- Generative AI is unlike any technology that has come before. It’s swiftly disrupting business and society, forcing leaders to rethink their assumptions, plans, and strategies in real time.
- To help CEOs stay on top of the fast-shifting changes, the IBM Institute for Business Value (IBM IBV) is releasing a series of targeted, research-backed guides to generative AI on topics from data security to tech investment strategy to customer experience.
- This is part 20: Physical asset management.
Generative AI is unlike any technology that has come before. It’s swiftly disrupting business and society, forcing leaders to rethink their assumptions, plans, and strategies in real time.
To help CEOs stay on top of the fast-shifting changes, the IBM Institute for Business Value (IBM IBV) is releasing a series of targeted, research-backed guides to generative AI on topics from data security to tech investment strategy to customer experience.
This is part 20: Physical asset management.
Generative AI is unlike any technology that has come before. It’s swiftly disrupting business and society, forcing leaders to rethink their assumptions, plans, and strategies in real time.
To help CEOs stay on top of the fast-shifting changes, the IBM Institute for Business Value (IBM IBV) is releasing a series of targeted, research-backed guides to generative AI on topics from data security to tech investment strategy to customer experience.
This is part 20: Physical asset management.
Say goodbye to downtime
Production lines. Power lines. Pipelines.
With generative AI, CEOs have the chance to put equipment failures and unplanned outages in the past. Its self-learning, self-monitoring, and self-maintaining capabilities are transforming physical asset management. For CEOs, that’s changing the business equation, as downtime that undermines productivity, revenue growth, and brand reputation dissolves.
By analyzing vast amounts of sensor data, maintenance records, and environmental metrics, gen AI can improve asset performance better than any human possibly could. And it’s better than old-style analytics. Its predictive prowess helps teams avoid costly surprises that cripple operations.
Not only can gen AI be good for an organization’s bottom line, it can also be good for the planet. Gen AI-powered assets can autonomously adjust operating parameters and plan work in ways that reduce energy consumption, shrinking an organization’s environmental footprint and limiting equipment wear-and-tear. This helps CEOs unlock new levels of efficiency, reliability, and environmental responsibility—and positions them for sustained success in increasingly contested markets.
IBM Institute for Business Value research has identified three things every leader needs to know:
1. Generative AI makes assets more valuable.
2. Connected assets take care of themselves.
3. Gen AI makes sustainability sustainable.
And three things every leader needs to do right now:
1. Lengthen the lifespan of your physical assets.
2. Make your machines self-aware.
3. Major on eco-friendly innovation in asset design.
Additional content
Meet the authors
Anthony Marshall, Senior Research Director, Thought Leadership, IBM Institute for Business ValueCindy Anderson, Global Executive for Engagement and Eminence, IBM Institute for Business Value
Christian Bieck, Europe Leader & Global Research Leader, Insurance, IBM Institute for Business Value
Karen Butner, Global Research Leader, AI and Automation and Supply Chain Operations, IBM Institute for Business Value
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Originally published 26 August 2024
This chapter is available in the latest edition of the IBM Institute for Business Value's book, The CEO's Guide to Generative AI.
1. Visibility
+ Generative AI
What you need to know
Generative AI makes assets more valuable
You can’t expect your business to run smoothly every day. Or can you? By harnessing the power of gen AI, CEOs gain unparalleled visibility into physical asset performance—giving them the power to predict potential failures before they disrupt operations.
The impact will be nothing short of transformative. 71% of executives say gen AI fundamentally changes how they will manage assets—and 72% say it increases the strategic value of physical asset management to their enterprise.
A chunk of that value will come from unlocking new levels of efficiency, productivity, and profitability through proactive maintenance, because the more reliably your equipment operates, the more value it can create for your business. And understanding the true value of physical assets can lead to more profitable business strategies. Most executives see gen AI playing a larger role in this type of decision-making, with 72% of executives saying gen AI will have a major impact on their asset investment strategy.
For example, gen AI can help leaders determine when it makes sense to invest in repairing equipment they already have—or if it’s time to buy something new. In the next two years, 68% of executives plan to use gen AI to assess the depreciation of individual assets and 77% expect to use it to assess entire asset classes. This level of granularity will give leaders the data they need to make more informed business decisions and derive more value from their physical assets over time.
What you need to do
Lengthen the lifespan of your physical assets
Get ahead of routine maintenance, fine-tune processes, and drive unprecedented reliability and profitability by embedding gen AI into physical assets. Insert AI assistants directly into sensors, robotics, and machines to find efficiencies and increase the longevity of your asset investments.
- Train gen AI assistants to be the organization’s antennae. Create gen AI-powered self-service assistants that can interact with assets, sensors, and devices to respond to vibrations before they lead to disruption.
- Increase predictive precision. Use gen AI to analyze historical data and find the root cause of past failures. Then ask it to assess current assets and schedule preventative care based on current condition rather than arbitrary milestones.
- Discover hidden treasure. Generate synthetic data where needed to better train gen AI models to spot opportunities to improve asset performance, increase asset availability, and decrease wear-and-tear.
2. Automation
+ Generative AI
What you need to know
Connected assets take care of themselves
Machines depend on people for many things—but managing the minutiae of maintenance is no longer one of them. Gen AI empowers connected assets to handle scheduled maintenance and spot potential issues all on their own, unlocking the latent potential of connectivity across the enterprise and ecosystem.
When complex asset ecosystems work in harmony, they can help businesses achieve results that weren’t previously possible. And by 2026, 76% of executives expect to use gen AI to derive differentiated outcomes from connected assets.
In a specific example, 67% of utility companies are aligning their IT/OT enterprise architecture with ecosystem partners for the items each organization designates as critical success factors. Moreover, in the context of physical asset management, 62% of utility companies have implemented proactive communication for notification and response across ecosystem stakeholders for all items each organization identifies as critical process flows.
Potential applications seem almost limitless—and executives expect them to quickly become common-place. By 2026, 77% of executives believe gen AI will enable connected assets to make autonomous decisions. Roughly three in four also expect to use gen AI to detect and diagnose asset anomalies, proactively schedule maintenance, and inspect assets across the portfolio.
But what does this look like for a typical organization? It starts with using gen AI to identify patterns and anomalies in disparate data streams that human analysts might miss, enabling proactive interventions that prevent equipment failures. By reviewing historical data, gen AI can analyze past failures and their effects, providing a treasure trove of insights to inform asset management decisions—and 71% of executives plan to use gen AI for this purpose in the next two years.
These capabilities go hand-in-hand with gen AI’s ability to streamline the maintenance tasks that need to be handled by humans. In the next two years, 69% of executives say gen AI will generate work instructions for field services technicians, streamlining maintenance processes and improving efficiency, while 74% say it will proactively schedule preventive maintenance. In the same timeframe, gen AI will also play a critical role in making maintenance recommendations, planning work orders, and authorizing service requests, with 76% of executives expecting to use it for this purpose.
What you need to do
Make your machines self-aware
Overcome predictive maintenance barriers by giving your assets the power to self-monitor, self-maintain, and communicate their status across the network and partner ecosystem. Connect robotics, sensors, drones, and IoT devices to self-service assistants so they can collaborate with one another to optimize their performance. Enable ecosystem visibility by connecting AI assistants across the supply chain.
- Solve problems before they appear. Empower machines to communicate when trouble is brewing. Free service personnel from one-off service calls by using gen AI to troubleshoot and address basic problems.
- Tap into the hive mindset. Design gen AI systems that enable collaboration among connected assets. Use edge computing to gather real-time monitoring data sent to hybrid cloud platforms to enable interconnected intelligence and modernize predictive maintenance programs ecosystem wide.
- Merge human experience and computational power. Streamline your employees’ to-do lists by using gen AI to prioritize and schedule maintenance tasks. Ask gen AI assistants to provide all the information technicians need to fix problems quickly—without the frustration of random troubleshooting.
3. Sustainability
+ Generative AI
What you need to know
Gen AI makes sustainability sustainable
As the world grapples with the challenges of climate change, CEOs are under pressure to reduce their environmental footprint, optimize resource usage, and promote sustainable practices throughout their operations. Generative AI is emerging as a powerful tool to help achieve these goals, powering a virtuous asset lifecycle.
And that process starts with ideation, with 76% of executives expecting to use gen AI to design more sustainable assets by 2026. Roughly four in five plan to tap it to monitor (79%) and optimize (78%) asset sustainability performance. For example, they expect gen AI to suggest ways to reduce CO2 emissions, water and energy consumption, and waste. It can also make it easier for employees to look for opportunities for improvement, with 74% of execs saying gen AI will enable self-service sustainability reporting for employees in the same timeframe.
As CEOs set ambitious, yet attainable sustainability goals for the future, gen AI can be an invaluable tool. 72% of executives say they will use gen AI to set sustainability targets based on real-world data in the next two years. By simulating complex systems, predicting potential environmental impacts, and spotting opportunities to optimize resource usage in real-time, gen AI-fueled digital twins can help companies make clear and consistent progress—and bring true sustainability within striking distance.
What you need to do
Major on eco-friendly innovation in asset design
Merge disparate data streams to uncover actionable insights that drive asset performance optimization and sustainability outcomes. Visualize the intricate web of asset relationships and simulate scenarios to future-proof sustainability strategies and reduce environmental impact.
- Revolutionize sustainable design. Weave environmental responsibility into the very fabric of asset design to forge new paths to achieve sustainability targets. Use data to simulate and predict the environmental performance of different design options and discover new, more sustainable materials with the right properties. Recognize and reward the designers and engineers who make the biggest difference.
- Divine truth from chaos. Use gen AI to analyze data from various sources, including sensors, drones, and IoT devices, to gain insights and optimize asset performance, including energy and water consumption, waste, and carbon emission reduction.
- Set the form for a sustainable future. Create a continuous feedback loop, delivering data from assets directly to the people responsible for meeting sustainability goals. Empower these teams with gen AI assistants that can help them identify adjustments that will keep the organization on the right trajectory.
The statistics informing the insights in this report are sourced from two proprietary surveys conducted by the IBM Institute for Business Value in collaboration with Oxford Economics and APQC. The first survey was fielded from July to August 2024 and asked 100 US-based executives about their perspectives regarding generative AI and physical asset management. The second survey asked 105 global electric power utilities executives regarding their organization’s maturity with respect to clean electrification in 2023.
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Additional content
Meet the authors
Anthony Marshall, Senior Research Director, Thought Leadership, IBM Institute for Business ValueCindy Anderson, Global Executive for Engagement and Eminence, IBM Institute for Business Value
Christian Bieck, Europe Leader & Global Research Leader, Insurance, IBM Institute for Business Value
Karen Butner, Global Research Leader, AI and Automation and Supply Chain Operations, IBM Institute for Business Value
Download report translations
Originally published 26 August 2024
This chapter is available in the latest edition of the IBM Institute for Business Value's book, The CEO's Guide to Generative AI.
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