How AI-driven asset management is channeling the sea of data into actionable insights for companies

KEVIN PRICE, IFS, AB 

The EU&R industry is collecting data, but a lack of correct or understandable data means that big decisions on oil and gas fields, energy pipelines, and wide-scale assets are just not informed enough. Operational success, profitability, and customer satisfaction for EU&R companies needs an approach to data collection and analysis that ensures investment decisions are sound and that proposed projects are worthwhile.  

Fig. 1. In In oil and gas fields, both onshore and offshore, data are provided by a wide variety of sources.

Technology paves the way for data-driven decision-making. Enter a more composable enterprise approach to delivering the essential data for optimized end-to-end asset lifecycle management for companies. Advanced technologies, such as Industrial AI, asset investment planning, and predictive maintenance, are all crucial to EU&R companies looking to collect and analyze essential data to better inform business decisions and asset investments, fast-track sustainability goals, and improve the overall health of critical infrastructure.  

Understanding the data deluge. Collecting energy data is no mean feat! The data are both diverse and diffuse. In oil and gas fields, data are provided by various sources, including smart meters, sensors, offshore platforms, and weather stations, Fig. 1. Additional sources include data from power plants, distribution network operators, and even individual consumers through smart home systems.  

The result is a data deluge, leaving many EU&R companies unable to make sense of contextual imprints but still, to this day, collecting more and more data. Yet, for the large part, these companies are unsure of how to use these data effectively, or at all.  

Some are just inundated with so much data to the point that it is now not feasible to sift through it all, while others do not have the expertise to action the issue, even with the correct data in place. 

As a result, critical asset data are either unrecognized or going unused, leaving businesses unable to monitor the full condition of assets, and unable to ensure full asset health and optimization.  

Fig. 2. While data are collected from the many assets across the upstream, this distribution of assets is vast, and many are aging, meaning constant maintenance is required.

Enter condition-based monitoring. To combat the issue, many companies have turned to condition-based monitoring solutions, that help organizations to understand the condition, performance, and expected availability of one’s assets. 

It works by leveraging insights to reduce unplanned asset downtime, drive predictive maintenance, optimize energy and resources, and enhance asset planning strategies at every level to meet short-, medium-, and long-term objectives. 

Why data are the key to surviving infrastructure strain and climate shocks. Global oil and gas assets will continue to be more distributed than ever—which only complicates data management. Data are collected from the many assets across the upstream, but this distribution of assets is vast, and many are aging, meaning constant maintenance is required, Fig. 2.  

Yet, innovating and rebuilding the asset base is no simple or quick fix. It involves significant investment in new infrastructure while maintaining existing operations, where finding replacement parts for outdated infrastructure is difficult, and insufficient funding has led to degraded assets and increased risk.  

Climate change and extreme weather events only exacerbate asset failures, both onshore and offshore. Globally, the issue carries on, as seen in the 2024 Balkan heatwave and North American weather events of 2024, such as Hurricane Helene, Hurricane Milton, Hurricane Beryl, and more. In the UK, recent storms such as Storm Darragh and Storm Eowyn, have left thousands of UK homes without power or train services, as 90mph+ winds brought down electricity lines.  

Here comes AI. To fully optimize E&P operations, companies need a full understanding of asset health, where it’s performing well and where it is underperforming—only then can companies determine whether an asset needs to be retired, maintained, or fixed. These conditions will determine capital funding, and where investments are important. 

Fig. 3. The unique capabilities of Risk-Based Inspections (RBIs) allow companies to more intuitively facilitate the detection of facilities that are weak, prone to failure, and where will be the biggest impact before major events like floods and hurricanes.

AI-influenced Risk-Based Inspections (RBI) are now in high-demand within the market. The unique capabilities of RBIs allow companies to more intuitively facilitate the detection of facilities that are weak, prone to failure, and where will be the biggest impact before major environmental events, i.e. floods, hurricanes, occur, Fig. 3. It’s all in the preparation, to ensure assets are strong and good enough to survive the impact. EU&R companies can then prepare for major events in multiple ways and with confidence.  

And AI-driven data decision-making goes beyond just physical assets. Companies can use data-based insights, real-time decision-making models, and AI to help prioritize critical infrastructure investments and monitor the health and performance of assets to extend lifecycles.  

Beyond this, companies can make sure that workers are available and ready to help pre- and post-event, all while assessing the sustainable impacts of these events.  

It’s clear that AI-driven asset management technologies have the potential to help entire companies, regions, and industries—but companies must work together, sharing goals and constraints to establish new benchmarks. 

Maintaining assets the composable way. In all asset-intensive industries, businesses expect to purchase an asset and see it perform to its best ability. Often, these are deployed in risk-critical operational roles. Naturally, if it isn’t performing well, then businesses want to know why before there are huge impacts on the business, operations, and the environment, Fig. 4.  

Fig. 4. Businesses expect to purchase an asset and see it perform to its best ability, particularly in risk-critical operational roles. If it isn’t performing well, then management wants to know why before there are huge impacts on operations and/or the environment. AI-embedded Enterprise Asset Management (EAM) software can help with such situations.

Here, AI-embedded Enterprise Asset Management (EAM) software improves visibility, reliability, and real-world efficiencies. But to succeed in knowing where an asset is failing and why, it’s not always necessary to buy an entire solution. It’s where a composable framework comes in. Designed to be flexible, composable EAM solutions can help companies install only the applications that they will benefit from, allowing then to hone in and map specific problem areas.  

IFS Customers report a 20% increase in uptime, 16% less unplanned downtime, and 14% lower maintenance costs with cloud asset management solutions from IFS. 

Full lifecycle management, with sustainability payoffs! An effective asset lifecycle management solution involves data that support operational, tactical, and strategic decisions. With advanced Enterprise Asset Management (EAM) software with embedded industrial AI, EU&R companies can be sure the full asset lifecycle is monitored—maximizing uptime, reducing costs, and supporting sustainable operations. 

Industrial AI, paired with strategic asset tools, such as IFS Copperleaf’s Asset Investment Planning (AIP) solution, offers advanced tools for strategic planning, resource optimization, and scenario analysis, enabling data-driven decision-making and efficient capital allocation. 

And it impacts sustainability too! Anglian Water, the largest water recycling company in England and Wales by geographic area, uses IFS Copperleaf Decision Analytics Solution to holistically evaluate investment projects and demonstrate progress against strategic objectives and ESG goals. It enables Anglian Water to model the impact of different asset investment plans and account for private and societal costs associated with flooding in decision making. 

The IFS Copperleaf case in point. To support its ambitious carbon reduction targets, Anglian Water uses IFS Copperleaf Cost Estimation to model capital carbon and capture operational carbon associated with an asset’s full lifecycle. The solution provides visibility of capital baselines in their proposed investments, from which performance against targets are measured. This capability allows engineers and designers to challenge the supply chain in the early design stages to consider lower carbon solutions, such as optimizing the use of existing assets, low-carbon construction techniques and/or the use of alternative low-carbon materials.  

It makes financial sense, too, and can impact ROI—analysis of their investment planning portfolio shows that a reduction in capital costs and a reduction in capital carbon come hand-in-hand.  

Turning data into decisions: The AI-powered assets powering energy of the future. As the pressure mounts from climate change, aging infrastructure, and evolving energy models, it’s increasingly clear that legacy approaches to managing business-critical assets are no longer fit for purpose. 

With technologies, such as condition-based monitoring and AI-enabled predictive maintenance and risk-based inspections, EU&R companies are beginning to turn the tide. Optimizing asset management is about transforming raw data into strategic, actionable insights that protect asset health, maximize investments, and enhance resilience across sprawling, distributed assets. The shift to composable, AI-powered EAM is more than a technological upgrade—it’s a new operational mindset.  

KEVIN PRICE is Global Head of Enterprise Asset Management at IFS. He has dedicated over 26 years to innovating and advancing data-centric Enterprise Asset Management (EAM). His career has been defined by a commitment to value-driven engagements with asset-centric customers and a forward-thinking vision for the future of asset management. Mr. Price is dedicated to leveraging IFS's status as a leading EAM vendor, as recognized by research/advisory firm Gartner, to realize the long-term goal of leading the asset management domain. He is committed to setting industry benchmarks and ensuring that IFS remains synonymous with excellence in EAM.