Kraft Heinz

As the No. 21 publicly owned consumer goods company globally, Kraft Heinz operates a supply chain of significant complexity — spanning manufacturing, North American distribution, retail partnerships, and agricultural sourcing down to the farm level. Despite employing approximately 50 dedicated data scientists, actionable demand insights remained locked inside technical teams and BI tooling that most operational employees lacked the expertise to navigate independently. When demand signals shifted unexpectedly — a product gaining sudden traction, a competitor going out of stock — getting answers required routing requests through data teams. In a consumer goods environment where shelf dynamics move within days, that bottleneck directly undermined the company's ability to respond with speed and confidence.

Kraft Heinz built KraftGPT, an internal generative AI application powered by large language models, that gives employees self-service access to product sales insights through natural language. The interface — described by SVP Helen Davis as an 'Ask Me Anything' app — allows employees to pose questions like "Why are we selling so much bacon?" directly against the company's data lake without requiring BI expertise. KraftGPT sits atop a broader 'self-driving supply chain' architecture that includes a cognitive decision layer building digital twins of supply chain decision-makers, enabling autonomous adjustments to production schedules and inventory movements. Development is led by 50 data scientists organized into Agile pods under Kraft Heinz's 'Agile@Scale' strategy — each pod working in weekly sprints and reporting quarterly to cross-functional leadership, with data scientists embedded alongside functional leads and IT to feed transactional data continuously into the enterprise data lake.

KraftGPT delivers what SVP Helen Davis called "getting 500 employees making those decisions in an instant" — collapsing a multi-step data request process into a conversational query. The self-driving supply chain initiative, underpinned by digital twin capabilities and the cognitive decision layer, has measurably improved autonomous response to consumer demand volatility, a capability Kraft Heinz explicitly drew from pandemic-era lessons. Key outcomes:

• Operational employees across the organization can query real-time product sales data conversationally, without data team intermediaries
• The Agile pod structure is credited with enabling faster AI deployment than comparable CPG organizations, per Davis's own assessment
• End-to-end supply chain visibility is being extended from retail shelf signals all the way to farm-level partners, shortening competitive response time when rivals go out of stock

• Embedding data scientists within operational Agile pods — rather than centralizing them in IT — keeps AI projects tied to business outcomes and compresses deployment timelines.
• Senior leadership sponsorship and dedicated funding were cited as the primary reasons Kraft Heinz is moving faster on AI than comparable consumer goods peers.
• Natural language interfaces remove the BI expertise barrier, enabling broad employee adoption without retraining at scale.
• Building a cognitive decision layer and supply chain digital twin extends AI value beyond individual tools to organization-wide autonomous decision-making.
• Pandemic-era supply disruptions validated the strategic case for autonomous, real-time demand response — a lesson worth embedding into long-term AI architecture.