10 Maintenance Industry Trends for 2025

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The maintenance industry is undergoing a significant transformation, driven by rapid technological advancements, a growing emphasis on sustainability, and evolving workforce dynamics. This article covers the Top 10 maintenance industry trends for 2025.

These changes are not just about keeping equipment running; they represent a fundamental shift towards strategic asset management and industrial maintenance that optimizes efficiency, reduces costs, and minimizes environmental impact.

As we move into 2025, several key maintenance industry trends are set to redefine the maintenance landscape.

1. Predictive Maintenance and Artificial Intelligence (AI)

In 2025 AI is what every industry is talking about. Large Language Models like ChatGPT are dominating the news cycle. However, these tools are not always valuable for maintenance technicians and managers, but the rise of predictive and preventive maintenance powered by artificial intelligence (AI) is transformative.

What is valuable and one of the most transformative trends is the rise of predictive maintenance and analytics powered by artificial intelligence (AI).

Benefits of AI solutions
Illustration: WorkTrek / Data: Joseph’s sons

The global predictive maintenance market has been experiencing significant growth and is projected to continue expanding in the coming years.

According to a report by IMARC Group, the market size reached USD 12.7 billion in 2024 and is expected to grow to USD 80.6 billion by 2033, exhibiting a compound annual growth rate (CAGR) of 22.8% from 2025 to 2033.

Another analysis by Precedence Research estimates the market size at USD 7.24 billion in 2024, with projections to surpass USD 79.70 billion by 2034, expanding at a CAGR of 27.10% between 2024 and 2034.

So how does it work?

AI-driven systems analyze vast amounts of data to forecast potential equipment failures, enabling maintenance teams to take proactive measures and reduce reactive maintenance.

This is a significant shift from reactive maintenance, where repairs are only initiated after a failure.

  • AI-driven systems can predict equipment failures and adjust dynamically to changing environmental conditions and usage patterns. This can result in lower maintenance costs.
  • Virtual simulations create digital environments that mirror real-world assets, providing insights that allow teams to anticipate performance shifts without physical intervention.
  • Machine learning algorithms improve predictive accuracy by using historical and real-time data to forecast maintenance needs effectively and improve routine maintenance tasks.
  • AI can analyze real-time IoT data streams, transform maintenance systems into autonomous, self-optimizing solutions, and improve equipment performance.
  • AI-enabled maintenance scheduling is one emerging technology that allows facilities to plan activities for the least disruptive times, reducing unexpected downtime.
  • AI-powered predictive maintenance can increase failure prediction accuracy by up to 90% while reducing maintenance costs by up to 12%.

By leveraging AI, maintenance teams can move from reactive to proactive strategies, minimizing downtime, reducing repair costs, and extending the lifespan of critical assets.

2. Sustainability as an Operational Imperative

Sustainability is no longer just a corporate buzzword; it has become a fundamental principle guiding maintenance strategies.

Maintenance equipment manufacturers are increasingly providing eco-friendly solutions that align with sustainability goals. In addition to its environmental impacts, sustainability will reduce costs and increase profits.

Data on carbon footprint
Illustration: WorkTrek / Data: Ecologi

In 2025 and beyond, maintenance operations are expected to align more closely with environmental goals. Integrating advanced technologies and sustainable practices will drive much of this alignment.

Companies must implement eco-friendly protocols that reduce waste and emissions and enhance operational efficiency.

Another trend is incorporating renewable energy sources and energy-efficient equipment.

Furthermore, maintenance teams will leverage data analytics to optimize resource utilization, ensuring that every aspect of maintenance operations contributes to a greener and more sustainable future.

By prioritizing environmental objectives, organizations can achieve cost savings, improve their brand reputation, and meet regulatory requirements, all while contributing to a healthier planet.

  • Circular economy practices are gaining traction, emphasizing repairing and repurposing components to reduce waste.
  • Carbon-neutral operations are becoming a priority, with organizations using low-emission tools and tracking carbon footprints.
  • Smart energy management is being integrated into maintenance practices. This includes smart thermostats, smart meters, IoT-based solutions, and energy analytics software, among many others.
  • Green asset management tools help reduce the environmental impact of assets and operations. Companies see an average of 15% cost savings through energy efficiency improvements.
  • Sustainable maintenance protocols and eco-friendly technologies reduce environmental impact, lower energy consumption, and reduce waste.
Environmental Sustainability Innovations.
Source: WorkTrek

Focusing on sustainability reduces maintenance operations’ environmental impact, achieves cost savings, and enhances their brand reputation as a responsible organization.

3. AI Agents – The Future

Just like Large Language Models (LLMs) like ChapGPT have dominated the past few years, 2025 will be the birth and growth of AI Agents.

Think of an AI agent as a digital assistant that can understand, learn, and take action to help with specific tasks.

Data on AI agents
Illustration: WorkTrek / Data: CSDN

Like a human assistant, an AI agent can observe what’s happening, make decisions based on what it sees, and take helpful actions.

The key difference is that AI agents can process vast amounts of information faster than humans and work 24/7 without getting tired.

Example of AI Agents for Maintenance Tasks

Imagine you’re responsible for maintaining equipment in a manufacturing plant. Here’s how an AI agent could help:

Without an AI agent, you might walk around the factory floor every morning, checking each machine, listening for unusual sounds, and looking at maintenance records to decide what needs attention.

You rely on your experience to catch problems, but you can’t be everywhere simultaneously, and some issues might slip through.

AI Agents Trained Assistant

With an AI agent, it’s like having a highly trained assistant who never sleeps. The agent continuously monitors all your equipment through sensors, collecting data about how each machine is running.

It learns what a “normal” operation looks like and can spot potential problems before they become serious. When it notices something concerning, it can alert you immediately and suggest what might be wrong based on patterns learned from thousands of similar cases.

The real power comes from how AI agents can help in different ways:

  • Understanding Language: They can read maintenance manuals, work orders, and technical documents, then answer questions in plain English. Instead of digging through hundreds of pages of documentation, you can simply ask, “What’s the maintenance procedure for the cooling system?” and get a clear answer.
  • Making Predictions: By analyzing patterns in data, AI agents can tell you things like, “Based on current performance, this bearing will likely need replacement in about three weeks.” This helps you plan maintenance before equipment fails.
  • Learning and Adapting: AI agents improve as they learn from experience. If they make a prediction that turns out to be wrong, they adjust their understanding, just like humans would learn from mistakes.
  • Providing Guidance: When working on equipment, an AI agent can guide technicians through repair procedures, showing each step on a mobile device or tablet, almost like having an experienced mentor look over their shoulder.
AI agent capabilities
Source: WorkTrek

However, it’s important to understand that AI agents aren’t meant to replace human workers. Instead, they’re tools that make human workers more effective by handling routine tasks, providing helpful information, and spotting problems that might be missed.

This lets people focus on more complex tasks that require human judgment and creativity.

Think of AI agents as team members who excel at monitoring, analyzing data, and providing information. They work alongside human employees who bring experience, judgment, and problem-solving skills.

Together, they can achieve better results than they could alone.

4. Unified Digital Ecosystems for Collaboration

You cannot run a maintenance organization without coordination among all stakeholders. Many organizations have started implementing digital tools, like CMMS systems, to improve collaboration and data collection.

In 2025, the adoption of digital tools and digital transformation will continue and accelerate. Organizations must depend on unified digital platforms that consolidate maintenance data, communication, and workflows.

  • Instant data sharing grants teams immediate access to real-time performance metrics and task progress.
  • Integrated compliance management automates systems to ensure regulations are met effortlessly.
  • Collaborative dashboards facilitate streamlined decision-making for quick issue resolution.
  • CMMS (Computerized Maintenance Management Systems), like WorkTrek and EAM (Enterprise Asset Management), are central to this trend. They help organize maintenance and track all activity in one system.
WorkTrek web app dashboard
Source: WorkTrek

These platforms also provide increased visibility into completed work, improve maintenance planning, enhance documentation, reduce unplanned downtime, and give maintenance managers increased transparency into asset histories.

These digital ecosystems reduce downtime, boost overall efficiency, and foster a unified approach to asset management by seamlessly connecting various operations.

5. Immersive Maintenance with Augmented Reality (AR) and Virtual Reality (VR)

Many professionals, like fighter jet pilots and NFL football players, have embraced AR and VR technologies.

In 2025, we expect immersive technologies like Augmented Reality (AR) and Virtual Reality (VR) to continue transforming maintenance training and execution.

This can significantly benefit maintenance workers and improve overall operational efficiencies. These technologies provide new ways to interact with equipment and train staff.

  • AR tools provide on-the-go overlays of equipment schematics, guiding technicians in real-time.
  • VR simulations immerse maintenance teams in realistic scenarios, enabling skill development without disrupting live operations.
  • AR-enabled glasses enable interactive diagnostics that highlight issues and suggest solutions on-site.
  • Scenario-based learning is facilitated by VR modules designed for advanced troubleshooting and emergency response.
  • Remote collaboration is significantly improved. Maintenance specialists can virtually assist field teams, thus reducing travel and response times.
  • Virtual technology is becoming a more common method for diagnosing and troubleshooting, allowing offsite personnel a near “hands-on” experience.
  • AR/VR can also be used to train technicians without the risk of damaging actual equipment.
Used for AR and VR tools in maintenance
Source: WorkTrek

These technologies significantly enhance the accuracy and effectiveness of maintenance tasks, making them indispensable in complex and high-stakes environments.

6. Decentralized Maintenance Models

The conventional approach of centralized maintenance teams is anticipated to transition towards more adaptable, decentralized structures by 2025.

A decentralized maintenance model distributes maintenance teams and resources across an organization’s areas or departments.

Each team has the authority, expertise, and resources to handle maintenance tasks in their specific area without always needing approval from a central authority. This approach brings several significant advantages:

This evolution is facilitated by IoT monitoring and sophisticated communication tools, enabling remote maintenance and oversight of geographically spread facilities.

This reduces the need for onsite dedicated maintenance technicians and allows for a more distributed model that improves efficiency.

  • Faster Response Times: When maintenance teams are positioned closer to the equipment they service, they can respond more quickly to problems. Instead of waiting for a central maintenance department to dispatch someone from across the facility, local teams can address issues immediately. This is particularly valuable in large facilities where travel time between locations can be significant.
  • Better Understanding of Local Needs: Maintenance teams working consistently in the same area develop deep knowledge of their specific equipment and its quirks. They become familiar with the operating conditions, common problems, and the needs of the operators who use the equipment daily. This local expertise often leads to more effective maintenance strategies.
  • Improved Communication: When maintenance personnel work closely with operations teams in their area, it creates better communication channels. Operators can easily share concerns or observations with maintenance staff they know and see regularly rather than submitting formal requests to a distant central department.
  • More Efficient Resource Use: Each area can maintain its inventory of commonly needed parts and tools, reducing the time spent retrieving supplies from a central location. Teams can also more effectively schedule maintenance activities around local production schedules.

This approach can lower overhead expenses and boost operational flexibility, enabling organizations to adjust to evolving demands swiftly.

Decentralized maintenance models provide a more agile approach to managing maintenance across multiple locations.

7. Edge Computing

In 2025, edge computing is poised to transform data processing in equipment maintenance processes by decentralizing decision-making.

Think of edge computing as having a mini data center right next to your equipment rather than sending all your data to a far-away computer center.

Data on edge computing
Illustration: WorkTrek / Data: itweb

Just as you’d want your maintenance technicians close to the machinery they maintain, edge computing puts computing power right where the action happens – at the “edge” of your network, next to your equipment.

Why does it matter for maintenance monitoring?

Your equipment sensors collect data about temperature, vibration, pressure, and other important metrics. This data travels to a central computer system, often in a distant data center or the cloud. The system processes this information and sends back alerts or insights.

This round trip takes time—sometimes just seconds, but those seconds can matter when dealing with critical equipment issues.

Now, here’s how edge computing transforms this process. Instead of sending all data to a distant location, edge computing devices process information right next to your equipment. These devices are like small, powerful computers that can instantly analyze data and make decisions. They only send the most essential information to the central system, keeping critical processing local.

Benefits to Maintenance Teams

  • Real-Time Response: Edge computing can instantly detect and respond to equipment problems. If a machine shows signs of failure, the edge device can trigger an immediate shutdown or alert, potentially preventing severe damage. This is especially crucial in high-speed manufacturing, where even a slight delay could lead to significant problems.
  • Improved Reliability: Since edge computing doesn’t depend on constant internet connectivity, your monitoring systems will continue working even if network connections are interrupted. The edge devices will continue collecting and analyzing data and storing important information until the connection is restored.
  • Better Data Management: Industrial equipment can generate enormous amounts of data—far more than it is practical to send to a central location. Edge computing lets you process this data locally, sending only the most relevant information to your central systems. For example, it might only transmit data when temperatures exceed normal ranges instead of sending constant temperature readings.
  • More Sophisticated Analysis: Edge devices can run complex analysis programs that would be impractical to run remotely. For instance, they can analyze real-time vibration patterns to detect subtle changes that might indicate developing problems. This kind of immediate, detailed analysis would be difficult or impossible if the data had to travel to a distant location first.

This trend enhances reliability and agility in maintenance, empowering organizations to address operational hurdles proactively.

8. The Rising Importance of Maintenance Metrics

By 2025, maintenance metrics will continue to play an important role and aid in strategic decision-making. In combination with AI and analytics tools, these metrics will

Maintenance and facility managers and organizations increasingly depend on sophisticated analytics to evaluate and benchmark performance across various dimensions, ensuring ongoing improvement and accountability.

  • Mean Time to Repair (MTTR) highlights repair efficiency and minimizes equipment downtime.
  • Asset utilization ratesensure equipment operates at optimal capacity.
  • Monitoring these metrics in real-time empowers organizations to pinpoint inefficiencies, strategically allocate resources, and align maintenance efforts with overarching business objectives.
  • Key metrics also include tracking uptime and unplanned asset downtime.
  • Planned maintenance percentage: is also a key metric, calculated as (planned maintenance hours / total maintenance hours) * 100%.

The focus on metrics shows a move towards data-driven maintenance, where insights are used to improve performance and efficiency.

9. Internet of Things (IoT) Integration

Data on IoT
Illustration: WorkTrek / Data: QServices

IoT devices have continued to proliferate in maintenance organizations. In 2025, we expect this trend to continue.

In a traditional maintenance environment, machines operate independently. Each piece of equipment works independently, and we rely on periodic inspections or apparent failures to know when something needs attention. It’s like having a group working in separate rooms and unable to communicate.

IoT changes this by giving equipment the ability to communicate. Here’s how it works: Small sensors are attached to different parts of your equipment – think of these as the equipment’s “senses.” These sensors can detect temperature, vibration, pressure, speed, and many other conditions. Each sensor connects to a network, allowing it to share this information with other devices and your maintenance management systems.

All these sensors send their data to a central system, creating a complete picture of how each unit is performing. This brings several powerful benefits:

  • Continuous Monitoring: Instead of periodic checks, you now have 24/7 awareness of how your equipment is performing. The system can alert you immediately if anything drifts outside normal parameters.
  • Predictive Maintenance: By collecting and analyzing data over time, IoT systems can learn to predict when equipment is likely to fail. For example, they might notice that a slight increase in vibration often precedes bearing failure, allowing you to replace bearings before they break.
  • System-Wide Optimization: Because all your equipment is connected, you can see how different components affect each other. For example, you might discover that problems with one air handler are making others work harder to compensate.
  • Better Decision Making: With detailed data about equipment use, you can make better maintenance scheduling and replacement decisions. You might find that some units need more frequent maintenance while others could go longer between services.
  • Resource Optimization: IoT can help you optimize resource use by showing when and where maintenance is needed. This prevents over-maintenance (maintaining equipment more often than necessary) and under-maintenance (waiting too long between services).

Looking to the future, IoT continues to evolve with new capabilities:

  • Self-diagnosing equipment that can identify its problems
  • Automated maintenance scheduling based on actual equipment condition
  • Integration with inventory systems to automatically order replacement parts
  • Mobile apps that give maintenance teams instant access to equipment data

10. Additive Manufacturing

In 2025, additive manufacturing will continue to grow for maintenance teams.

What exactly is additive manufacturing? Think of traditional manufacturing, like carving a sculpture from a block of stone – you start with more material than you need and cut away the excess. Additive manufacturing works oppositely, building objects layer by layer, like stacking bread slices to make a sandwich.

Data on additive manufacturing
Illustration: WorkTrek / Data: Precedence Research

Impact on Maintenance

This technology is particularly valuable for maintenance teams because it fundamentally changes how we think about spare parts and repairs. Instead of maintaining large inventories of replacement parts or waiting weeks for specialized components to arrive, maintenance teams can often print what they need on demand.

Key Benefits for Maintenance Teams

  • Reduced Downtime: Instead of waiting days or weeks for replacement parts, many components can be printed within hours. This dramatically reduces equipment downtime and its associated costs.
  • Cost Effectiveness: While the initial investment in 3D printing equipment can be significant, it often pays for itself by:
  • Reducing inventory costs: With 3D printing organization, organizations can eliminate shipping expenses for emergency parts. 3D printing also allows the quick production of otherwise expensive custom components
  • Design Flexibility: Maintenance teams can modify part designs to address recurring failure points and add reinforcement where needed, enabling repairs of parts that might otherwise require complete replacement.
  • Preservation of Legacy Equipment: Additive manufacturing can be a lifesaver for older equipment where parts are no longer available from manufacturers. Teams can scan existing parts to create digital models and recreate discontinued components.

Looking to the Future

The technology continues to evolve, bringing new capabilities:

  • Faster printing speeds
  • More material options
  • Better surface finishes
  • Increased precision
  • The ability to print parts with embedded sensors

Challenges and Opportunities

While these trends offer significant opportunities, there are challenges to overcome. Integrating new technologies into legacy systems requires investment and expertise, and bridging workforce skill gaps requires robust training initiatives.

Cybersecurity remains a key concern as connected systems become more integral. However, these challenges also present opportunities for organizations willing to innovate and adapt to the industry’s evolving demands.

Conclusion

The maintenance industry in 2025 and beyond will be defined by technological innovation, sustainability, and a focus on workforce development.

From AI-driven insights to agile frameworks and immersive technologies, the trends transforming maintenance are poised to redefine its influence across various industries.

Companies that adapt to this evolution will enhance their efficiency and dependability and establish themselves as frontrunners in a swiftly progressing operational environment.

Maintenance has evolved beyond ensuring functionality—it is about forging a path toward a resilient, sustainable, and innovative future.

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