How connected operational intelligence and Industrial AI help organizations anticipate risks, make better decisions, and act with confidence. 

Industrial organizations don’t need more data. They need to connect what’s happening across their operations with the information, decisions, and actions that keep the business moving. Imagine a critical production pump begins showing abnormal vibration and temperature readings – the data is available in the plant’s control systems, but maintenance records exist elsewhere, and the next shift is about to take over. The warning signs are there, but does the team have everything it needs to respond? 

This is a familiar challenge for industrial organizations. Operational information is spread across SCADA systems, historians, sensors, maintenance applications, and enterprise software. Even when teams identify an emerging problem, they may still need to investigate its cause, determine the potential production impact, locate available resources, and coordinate a response. 

The opportunity isn’t simply to detect problems earlier – it’s to connect operational intelligence with the broader business so teams can make informed decisions and take action. That’s where IFS.ai Operational Intelligence and IFS Intelligence come together. 

Start with a Connected Understanding of Operations 

Industrial assets generate enormous volumes of information. Temperature readings, vibration measurements, process conditions, production performance, quality records, and maintenance events all help tell the story of what’s happening across an operation. The challenge is bringing that information together in a way people can actually use. 

IFS.ai Operational Intelligence connects and contextualizes data across industrial systems, including SCADA, historians, sensors, IoT, and other operational sources. Rather than requiring teams to investigate individual systems independently, Operational Intelligence helps them: 

  • Monitor asset health, process conditions, and production performance 
  • Identify abnormal operating patterns and emerging failure indicators 
  • Compare current conditions with historical performance 
  • Investigate operational issues using connected data and diagnostic context 
  • Document findings, outstanding actions, and operational events through case management and shift logs 

That last capability is especially important. Industrial operations don’t stop when one shift ends. If an operator identifies a potential equipment issue at 6:30 p.m., the incoming team needs to know what happened, what has already been investigated, and what still requires attention. 

By capturing operational findings in shift logs and maintaining a record of events and actions, teams can preserve context across handovers instead of starting the investigation again. But understanding what’s happening across operations is only part of the picture. 

Connect Operational Insights with the Rest of the Business 

Consider what happens after an emerging equipment issue is identified. A maintenance planner may need to know whether the asset has experienced similar failures, whether replacement parts are available, which technicians are qualified to perform the work, and how taking the equipment offline could affect production. Those answers often live outside operational monitoring systems. 

IFS Intelligence brings Industrial AI into the broader enterprise, connecting relevant business information, processes, and workflows to help people understand their business, make decisions, and get more work done. Through conversational AI, AI-powered skills, and Digital Workers, IFS Intelligence makes enterprise information easier to access and use, while supporting governed actions within business workflows. For a maintenance planner, that can mean moving beyond the initial operational finding to investigate questions such as: 

  • What maintenance has previously been performed on this asset? 
  • Are there existing work orders related to this issue? 
  • Do we have the necessary replacement parts? 
  • Which qualified technicians are available? 
  • What are the potential production implications of taking this equipment offline? 

Where the relevant systems and information are connected, IFS Intelligence can help bring that context together, summarize findings, and support recommendations for the next steps. 

The result is a more complete understanding of the issue, combining what’s happening at the asset level with what matters across the business. 

From Emerging Asset Risk to Coordinated Response 

Let’s return to the production pump. 

Step 1: Identify and Document the Issue 

IFS.ai Operational Intelligence connects vibration and temperature readings from industrial systems and identifies operating patterns that differ from the pump’s normal conditions. 

By comparing current readings with historical asset performance, the team identifies a potential bearing issue. 

An operational case captures the affected asset, abnormal readings, and investigation findings. The issue and outstanding actions are also recorded in the shift log so the incoming team understands the situation. 

Step 2: Understand the Business Impact 

The maintenance planner uses IFS Intelligence to explore the issue alongside relevant enterprise information. 

With the appropriate systems connected, the planner can review previous maintenance events, check existing work orders, investigate spare-parts availability, and understand resource and production constraints. 

Instead of manually gathering information from multiple applications, the planner can use conversational AI to access relevant context and evaluate the available options. 

Step 3: Coordinate the Response 

With the operational findings and business context available, the planner determines the appropriate maintenance response. 

Depending on the configured workflows, IFS Intelligence can support guided actions, work-order activities, and governed AI-assisted execution. 

Meanwhile, Operational Intelligence maintains the operational case and shift log, preserving the issue status, investigation findings, and outstanding actions for the next team. 

The maintenance team has the information needed to coordinate the work, and the incoming shift can continue the response without repeating the original investigation. 

The business value is clear: earlier identification of risk, less time gathering information, better-informed maintenance decisions, and greater continuity across shifts. 

This scenario illustrates how the combined capabilities can support a connected workflow. Specific integrations and execution capabilities depend on the customer’s configuration. 

Two Complementary Capabilities. Greater Business Value. 

IFS.ai Operational Intelligence and IFS Intelligence address different but connected challenges. 

  • IFS.ai Operational Intelligence provides depth across industrial operations. It unifies operational signals, applies analytics, supports investigations, and helps teams monitor and optimize performance across assets, production, quality, and maintenance. 
  • IFS Intelligence provides breadth across the enterprise. It brings Industrial AI into business information, processes, and workflows, helping people ask questions, understand context, make decisions, and delegate more work to AI within trusted controls. 

Together, they connect operational understanding with enterprise-wide intelligence. 

That combination can help organizations: 

  • Identify emerging risks earlier by connecting operational signals and historical performance 
  • Reduce investigation effort by making relevant operational and enterprise information easier to access 
  • Improve maintenance decisions by considering asset conditions alongside resources, inventory, and production priorities 
  • Preserve operational knowledge through documented cases, shift logs, and connected information 
  • Accelerate response by supporting coordinated decisions and governed workflows 
  • Improve operational performance by connecting asset-level findings with broader business priorities 

And while asset reliability is one practical example, the opportunity extends to production performance, quality, process optimization, and other operational challenges where industrial and enterprise information need to work together. 

Move Beyond Operational Visibility 

Industrial organizations have spent years investing in the systems needed to monitor assets, manage operations, and run the business. The next opportunity is connecting the intelligence those systems provide. 

When teams can understand what’s happening across industrial operations and connect those insights with broader business context, they can move beyond isolated monitoring and manual coordination. 

They can investigate issues faster, make more informed decisions, preserve knowledge across shifts, and put Industrial AI to work where it matters. 

IFS.ai Operational Intelligence and IFS Intelligence bring deep operational understanding and enterprise-wide Industrial AI together, helping organizations move from asset intelligence to intelligent execution.