Asset Integrity - Why AI Hasn't Moved the Needle

In today’s infrastructure world, “AI” is the buzzword that gets you in the door. Once inside, reality sets in, predictive promises don’t automatically translate into measurable operational outcomes.   

Here’s the issue.

Many AI providers offer platforms costing tens of millions of dollars per year, and some with valuations so inflated that respected publications like The Economist call them out as being “possibly the most overpriced stock in history.” 

It is also reported that a well-known energy major signed a 10-year deal with an organisation offering AI  at $1.2 billion. A staggering commitment, and the uncomfortable truth.  

No matter how sophisticated the AI, one size does not fit all.   

The reason asset integrity and maintenance strategies live in the messy real world is simple. They differ in age, location, environmental exposure, and where regulations shift from state to state. Even within a single company, different divisions often operate under completely different workflows. 

The idea of “lift-and-shift” deployment is a nice dream and yet not a reality.  

It’s like assuming a payroll system built for one region will seamlessly work across multiple countries and jurisdictions without adaptation. Regulations, working practices, and supply chains introduce complexity that even the largest  AI platform simply isn’t built to handle. This is why global ERP systems like SAP often rely on niche, specialised solutions to handle critical but nuanced workflows.  

The Difference That Matters  

Where others sell broad promises, KartaSoft delivers measurable, operationally relevant insights. 

Our platform links prescriptive maintenance directly to asset integrity budgets, with tangible proof points, including:  

• Fewer failures -  targeting the highest-risk “islands” in the network.  

• Optimized spending - reallocating budgets based on real-world degradation risk. 

• Decarbonization impact - for example, in reducing methane emissions and other environmental harm as a direct outcome of better maintenance planning.  

This isn’t AI for AI’s sake. 

It is targeted risk intelligence, tied to metrics that infrastructure operators already live by; namely, performance, cost, compliance, and environmental responsibility.   

The new norm in asset management isn’t abstract AI hype. It’s measured outcomes that align with business priorities and regulatory obligations.   

The companies that embrace this shift will not only outpace their peers but will also have the evidence to prove it.