AI is transforming data centres, promising greater efficiency, automation, and optimisation. However, many facilities struggle to harness its full potential due to fragmented, unstructured data. This article from Willow Williams explores why AI alone is not the solution—without structured, reliable information, its impact remains limited.

AI is reshaping infrastructure, but are data centres ready? 

AI is transforming everything—from how we design buildings to how we manage infrastructure. But what happens when AI meets data centres? 

For an industry that powers cloud computing, AI training, and global digital services, you would expect data centres to be leading AI-driven optimisation. Instead, many are struggling to keep up. Why? Because AI is not a standalone solution—it is only as effective as the data it processes. 

Many organisations are investing in AI, expecting immediate efficiency gains, but they are overlooking a fundamental challenge: data in its current state lacks the structure, connectivity, and reliability AI requires to function effectively. 

This is where the Golden Thread becomes critical—not just as a compliance framework, but as the foundation for AI-driven efficiency, risk mitigation, and long-term resilience. 

The data challenge: Why AI alone won’t fix data centre operations 

AI is often presented as the ultimate solution to operational inefficiencies in data centres. Predictive maintenance, automated monitoring, intelligent workload distribution—it all sounds promising. 

However, AI cannot deliver these benefits without well-structured, high-integrity data. The reality is: 

  • AI cannot function optimally with fragmented, outdated, or siloed data. 
  • AI-driven automation depends on interoperable, structured information. 
  • Many data centres still operate with disconnected legacy systems, limiting AI’s effectiveness. 

Industry reports highlight these challenges: 

  • McKinsey & Company (2024) highlights that demand for AI-ready data centre capacity is projected to grow 33% per year through 2030, yet most facilities lack structured data strategies to scale AI effectively. 
  • Deloitte reports that data integration, governance, and quality issues are among the most significant obstacles to AI-driven optimisation. Without a Golden Thread, AI remains disconnected from reliable decision-making. 
  • The Uptime Institute warns that many data centres still rely on outdated infrastructure, making AI integration slow, complex, and unreliable. 
  • Flexential identifies that integrating AI with existing data centre systems is hindered by legacy information structures, preventing AI from making timely, data-driven decisions. 
  • AvePoint found that poor data quality is the single biggest obstacle to AI adoption—without structured data, AI-generated insights become inconsistent and difficult to validate. 

The key takeaway? AI can only be as effective as the quality and structure of the data it relies on. 

The Golden Thread: A blueprint for AI-optimised data centres 

The Golden Thread is often framed as a compliance requirement, but it is far more than that—it is a data governance model that AI depends on. 

The term was introduced following the Grenfell Tower tragedy, when Dame Judith Hackitt’s 2018 review exposed how poor information management led to serious risks in the built environment. The UK Building Safety Act 2022 enshrined the Golden Thread as a legal requirement for accurate, structured, and accessible data across a built asset’s lifecycle. 

While much of the focus has been on high-risk residential buildings, the same principles are essential for data centres and other mission-critical infrastructure. 

Why the Golden Thread matters for AI in data centres

  • AI models require structured, traceable data to learn, predict, and optimise effectively. 
  • Digital twins must go beyond static models—they need continuously updated, structured data. 
  • Compliance and risk management are shifting toward automation—but AI can only enforce regulations if it can access and process well-structured information. 

Without a Golden Thread approach, AI risks becoming a disconnected tool, unable to reach its full potential in data centre management. 

BIM, digital twins & structured data: The AI enablers 

BIM and digital twins are not just design tools—they bridge the gap between AI and structured data. 

Currently, many data centres treat BIM as a project phase rather than an ongoing data management system. If we want AI to work effectively, we need to transition BIM into a real-time, structured data ecosystem rather than just a documentation process. 

  • BIM & AI Integration – AI can enhance design, efficiency, and cost prediction, but only if BIM data is structured, accurate, and machine-readable. 
  • Digital Twins & AI-Driven Insights – A digital twin is not just a 3D model—it must be continuously updated with structured data to provide meaningful operational insights. 
  • Automated Compliance & AI Monitoring – AI cannot detect compliance risks if the data it reads is incomplete, inconsistent, or siloed. 

Without structured data frameworks like ISO 19650 and the UK BIM Framework, AI in data centres will continue to face limitations. 

Women in digital construction: Leading the change 

AI, digital twins, and structured data are reshaping leadership opportunities in digital construction. 

For decades, technical and leadership roles in construction and data centres lacked diversity. But as AI, information management, and automation become central to digital infrastructure, the demand for expertise is shifting—creating new opportunities for leadership. 

This is not about replacing one group with another. 

It is about ensuring that those with the right expertise are leading digital transformation. 

Women in BIM (WIB) plays a crucial role—not by focusing on quotas, but by ensuring that professionals with expertise in BIM, AI, and digital workflows have visibility and leadership opportunities. WIB supports: 

  • Career transitions into digital roles: Highlights female role models and maintains support mechanisms to inspire more women to pursue careers in BIM and digital construction. 
  • Development of future leaders: Celebrating women in Senior BIM roles and provides opportunity and knowledge to help advance further. 
  • A professional network where expertise, not gender, defines success: A space to connect, share knowledge and support each-others growth.  

The future of AI-driven construction is not just about technology—it is about ensuring capable professionals are at the forefront of this transformation. 

Final thoughts: AI needs the Golden Thread (and the right leadership) 

AI alone will not revolutionise infrastructure. 

It requires structured data, governance, and leadership. 

So instead of asking “Will AI replace us?” the real question is: 

  • “Are we structuring our data in a way that AI can actually use?” 

The future of AI in data centres will not be shaped by algorithms alone—it will be led by those who understand structured data, AI-driven decision-making, and the Golden Thread. 

Are we ready to lead this transformation? 

Citations & Further Reading 

About the Author 

Willow is a BIM Manager at Colt Data Centre Services with over a decade of experience in information management and digital transformation. Her focus is on embedding the Golden Thread, ensuring structured data flows seamlessly from design to facility management to drive efficiency and long-term value. 

As an executive leader at Women in BIM, she drives industry conversations through speaking, mentorship, and leadership initiatives, supporting professionals in advancing their careers. 

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