MicrosoftExpandedEvidence: Medium45/100

EY boosts European Manufacturing AI Adoption Insights

Use case typeAI platformUpdated Jun 13, 2026

This use case explores the findings of an EY and Microsoft survey conducted among 86 manufacturing companies across Europe, providing a comprehensive overview of AI adoption levels, key challenges, and technology enablers. The survey found that while 81% of the companies considered AI increasingly important for their business, only 10% have a detailed AI implementation plan. Manufacturers using Microsoft AI, Azure AI, Azure Digital Twins, and chatbots are leveraging these technologies for predictive maintenance, supply chain resilience, field operations, and improving customer and employee engagement. The report details typical stumbling blocks, such as poor data quality, lack of governance, and cultural resistance, which impede AI scaling. Best-practice organizations are characterized by engaged executive leadership, a holistic approach to data and solution architecture, and continuous upskilling of the workforce. The use case highlights the importance of cross-functional collaboration, robust data governance, and engaging partners to unlock the transformative value of AI in manufacturing. Success stories revolve around tangible impacts: cost reductions, better decision-making, streamlined operations, and improved product quality.

Organization
EY
Location
EU
Published
May 2025
Why do we believe this?Outcome claims, sources, and evidence checks

Normalized claim

Cost: 20%

EY InsightsMay 5, 2025UnknownInferred claimMedium evidence strength

Manufacturers using AI reported up to 20% cost reductions.

Normalized claim

Quantified impact: 64%

EY InsightsMay 5, 2025UnknownInferred claimMedium evidence strength

Noted CAGR of 64% in AI partnerships or acquisitions within manufacturing.

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
Customer
EY
Provider
Microsoft
Maturity
Unknown
Linked source
EY Insights

No explicit deployment-stage evidence found.

Customer identity supportedSource describes one deploymentMaturity evidence evaluated

Primary read

Use case focus

Showing 3 of 4

  • 1Predictive Maintenance for Industrial Equipment
  • 2Supply Chain Resilience with Digital Twins and AI
  • 3AI-powered Chatbots for Operations and Support
  • Surveyed 86 manufacturing firms on AI practices and outcomes.
  • Promoted best practices of using Microsoft AI and Azure AI tools for enterprise solutions.
  • Adoption of Azure Digital Twins and chatbots for predictive maintenance, supply chain, and cyber-risk management.
  • Instituted data units and company-wide data governance for AI readiness.
  • Encouraged C-suite leadership and broad upskilling for effective AI transformation.
Firms with mature AI practices experienced better supply chain resilience and product lifecycle management.
Architecture

Manufacturing companies integrate smart sensors, IoT, and Microsoft AI/ Azure AI to enable predictive maintenance. Data lakes structure the data flow for analytics. Azure Digital Twins provide virtual representations for simulation and supply chain optimization. Chatbots leverage natural language processing for customer and employee interactions. A data governance framework orchestrates these technologies alongside a digital committee and company-wide data unit.

Sources & evidence2
Evidence: Medium45/100Evidence strength
  • Customer explicitly identified
  • Quantified outcome available
  • Technical implementation details available
  • Multiple corroborating sources available
ExpandedExpanded

The same organization appears in newer AI deployment evidence.

  • Same organization re-documented as recently as 2026.

Measures whether this deployment's public evidence persists — not whether the system is still in production.

Published: May 5, 2025Publisher: EY Insights

AI-generated summary. Verify important details with the linked sources before relying on this case.

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