The future of industrial information management: Key trends for 2025
Posted: January 30, 2025
Industrial businesses are actively seeking new wins in the new year by focusing on harnessing the power of structured data and accessible information. By capturing fresh insights, industrial companies expect to reach new heights of reliability, operational efficiency, innovation, and sustainable growth. Discover the key trends they expect to shape the future of industrial information management in 2025 and beyond.
- Increased automation and AI integration
Automation and AI integration will continue to drive the demand for reliable, contextualized data in 2025 to develop valuable industrial intelligence.
At the core of industrial automation are AI algorithms that leverage vast amounts of sensor data to learn, adapt, and optimize processes. Machine learning models enable predictive maintenance, optimized scheduling, and autonomous responses, resulting in enhanced operational efficiency and optimized resource utilization.
AI-powered tools also identify patterns, trends, and anomalies in physical asset behavior, enabling data-driven control and faster troubleshooting, resulting in improved resiliency and compliance with quality control standards.
Industry leaders are also using AI to automate routine and repetitive tasks, such as data entry and report generation. Minimizing human interaction can optimize workflows, improve throughput, and reduce human error.
- Focus on data quality and transformation
Enhanced data quality and transformation will be pivotal to information management in 2025. As industries generate ever-greater volumes of data from various sources, the ability to effectively collect, contextualize, and analyze this data is more critical than ever. By investing in robust, high-performance data infrastructure, organizations ensure that the foundation for analysis and industrial intelligence is accurate, consistent, and reliable. This will lead to more accurate insights—and improved decision-making—across businesses.
Data transformation techniques such as user-centered visualization dashboards, reusable data structures (or frameworks), and predefined analytics will play a vital role in unlocking the full potential of industrial data. By integrating data from disparate sources into a single view, organizations can gain a more holistic understanding of their operations. As a result, businesses can identify new opportunities, mitigate risks, and drive innovation.
- Consolidated data platforms
Industrial organizations earn measurable benefits from collecting data generated by various HMI, SCADA, IIoT, and production systems into a common datastore and providing a single source of truth to operations personnel. From there, many organizations aggregate data from multiple locations into a single, cloud-based data hub that offers data access to a broader set of decision-makers, including operations analysts, data scientists, and trusted business partners outside the organization.
In asset-heavy industries, consolidation is being used to optimize the performance of assets like plants, floating production units, and manufacturing platforms. Companies that integrate information from asset design and build functions with real-time operations data can more easily find opportunities to increase reliability, boost output, and reduce maintenance costs.
The next frontier is consolidating the data platform with key data-driven applications to accelerate industrial insight and automate the response to anomaly detection.
- The Internet of Things (IoT) and edge computing
The convergence of IoT and edge computing will continue to dramatically reshape industrial information management. By connecting a vast array of devices and sensors, IoT devices embedded in machinery, and infrastructure, enterprises are generating vast amounts of real-time performance, efficiency, and maintenance data. Edge computing, on the other hand, processes and analyzes this data at source, reducing latency and enabling rapid decision-making. This combination empowers organizations to gain real-time insights into their operations, optimize resource utilization, and improve overall productivity.
In addition, IoT and edge computing will continue to drive the development of predictive maintenance, a proactive approach to equipment maintenance that can significantly reduce downtime and operational costs. By analyzing sensor data, AI-powered systems can predict potential equipment failures and schedule maintenance before they occur. This will enhance the reliability and efficiency of industrial systems, leading to improved product quality and customer satisfaction.
The emergence of autonomous systems, such as self-driving vehicles and robotic systems, also further transforms industrial processes and how information will be managed in the future.
- Connected industrial ecosystems
Supply chain optimization, powered by advanced analytics and AI, will evolve industrial processes in 2025. By leveraging real-time data from various sources, such as IoT devices, transportation systems, and supplier networks, companies can gain higher levels of visibility into their supply chains. This enhanced visibility will enable organizations to identify bottlenecks, optimize inventory levels, and improve delivery times. AI-driven predictive analytics will also be important for forecasting demand fluctuations, anticipating disruptions, and proactively adjusting supply chain strategies.
Supply chain optimization will also drive the adoption of digital supply chain platforms. These platforms will help to streamline communication, collaboration, and information sharing among supply-chain partners. Integrated data will empower businesses to make informed decisions, mitigate risks, and respond to disruptions more effectively. Therefore, the demand will increase for advanced data management tools and platforms that can handle the increasing volume and complexity of supply chain data.
- Increasing use of digital twin technology
Digital twin technology, which uses virtual replicas to optimize the design, build, operation, and enhancement of critical physical assets, is gaining significant traction. Organizations across industries are leveraging their data and experiential models to answer important what-if questions to optimize results.
By simulating real-world scenarios, organizations can identify potential issues and bottlenecks, allowing for proactive adjustments to improve asset performance. These digital twins will enable organizations to monitor and analyze the performance of their equipment and processes in real time. By simulating various scenarios and predicting potential issues, businesses can make informed decisions to accelerate product development cycles, improve quality control, and enhance maintenance outcomes.
Digital twins are increasingly using AI to identify the right data sets for a simulation and build predictive models using historical data. Early adopters are seeing measurable gains in predictive maintenance, remote monitoring, and autonomous operations.
- Hybrid approach to industrial information management
Cloud-based industrial information management (IIM) solutions will continue to grow in popularity in 2025. By migrating their IIM systems to the cloud, organizations can benefit from enhanced scalability, flexibility, and cost-effectiveness. Cloud-based IIM solutions offer continuous access to data and applications from anywhere, enabling remote monitoring, control, and analysis. This increased accessibility empowers teams to collaborate effectively and make timely decisions regardless of their physical location.
In 2025, more organizations will migrate their IIM workloads to the cloud, leveraging the benefits of cloud-native technologies. Hybrid cloud models, combining public and private cloud environments, will become more prevalent, enabling organizations to optimize their IIM infrastructure.
How AVEVA can help
Looking ahead to 2025, new techniques for industrial information management offer many opportunities to add value. Discover how these emerging technologies and best practices can help your organization unlock the full potential of its data, drive innovation, and achieve sustainable growth.
To learn more about how AVEVA’s solutions can help you navigate the evolving landscape of information management, speak to one of our experts today.
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