What challenges did Mitsubishi Tanabe Pharma face before AI implementation?

Incident check times averaged 10 minutes each, delaying rapid response. Security recommendations and alerts were only available in English, impeding understanding for Japanese staff. Growing complexity and volume of cloud-based operations increased the risk of misconfigurations or missed threats. Limited human resources required that security processes be highly efficient. Data utilization for precision medicine and patient care needed a robust, secure cloud foundation.

What was the impact of the AI solution?

Reduced incident check time from 10 minutes to 1 minute per case, saving approximately 550 hours annually. Enabled efficient cloud security management with minimal human resources. Enhanced ability to respond quickly and effectively to security incidents, directly supporting digital transformation objectives.

Source

MicrosoftEvidence: Medium50/100

Mitsubishi Tanabe Pharma streamlines cloud security operations and employee literacy

Use case typeRisk assessmentUpdated Jun 13, 2026

Mitsubishi Tanabe Pharma, a leader in the pharmaceutical industry, sought to improve its cloud security operations amid a company-wide push for digital transformation and data utilization. The company was challenged by the increasing complexity of cloud security, especially as workflows expanded into precision medicine and patient-centric solutions. Security incident checks and alerts primarily in English made rapid response and understanding difficult for its Japanese-speaking team. To address these issues, the firm undertook a comprehensive assessment of its Azure-based infrastructure with Microsoft guidance, adopting Microsoft Defender for Cloud and Microsoft Sentinel for consistent policy enforcement and continuous monitoring. The real breakthrough came with the integration of Azure OpenAI Service, which automated the translation and summarization of security alerts into Japanese and provided clear explanations of threats and recommended actions. This reduced incident handling time tenfold and significantly bolstered employee security literacy. Now, security incidents are handled more efficiently by a lean team, supporting the company's 'VISION 30' strategy for advanced, secure digital healthcare initiatives.

Organization: Mitsubishi Tanabe Pharma
Industry: Pharma
Location: Japan

Reported outcomes

Time: Approximately 10 minutes

Time & speed

Time: Approximately 1 minuteTime: Approximately 550 hours

Why do we believe this?Outcome claims, sources, and evidence checks

Normalized claim

Time: 10 minutes decrease

microsoft.comCustomer storyInferred claimMedium evidence strength

Reduced incident check time from 10 minutes to 1 minute per case, saving approximately 550 hours annually.

Normalized claim

Time: 1 minutes decrease

microsoft.comCustomer storyInferred claimMedium evidence strength

Reduced incident check time from 10 minutes to 1 minute per case, saving approximately 550 hours annually.

Normalized claim

Time: 550 hours decrease

microsoft.comCustomer storyInferred claimMedium evidence strength

Reduced incident check time from 10 minutes to 1 minute per case, saving approximately 550 hours annually.

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks

Customer: Mitsubishi Tanabe Pharma
Provider: Microsoft
Maturity: Unknown
Linked source: microsoft.com

No explicit deployment-stage evidence found.

Customer identity supportedSource describes one deploymentMaturity evidence evaluated

Primary read

Use case focus

Showing 3 of 3

1Automated Security Incident Translation and Summarization for Cloud Operations
2Real-Time Alert Explanation for Cloud Security
3Integrated Cloud Security Monitoring with AI-Driven Language Processing

Incident check times averaged 10 minutes each, delaying rapid response.
Security recommendations and alerts were only available in English, impeding understanding for Japanese staff.
Growing complexity and volume of cloud-based operations increased the risk of misconfigurations or missed threats.
Limited human resources required that security processes be highly efficient.
Data utilization for precision medicine and patient care needed a robust, secure cloud foundation.

Implemented Microsoft Defender for Cloud and Microsoft Sentinel for automated detection, assessment, and continuous monitoring.
Adopted Azure OpenAI Service to translate and summarize English security notifications into Japanese, explaining the significance and risk of each alert.
Integrated security operations, enhancing visibility and policy enforcement based on Azure Well-Architected Framework recommendations.
Automated delivery of digestible, incident-specific security summaries to staff via email and Microsoft Teams, reducing manual review.
Received technical guidance and knowledge transfer from Microsoft for successful cloud security and AI integration.

Technologies

Azure OpenAI Microsoft Defender for Cloud Microsoft Sentinel

Reduced incident check time from 10 minutes to 1 minute per case, saving approximately 550 hours annually.
Enabled efficient cloud security management with minimal human resources.
Enhanced ability to respond quickly and effectively to security incidents, directly supporting digital transformation objectives.

Architecture

The solution architecture includes Microsoft Defender for Cloud as a central platform for managing security policies and workloads, integrated with Microsoft Sentinel for SIEM functions—collecting and analyzing security logs, managing identity-based access, and issuing automatic alerts. Azure OpenAI Service is used to process incident messages: translating, summarizing, and annotating security alerts into Japanese, then distributing them via email and Microsoft Teams. The automation leverages Azure Logic Apps for workflow orchestration, connecting Defender for Cloud and Sentinel incident data to OpenAI and onward notification channels.

Sources & evidence1

Evidence: Medium50/100Evidence strength