystem at CarMax. Whether optimizing appraisal accuracy, content clarity, or test-and-learn releases, AI will continue to play a role across the business: “I think we’re just scratching the surface with machine learning and AI. I’m most excited about that.”

With foundational systems in place, CarMax is exploring deeper layers of personalization, matching users with ideal vehicles based on lifestyle signals, and expanding AI into back-office functions like supply chain optimization, service scheduling, and customer care. By standing at the forefront of AI-powered retail innovation, the company is now poised to lead the industry's future.