Albert Heijn Empowers Store Employees with AI Assistant

Albert Heijn, a leading Dutch supermarket chain, faced challenges in a tight labor market and aimed to optimize processes for their largely young, part-time workforce. To address this, the company developed a conversational AI assistant within its @AH Employee App using Azure OpenAI, Azure Kubernetes Service, and Azure Database PostgreSQL. The assistant answers store employees' questions related to their tasks and customer service on their mobile devices. The implementation, co-developed with Microsoft and EPAM, was rooted in deep user involvement: store employees contributed to the design, which led to high adoption and usability. The assistant integrates with barcode scanning and floorplanning features for product search and shelf management. Pilots across several stores showcased improvements in process efficiency and employee satisfaction. The tool delivers instant, in-context answers for everyday tasks, reducing the need for managerial support and enabling a more independent workforce. The generative AI platform on Azure ensures scalability and means the solution is ready to roll out to all owned stores. Its cultural impact has been significant, fostering excitement and a forward-looking mindset among staff. The project is setting a new standard for employee digital experience in retail and is expected to contribute to talent retention and workplace productivity. The adoption journey involved iterative prototyping and close feedback, ensuring the solution matched real-world workflows and generational preferences.

Organization
Albert Heijn
Industry
Retail
Location
Netherlands

Reported outcomes

Strategic outcomes

New product / capabilityLaunched conversational employee AI assistantSpeed & agilityImproved store workflow efficiencyEmployee experienceIncreased employee autonomy and satisfactionScale & capacityPrepared rollout across owned stores

Primary read

Use case focus

Showing 3 of 3

  • 1Conversational AI Assistant for Store Employee Support
  • 2Mobile Task Guidance and Workflow Optimization for Retail Staff
  • 3Automated Product Location and Stock Enquiry via AI
  • Tight labor market and growing need to retain young talent.
  • Inefficient, labor-intensive store processes like shelf restocking and customer assistance.
  • Many employees are minors with limited experience, hesitant to seek help from management.
  • Store employees often lacked quick, contextual answers to workflow and customer queries.
  • The company needed to drive technology adoption among a digitally native, Gen Z workforce.
  • Developed a conversational AI assistant in the @AH Employee App using Azure OpenAI.
  • Built on Azure Kubernetes Service and Azure Database PostgreSQL for scalability and integration.
  • Collaborated closely with Microsoft and EPAM for technical expertise and iterative design.
  • Included features like barcode scanning and digital planograms for efficient stock and product location support.
  • Conducted pilots and iterative prototyping with strong employee feedback and involvement.
  • Early pilot results showed clear increases in store efficiency and workflow optimization.
  • Store employees reported higher job satisfaction and a greater sense of autonomy.
  • Managerial workload associated with employee queries was reduced.
  • Cultural shift toward increased technology adoption and digital fluency in day-to-day work.
  • Platform ready for expansion to all 700 owned stores, covering over 80,000 employees.
Architecture

The solution runs as a conversational AI assistant embedded into the @AH Employee App. The backend leverages Azure OpenAI for generative conversational intelligence, is containerized and scaled using Azure Kubernetes Service, and manages structured/store and product data using Azure Database for PostgreSQL. The app integrates barcode scanning, floorplans, and planograms, providing real-time task-oriented assistance. The technical approach allowed for continuous feedback and adaptation to store environments.

Implementation partners1
Sources & evidence1
Groundedness: Unavailable

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