Upcoming Research On Digital Twins For Data Centers

2026-02-26 · Source: Featured Blogs - Forrester · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Cloud Computing & IT Infrastructure, Internet of Things (IoT) & Connected Devices · Depth: Intermediate, quick

Summary

New research is commencing on digital twins for data centers, focusing on identifying available solutions, expected benefits, and high-ROI use cases. A digital twin is defined as a continuously updated virtual model of a physical system, synchronized with real-time sensor data, analytics, and AI, enabling pre-validation of decisions. Applying this technology to data centers aims to optimize performance, reduce risk, and accelerate operations by transforming organizations into data-driven operators. Initial research will prioritize quickly achievable value, such as scenario-testing infrastructure decisions. A key challenge, posed by Dr. Tim Shedd of Dell Technologies, is to identify use cases that offer substantial value beyond static analysis and justify the cost of a digital twin platform without requiring supercomputing resources.

Key takeaway

For Research Scientists evaluating new data center management technologies, you should prioritize digital twin solutions that demonstrate clear, quantifiable ROI beyond what static analysis or basic monitoring can provide. Focus on use cases that address critical operational challenges and offer substantial value, such as optimizing resource allocation or pre-validating complex infrastructure changes, to ensure the technology adoption is justified by tangible benefits.

Key insights

Digital twins offer real-time virtual models for optimizing complex physical systems like data centers.

Principles

• Value must exceed static analysis.
• ROI justifies technology adoption.

Method

Research will explore existing digital twin solutions for data centers, evaluate their expected capabilities, and identify specific use cases that deliver significant return on investment.

In practice

• Scenario-test infrastructure decisions.
• Optimize data center performance.
• Reduce operational risk.

Topics

• Digital Twins
• Data Center Management
• Performance Optimization
• Real-time Analytics
• ROI Analysis

Best for: Research Scientist, MLOps Engineer, AI Architect, Business Analyst

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Editorial summary, takeaway, and curation by AIssential. Original article published by Featured Blogs - Forrester.