Artificial Intelligence in Asset Integrity Management
Turning Decades Of Integrity Data Into Actionable Intelligence
Over more than 45 years, we have built one of the industry’s largest collections of pipeline integrity data. This gives us a distinctive foundation for advancing AI-augmented integrity management. Combined with our engineering expertise, this data helps turn complex integrity information into reliable insights for better-informed decisions.
Engineered for trust
Trust in Artificial Intelligence requires evidence that a model performs reliably in its intended application. We validate AI methods against defined requirements before they become part of an operational assessment process.
The same engineering rigor continues after deployment. Our experts monitor model performance as new data becomes available. This lifecycle approach holds AI to the standards expected in integrity engineering.
AI augments the analysis of integrated data by recognizing patterns across large datasets. This allows our experts to concentrate on findings that require closer investigation and engineering interpretation.
Every integrity process begins with a decision that needs to be made. The condition and operating history of the asset determine what information is required and which inspection and assessment approach is appropriate.
The inspection captures the data needed to evaluate the asset. The technology is selected according to the integrity challenge and the information required. The quality of this data is fundamental to the subsequent analysis.
Inspection results become more meaningful when they are connected with other available information. ROSEN brings together data from different technologies, previous inspections and relevant asset records to create a more complete view of the asset.
Validated information can indicate how asset condition may develop over time. Our experts interpret these insights, while the operator decides how they should inform integrity planning and action.
ROSEN’s experts compare the analytical results with the available data. The performance of the artificial intelligence methods is monitored to confirm that they continue to function as intended.
Our goal is to validate AI according to the same rigorous engineering principles we apply to our established technologies. This prepares us for future regulatory expectations and strengthens confidence in how AI is applied.
The Real Value of AI Human Collaboration in ILI Data Analysis
Navigating growing complexity
Turning more data into clearer integrity insights
As integrity datasets grow in scale and complexity, operators need reliable ways to connect information and translate it into decisions. Combining data from different inspection technologies and inspection runs can deepen the understanding of an asset. Realizing its full value, however, requires the information to be connected and interpreted in context.
AI-augmented analysis helps experts examine these relationships across large datasets. This gives operators a clearer view of asset condition and a sound basis for integrity decisions.
Our foundation
An integrity data advantage built over decades
Reliable AI depends on the quality and relevance of the data behind it. ROSEN’s Integrity Data Warehouse reflects decades of pipeline inspections across different technologies and operating conditions. Verified findings from real assets add the evidence needed to develop and validate AI models for integrity applications.
This foundation allows our models to learn from a broad range of integrity scenarios and recognize patterns across datasets that would be difficult to identify manually.
We combine this data with a deep understanding of inspection technology and asset behavior. This knowledge shapes the models we develop and guides how their results are interpreted.
Applying AI where it creates tangible value
The value of Artificial Intelligence does not come from a single application. It comes from applying AI to the right task. ROSEN uses it at different stages of the integrity assessment process to address specific analytical challenges.
Accelerate evaluation cycles
Understand defects in greater detail
Predict future conditions
How AI Strenghtens Crack Inspection
Visit us at IPCE 2026
Meet us at Booth #512 and discover how AI is helping advance pipeline integrity. Don't miss Stephan Eule's (Senior AI Specialist at ROSEN) presentation, "Improving Identification and Sizing of Stress Corrosion Cracking in Gas Pipelines by Complementing EMAT Signal Data With AI-Generated Metal Loss Profiles Derived From MFL Data," on Friday, September 25, 2026, from 9:30 - 10:00 AM.
Visit our booth to connect with our experts and learn more about ROSEN's latest inspection and integrity solutions.
Learn more about ROSEN at IPCE 2026 here.
Talk to a ROSEN Expert
Every asset presents its own integrity challenges. Our experts can help you explore where AI-augmented analysis can add value to your integrity program.
Let us discuss how AI-augmented analysis could support your integrity objectives.
Latest Insights
Explore our latest publications on the use of Artificial Intelligence in asset integrity management. Discover how ROSEN applies AI to real integrity challenges and continues to advance its capabilities.