Navigating megatrends: where AI will have the most impact in asset management
Megatrends are like weather systems. They are dynamic and ever-present. Sometimes they are extreme and devastating and at other times, gentle. Organizations contend with megatrends on a regular basis. Climate change, inflation, aging assets, regulatory change and an aging workforce are examples of current megatrends that all impact an organization's asset management system. The next few paragraphs will explore how asset management collides with these megatrends and how AI has emerged to help individuals and industries adapt to the change that they bring.
Artificial intelligence's timely arrival
The current state of artificial intelligence (AI), and the ways it can be applied, couldn't have arrived at a better time as these megatrends collide. Industries everywhere are dealing with aging assets, whose true condition is anyone's guess, pushing regulators to issue new standards for addressing asset age-related risk. Meanwhile, we're racing to document and maintain the legacy knowledge of senior workers before they head for retirement. Organizations need to capture their expertise and integrate their knowledge into current systems. Add climate change forcing everyone to juggle asset risks against their budgeted environmental footprint, and inflation making everything painfully expensive – limiting investments to just the bare necessities for compliance and safety, which puts a real damper on growth and fresh ideas.
My intent here is to show how we can understand the potential of AI and its applicability amidst the influence of these megatrends. There is a saying widely attributed to former Prime Minister of the United Kingdom, Winston Churchill, "Never let a good crisis go to waste." While I don't suggest we're in a crisis, the challenges that asset managers face are numerous and complex. We can use this moment to dig in and take advantage of this opportunity and use AI to reach asset management system performance beyond previous levels.
Aging assets
If your confidence in the completeness or quality of asset data is low, you're in luck. AI can identify patterns in asset performance data even with incomplete records. Pair this capability with established capabilities such as Monte Carlo Simulation and a "best guess" can reach a higher level of certainty than you would have otherwise. More complex methods like decay modeling can represent mathematically how assets deteriorate over time.
Aging workforce
The challenge of the aging workforce is one of the more important applications of AI because the reality of achieving a more optimal division of labor between human intelligence and computers is within reach. For years there has been a struggle of administrative burden. We want skilled operators and technicians to make use of enterprise technology. However, an unintended outcome emerged: skilled craftsmen and operators spent their time on administrative tasks rather than focusing on the work where they are most effective. This megatrend forces organizations to act with greater urgency to implement work process automation and embed organizational experts' knowledge into these processes before their skills and experience exit the workforce completely.
Climate change
Companies have begun to incorporate climate risk assessments into their asset management strategies. Climate risk is as much a consideration as the risk of failure modes. The consequences of asset failure extend beyond human health and safety or revenue loss; they also include the risk of surpassing the budgeted environmental impact.
Here, AI can help develop and operationalize strategies that link lifecycle activities and monitoring to Environmental, Social and Governance (ESG) goals.
The approach for impactful AI in asset management
Before an organization goes on a shopping spree for artificial intelligence, it's important to put some effort into learning the ISO 55000 overview of asset management principles. Read more in part 3 of this blog series.
An asset management policy will help to gain commitments from top management, alongside their support and authority. A strategic asset management plan will connect asset management to the organization's objectives and establish the measures and outcomes needed to do so successfully. These standards contain guidance on leadership, planning, support, operation, performance evaluation and improvement. Understanding these important fundamentals will help tremendously when it comes to selecting technology as they establish processes that technology enables.
Elevating asset management system performance through strategic AI integration
AI represents a significant opportunity for asset management professionals navigating today's complex landscape of challenges. Strategically implemented AI solutions that address aging assets, workforce transitions and climate imperatives allow organizations to not only mitigate risks but also discover new efficiencies and insights that were previously out of reach. The most successful implementations will align AI capabilities with established asset management frameworks like ISO 55000, ensuring technology serves organizational objectives rather than becoming an end in itself. As these megatrends continue to evolve, organizations that thoughtfully integrate AI into their asset management systems will be best positioned to turn challenges into competitive advantages, creating sustainable value for stakeholders while maintaining resilience in an increasingly unpredictable world.
Learn more in the series:
The role of AI in asset performance management
The role of AI in asset performance management – start with the data you have
Embracing the future: how three AI solutions are shaping the workforce and asset management