Apr-2025

The strategic value of an industrial data and AI platform

For organisations looking to stay competitive, the choice is clear: data must be treated as a critical, strategic asset.

Cognite

Article Summary

Despite the massive investments in digital transformation over the last many years, companies are still struggling to implement digital transformation and advanced operational use cases such as field operations, data-driven turnarounds, and advanced troubleshooting at scale. As a result, organisations often do not know where to start when it comes to industrial AI and deploying AI agents safely across their operational workflows.

To solve advanced operational use cases, companies must first prioritise simple access to complex industrial data across their organisation. This foundational step is essential to empower their subject matter experts and drive the success of digital applications.

Once a robust industrial data and AI platform is in place, it provides the necessary infrastructure and capabilities to deploy AI and solve industrial use cases at scale. It also helps transform data management from a bottleneck into a business enabler, driving wide-scale implementation and adoption of advanced use cases. Ultimately, the aim is for organisations to be future-ready, with the ability to deploy autonomous AI agents and other advanced AI technologies at scale and as new opportunities emerge (see Figure 1).

From data chaos to data clarity: Key benefits of an industrial data and AI platform
Scaling data-driven solutions across energy and manufacturing companies has historically been difficult due to the complexity and inconsistency of industrial data. Industrial operations are inherently complex, assets have typically been built and changed over literal decades, with some sites being more than 100 years old. This has resulted in multiple legacy source systems, varying data formats, and inconsistent naming conventions (see Figure 2).

Combined with a high degree of operational variability, these factors make deploying digital solutions challenging, expensive, and time-consuming.

In fact, according to Verdantix’s Industrial Transformation Global Corporate Survey 2024, only 6% of organisations surveyed have fully integrated their IT, OT, and engineering data, and 25% of industrial organisations are still collecting data manually and performing analytics periodically rather than in real time.

The fragmented and inconsistent nature of industrial data prevents organisations from unlocking it’s full value. Establishing a future-proof Industrial data and AI platform is a crucial cornerstone for transforming industrial operations delivering multiple benefits, including achieving business KPIs, helping frontline users to solve daily challenges, improving productivity, and streamlining IT processes.

Let’s break down the benefits offered by an industrial and AI platform:

1. Enhanced data management
• Automatic connection and contextualisation of data: Seamlessly connect and make industrial data from multiple source systems and data types accessible and usable across the organisation. Automated, scalable integration and contextualisation ensures that data is not only centralised but also context-rich, actionable, and optimised for analytics and AI.
• Integrated data governance: An industrial data and AI platform enforces data quality standards, applying governance protocols throughout the data lifecycle. This ensures consistency and accuracy, providing stakeholders with reliable data they can trust for critical decision-making.
• Version control and data lineage tracking: Comprehensive data lineage tracking provides transparency and auditability. Teams can trace data back to its origin and understand changes over time, enhancing confidence in data integrity.

2. Solving operational use cases at scale
• Solves real-time operational use cases: Focuses on real-time and near real-time data to solve the next generation of operational use cases, such as predictive maintenance with real-time anomaly detection. This helps prevent costly equipment failures and unexpected shutdowns.
• Ability to scale seamlessly across the enterprise: Facilitates seamless scaling of applications and use cases across multiple units and sites. By utilising a cloud-based SaaS deployment model, industrial companies can ensure their industrial data and AI platform remains efficient and adaptable. It can automatically adjust to changes in demand or performance needs, maintaining high, reliable performance without the need for manual intervention.
• Seamless deployment and enablement of AI agents: Provides the infrastructure and capabilities required to deploy AI agents, including advanced data management and AI capabilities tailored to industrial use cases.

3. Improved collaboration and productivity
• Unified platform for cross-functional teams: Bridges the gap between data scientists, engineers, IT, and business users, providing unified access to the same data and insights. This creates a shared space for collaboration, reduces silos, speeds up decision-making, and ensures consistency across data-driven projects.
• Self-service data access for SMEs: Non-technical users can access and utilise data without extensive training, democratising data usage and allowing IT resources to focus on more complex tasks.
• Centralised knowledge repository: Besides connecting disparate industrial data, an industrial data and AI platform also consolidates documentation, best practices, core workflow records, and more into a centralised repository, streamlining team onboarding and fostering more effective collaboration.

4. Robust safety, security, and compliance
• Interpretability and trust: An industrial data and AI platform enables the creation of an industrial knowledge graph so industrial companies can trust the data and insights to have confidence in their decision-making and deployment of their data and AI solutions.
• Advanced security features: Encryption, multi-factor authentication, role-based access controls, and data governance protect sensitive information by ensuring that only authorised users can access, modify, and share data, all while aligning with corporate and industry standards.
• High compliance standards: Industrial data and AI platforms undergo security testing and third-party audits to ensure compliance with industry standards and regulations.
Business impact of an industrial data and AI platform: Digital transformation at scale

An industrial data and AI platform can deliver significant value through both direct and indirect cost savings. Direct savings come from reduced software licensing and consulting expenses, while indirect savings typically come from avoiding the costs and risks of in-house or “Do-It-Yourself” (DIY) development.

When the platform is established, it enables companies to solve advanced operational use cases. These use cases have eluded the industry for decades as the necessary technology has not been available to help bridge the gap between the office and the field. The use cases include everything from field operations to advanced troubleshooting, and data-driven turnarounds.