Walmart's primary view of AI is offensive, focusing on growth opportunities like creating a personalized, multimedia e-commerce experience. This shifts the narrative from AI as merely a defensive efficiency tool to a strategic growth driver, fundamentally changing how people shop.

Walmart measures the ROI of its internal AI tools for product managers using a three-part framework. They track user adoption (3,100 PMs), output accuracy (88% of AI-generated user stories are accepted on the first pass), and efficiency gains (a 75% reduction in time spent on the task).

Walmart demonstrates the tangible revenue impact of mature AI integration. By deploying tools like GenAI shopping assistants, computer vision for shelf monitoring, and LLMs for inventory, the retailer has significantly increased customer spending, proving AI's value beyond simple cost efficiencies.

Walmart leverages agentic AI to learn from its vast complexity across languages, brands, and markets. Instead of slowing them down, this complexity serves as a massive training dataset, making their AI systems smarter and more resilient, creating a unique competitive edge that is difficult for others to replicate.

While initial sales conversations for BPO replacement focus on 50-75% cost savings, customers discover greater value in AI's unique abilities. These include superhuman speed to close business faster, instant scalability for seasonal demand, and unprecedented observability into previously "black box" processes.

For enterprise customers, a "good" translation goes far beyond literal accuracy. It must adhere to specific brand terminology, tone of voice, and even formatting rules like bolding and quotes. This complexity is why generic tools fail and specialized platforms are necessary for protecting brand integrity globally.

Product managers often hit cognitive fatigue from constantly re-formatting the same core information for different audiences (e.g., customer notes to PRD, PRD to Jira tickets, tickets to executive summaries). Automating this "translation" work with AI frees up mental energy for higher-value strategic tasks and prevents lazy, context-poor handoffs.

The biggest impact of AI isn't just generating translations. It's programmatically assessing the quality to decide if a human review is even necessary. This removes the most expensive and time-consuming part of the process, dramatically cutting costs while maintaining quality standards.

In businesses with tight 5-8% margins, like retail, AI-driven efficiencies in areas like customer support aren't just incremental. They become extraordinarily powerful levers for profitability and scaling, fundamentally altering the cost structure of the business.