Use Case Intelligence RSS Search use cases Search
Microsoft Travel and Hospitality China

McDonald's China

Enterprise Knowledge Search

Core to McDonald's China innovation is AI. The company wanted to explore how using AI could help it increase operational efficiency, reduce costs, and support more data-driven decision-making at scale.

Read the original story Explore all use cases
In 2023, McDonald's China, in collaboration with Microsoft, established the AI Lab to explore the practical implementation of AI in all McDonald's China locations. The Lab is part of the McDonald's IT R&D team.
To help employees stay at the forefront of business innovation while opening nearly 1,000 new locations per year, McDonald's China decided to use AI to elevate all levels of customer service, quality, and operational excellence.
While the golden arches of McDonald's can be found in more than 40,000 locations worldwide, one of the company's fastest-growing markets is China. The fast-food leader got its start there in 1990 and has around 6,000 restaurants on the Chinese mainland.

Reported impact

Business outcome

Core to McDonald's China innovation is AI. The company wanted to explore how using AI could help it increase operational efficiency, reduce costs, and support more data-driven decision-making at scale.

  • Cost Reduction
  • Customer Experience
  • Productivity Improvement
  • Scalability

Solution

To help employees stay at the forefront of business innovation while opening nearly 1,000 new locations per year, McDonald's China decided to use AI to elevate all levels of customer service, quality, and operational excellence. Core to McDonald's China innovation is AI. The company wanted to explore how using AI could help it increase operational efficiency, reduce costs, and support more data-driven decision-making at scale. Amid expansion, McDonald's China remains committed to being a leader in innovation, using technology to elevate all levels of customer service, quality, and operational excellence while also empowering its employees. Core to McDonald's China innovation is AI. The company wanted to explore how using AI could help it increase operational efficiency, reduce costs, and support more data-driven decision-making at scale. The implementation centers on Azure AI Studio, Azure AI Search, Microsoft Teams, GitHub Copilot to support enterprise knowledge search workflows.

Solution architecture

4 components · 2 layers
  1. Serving
    • Azure AI Search Indexes enterprise content and retrieves grounding context for assistant responses.
    • Microsoft Teams Acts as the collaboration surface for prompts, meetings, and shared knowledge.
    • GitHub Copilot Assists developers with code generation and implementation tasks.
  2. Orchestration
    • Azure AI Studio Provides the managed environment for building, evaluating, and governing AI applications.

Architecture clues

  • "Through our long-term, established partnership with Microsoft, we wanted to find ways to use AI to transform operations, empower and train employees
  • To help employees stay at the forefront of business innovation while opening nearly 1,000 new locations per year
  • While the golden arches of McDonald's can be found in more than 40,000 locations worldwide, one of the company's fastest-growing markets is China.

Evidence from the source

Core to McDonald's China innovation is AI. The company wanted to explore how using AI could help it increase operational efficiency, reduce costs, and support more data-driven decision-making at scale.
The AI Lab group chose Microsoft Azure AI for its enterprise AI models, along with foundational models provided by Azure AI Speech and Vision Azure AI Studio Azure AI Search Azure AI Infrastructure are also a part of the lab's generative AI...
To help employees stay at the forefront of business innovation while opening nearly 1,000 new locations per year, McDonald's China decided to use AI to elevate all levels of customer service, quality, and operational excellence.
Transparency Evidence & methodology 65/100 reference value · 80% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value65/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth15/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact0/25
    0 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence80%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence15/20
    3 direct source quotes retained.
  • Date provenance10/10
    The publication date comes from the source page or publisher.
  • Source transparency8/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity6/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. Microsoft

    McDonald's China customer story

    First-party
    https://www.microsoft.com/en/customers/story/1749886282579475320-mcdonalds-china-azure-retailers-en-china
    Source type
    Vendor-published customer story
    Published
    Mar 25, 2024
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes
    • Publication date

Date evidence

  • Published on source page Mar 25, 2024 · Microsoft · First-party
    Open date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.

Related

Similar use cases

See all like this
Microsoft Jan 13, 2026 Hertz Travel and Hospitality Global Hertz needed to modernize hundreds of legacy processes—employee shift planning, roadside-assistance lookups across vehicle manuals on SharePoint, and payroll updates—to improve responsiveness for 26,000+ employees… 11,000+ rental locations in 160 countries Customer Service AutomationEnterprise Knowledge Search Dataverse · Microsoft Copilot Studio · Microsoft Power Platform Microsoft Dec 3, 2024 Cathay Pacific Airways Limited Travel and Hospitality Hong Kong SAR Cathay is a premier travel brand offering flights, holidays, shopping, dining, and wellness. As Hong Kong’s flagship carrier, Cathay Pacific operates a diverse fleet from Hong Kong International Airport, connecting Hong… By automating routine tasks, Microsoft 365 Copilot empowers Cathay’s employees to work smarter and free up… Enterprise Knowledge Search Microsoft 365 · Microsoft 365 Copilot Microsoft Nov 15, 2024 Air India Travel and Hospitality India Facing a rapidly growing passenger base and rising traveler expectations, Air India needed to modernize its customer experience without increasing operational costs. And it gives a beautiful answer that includes the name of the dog along with the policies." To date, AI.g has… Customer Service AutomationEnterprise Knowledge Search Azure AI Search · Azure AI Services · Azure App Service