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As the Industrial AI revolution gains momentum, the critical need for robust, high-quality data has become undeniable. The "digital divide" is widening between organizations that effectively leverage AI and those that lag behind, and at the heart of this divide lies the ability to manage and harness industrial data. To address this crucial challenge, the ARC Industry Leadership Forum in Orlando, Feb 10-13, 2025, is hosting a vital session on Industrial-Grade Data Fabrics. Colin Masson will be leading this session on Wednesday, February 12th, at 10:30 AM. We’ll hear from experts from CESMII, High Byte, Koch Industries, and Owens Corning to explore the strategies, technologies, and best practices for building and deploying data fabrics that fuel industrial AI.
The Importance of Data Quality
The success of any AI initiative, especially in the industrial sector, hinges on the quality of the data being used. Our recent ARC survey results illustrate the magnitude of this challenge, with over 50 percent of respondents citing ‘Ensuring Data Quality’ as one of their top three AI implementation challenges. More than 35 percent of respondents also indicated “Finding the right supporting technologies” as a key issue, further emphasizing the need for a robust data management strategy. To ensure accurate and reliable insights from AI models, it is essential to address these challenges by investing in a data foundation that can handle the unique complexities of industrial data.
IT, OT, and BDM Alignment on Industrial Data Fabric Components
While the importance of data quality is universally acknowledged, different functions within an organization may have different perspectives on how to achieve it. Our Q4 2024 Survey question on “Ensuring Data Quality for Industrial AI Solutions”, reveals some interesting areas of alignment and divergence across IT, OT, and BDM audiences on their approach.
Shared Ground—Leveraging Enterprise Apps and Industrial Edge Data: A key point of convergence across all three groups is the recognition of the value of leveraging AI in enterprise applications. This consensus highlights that data and AI models residing within enterprise applications are considered important components in the overall industrial data fabric. This makes sense since many industrial organizations have already invested significantly in enterprise software such as ERP, CRM, PLM, and SCM. Moreover, there's also a clear consensus across all three groups on the need to ingest data from the industrial edge, reflecting a real-world need to connect the physical and digital. The importance of data at the edge is further underscored by the investments companies are making in edge AI hardware and solutions that allow for local processing and low-latency analytics.
BDMs Favor Enterprise Data Fabrics While IT Prefers Cloud Hyperscalers: The survey results reveal that BDM stakeholders are more likely to invest in Enterprise Data Fabrics from the likes of Databricks, Palantir Technologies and Snowflake. This suggests that they see value in a more holistic, enterprise-wide approach to data management. For OT, enterprise data fabrics allows them to align production data with the rest of the business for the insights needed to support higher levels of performance. However, IT professionals are more likely to favor leveraging their cloud hyperscaler's data fabrics. This likely reflects a preference for using standardized, cloud-based platforms they already have established relationships with. These hyperscalers are already investing heavily in data centers to support AI workloads, so there is no doubt that many IT professionals see a cloud hyperscaler platform as a low risk and logical approach.
BDM’s Support for Industrial Analytics: Interestingly, business decision-makers are the most likely to prioritize industrial analytics solutions for OT. This might be driven by their need for better visibility into operational performance and to address any bottlenecks within the organization. This suggests that business decision-makers are looking for actionable insights to drive better business outcomes and may be frustrated with the sparsity of information available to them in many industrial organizations.
Mid-Pack Alignment: Deploying AI on the Industrial Edge
A significant portion of the survey respondents from all three groups indicated that they intend to train their AI in the cloud and deploy on the Industrial Edge. This finding shows a common understanding that while the cloud provides scalability and resources for training complex models, edge deployment is crucial for real-time insights, reducing latency and ensuring operational continuity. Companies are also investing in ruggedized edge devices with local inference capabilities for Industrial AI applications. This also underscores the importance of an Industrial Data Fabric, for managing data across various endpoints and ensuring that AI models have access to all the data they need, wherever they are deployed.
The Importance of Time-Series Data and Industrial IoT
Even the most business-focused BDM audience recognizes the need to handle time-series data. This is shown by the high number of respondents who are investing in Industrial IoT Edge Platforms and Enterprise Data Historians, indicating an awareness of the challenges in incorporating time-sensitive data into their Industrial Data Fabrics. These platforms can help them address the unique challenges of managing data that changes rapidly over time, such as machine logs, sensor data, and other types of OT data.
Don't Miss the ARC Leadership Forum to Learn More
These are just some of the initial insights revealed by our survey, and we will be exploring these results and many others at the ARC Industry Leadership Forum in Orlando, Feb 10-13. This is a great opportunity for IT, OT, and BDM professionals to learn more and share their best practices for implementing AI and assembling industrial-grade data fabrics. I invite you to join me on Wednesday, February 12, at 10:30 AM for an insightful session featuring perspectives from CESMII, High Byte, Koch Industries, and Owens Corning. I look forward to seeing you there!
Register here.
By attending this forum, industrial executives can gain a deeper understanding of how to compete in the new age of Industrial AI, learn from the experiences of industry leaders, and accelerate their digital transformation journeys. This is a great opportunity to network with both technology vendors and industrial end users and help your company get on the right path with your Industrial AI strategy.
For ARC Advisory Group recommendations for navigating the AI Wars, and closing the digital divide by embracing Industrial AI, and governing and guiding major decisions about enterprise, cloud, industrial edge and AI software, please contact Colin Masson at [email protected] and set up a meeting at the ARC Leadership Forum!