AI promises faster insights and smarter operations, yet many industrial projects still fail to deliver because the data behind them isn’t reliable. In this commentary, ITCAN Solutions shares its perspective on why that happens and how to overcome it.

AI is only as good as the foundation it’s built on. Without clean, validated, and intelligently structured data, even the most advanced technologies fall short, offering illusions of insight instead of reliable intelligence.

As industries including Oil & Gas, Petrochemicals, Power, and Food & Beverage accelerate digital transformation, Artificial Intelligence (AI) has emerged as a central component of strategy. The promise is clear: predictive insights, faster decision-making, and improved efficiency. Yet, despite high expectations, real-world outcomes often fall short.

So, what’s going wrong?

Amid the rush to adopt AI, a critical truth is becoming clear: success doesn’t depend on how early AI is adopted but on how strong and structured the data foundation is. As we explored in Why Your AI Needs a Trusted Digital Twin to Deliver Real Value, the presence of a reliable, unified source of information is fundamental to any trustworthy AI initiative.

Digital Twin technology is a cornerstone of industrial intelligence, especially in brownfield environments. It’s the Digital System Integrator (DSI) that determines whether that digital twin is truly reliable. Outdated documentation, legacy systems, and fragmented data are common challenges. But with the right partner and tools, even decades-old facilities can be digitally transformed to support intelligent, AI-ready operations.

To build a trustworthy digital twin, you need more than technology—you need a DSI that ensures every element is complete, correct, and consistent.

A DSI plays a pivotal role in bridging the gap between physical assets, engineering documentation, and operational systems. It ensures that this complex ecosystem is not only digitally connected but also verified, intelligised, and contextualised, creating the foundation AI needs to generate meaningful and reliable outcomes.

Why AI Fails Without Structured Data

In high-asset industries, every physical asset is tied to a large volume of data. Take a single valve, for example, it has a datasheet, P&IDs, isometric drawings, manuals, General Arrangement drawings, 3D models, and more. This data is often scattered across different systems, saved in inconsistent formats, and contains discrepancies across versions.

Now scale that to an entire facility. The result? A flood of conflicting information that overwhelms teams and breaks AI logic.

What might seem like a small inconsistency in one asset becomes a major issue at scale. If the valve is tagged one way in the datasheet, another in the P&ID, and differently again in the 3D model, an AI solution will interpret them as three separate components—leading to fragmented insights, broken data links, and ultimately, unreliable recommendations.

This is not a hypothetical scenario. According to a 2023 McKinsey study, nearly 70% of industrial AI initiatives fail to scale, not because of flawed algorithms, but due to inconsistent, incomplete, and unstructured data.

And that’s where the Digital System Integrator (DSI) becomes essential.

What Makes a DSI Critical?

Partnering with a Digital System Integrator doesn’t just solve technical gaps, it establishes the digital foundation needed for transformation to succeed at scale. By addressing the core challenges that hold industrial facilities back, a DSI unlocks reliable intelligence across the asset lifecycle.

This includes redrawing outdated P&IDs, intelligizing legacy documents, conducting laser scans to capture the true as-built state of facilities, and creating or enhancing 3D models where each asset is correctly tagged. DSIs also standardise all engineering and operational documentation, bringing clarity, consistency, and centralised data ownership. The result is not just visual consistency, but data that is structured, traceable, and aligned across disciplines.

Once this groundwork is established, the DSI implements a unified, tag-centric data structure. This enables teams to access a single source of truth—consolidating 1D, 2D, and 3D data into a searchable, navigable system where datasheets, drawings, and models are interconnected, offering a complete view of each asset.

But above all, reliable DSIs give AI value. By ensuring that each asset is uniquely identified, verified, and contextually intelligized, AI solutions can operate with clarity and precision.

This means the insights generated aren’t just smar,t they’re actionable and trusted.

What makes a DSI critical is not just their ability to integrate systems, but their ability to connect people, processes, and data. They bring a rare combination of technical expertise, domain knowledge, and strategic vision, working closely to uncover root challenges, design tailored approaches and solutions, and guide transformation from planning to execution and beyond.

Founded in 2016, ITCAN Solutions has become a transformative leader in digital transformation, particularly in data-intensive and high-stakes industries such as Energy, Power, Mining, Marine, and Food & Beverage. As a Digital System Integrator, ITCAN employs expert teams with the know-how to implement complex solutions effectively, with the mission to help organisations “Achieve Further” through AI-driven insights based on trusted data.

ITCAN aims to democratise complex and extensive datasets. This approach enhances productivity, safety, planning, and operational reliability. Serving over 30 prominent industry players, ITCAN has redefined how AI functions in settings where accuracy, reliability, and seamless data integration are critical.

One such example is a major brownfield transformation for a petrochemical company in Qatar. ITCAN Solutions was engaged to resolve the challenge of managing fragmented engineering data across five ageing plants.

By streamlining over 900 engineering datasheets down to 80 and reducing the number of attributes from 50,000 to 17,000, the project delivers a significant leap in operational efficiency and data quality for the plant. Operations and engineering teams now have faster access to accurate, trusted information — enabling quicker decision-making, more effective troubleshooting, and enhanced maintenance planning. This simplified, high-quality data foundation also accelerates the adoption of advanced digital tools and AI-driven solutions across the plant, ultimately improving reliability and driving down operational costs.

So what happens once the digital twin is implemented?

Once the digital twin is enriched and validated, it transforms from a visual model into a living, data-rich ecosystem.

Engineers can perform virtual walkthroughs of the site, plan modifications digitally, retrieve data instantly, review shutdown procedures, and analyse historical trends, all from a single, unified interface. They can also access technical documents, inspect equipment relationships, and collaborate across teams with ease.

AI solutions can simulate operational scenarios, detect anomalies, generate reports and flag deviations because every component is intelligently structured, contextually verified, and machine-readable.

When DSIs take the lead in integration:
• Engineers trust what they see
• AI operates on validated thresholds, not assumptions
• Teams collaborate via a central, structured data hub
• Operations become safer, scalable, and insight-driven

Once data is consolidated and contextualised, AI shifts from reactive to proactive. Whether it’s a voice-guided assistant or a dashboard, intelligent tools function better when fed structured data.

Final Word: Don’t Let Bad Data Derail Great Technology

AI and Digital Twins can unlock unprecedented industrial performance, but only when built on a trusted foundation. A Digital System Integrator ensures that what you see is real, what AI analyses is reliable, and what your teams act on is safe.

For industries navigating critical operations, the DSI is the core enabler of intelligent, confident transformation.