Systems of Record are Dying

We have written before about how Systems of Record (SORs) are not enough to meet the unique, real-time needs of production engineers, operations, maintenance, reliability teams, and other subject matter experts (SMEs) who require simple, performant, and interactive access to industrial data. These SMEs also need a System of Engagement (SOE) designed for industrial environments, with an interactive-level user-friendly experience, self-service, and automation to help users quickly access the data they need.

As generative AI rapidly evolves and matures, we are seeing traditional SORs challenged in another way. We are approaching a future where AI-driven agents can take on roles that traditionally require specialized software tailored to specific business processes. These agents can revolutionize company operations by automating decision-making and execution in complex environments.

Existing Challenges with SORs

Traditional enterprise software providers that function as an SOR have a common business model to cater to enterprise needs:

They are considered sources of truth for data in their domain.
Their platforms are highly configurable and customizable, aiming to tailor their solutions to the specific business process configuration of the customer.
They are extensible, leveraging third parties to build specific solutions that solve business problems beyond the scope of the platform itself.

That said, these SORs often come with a set of lock-in effects that can pose challenges to the organizations dependent upon them:

Data Integration and Migration Costs

Complexity of Data Migration: SORs often manage vast amounts of critical business data. Migrating this data to another platform can be highly complex, costly, and time-consuming, especially when dealing with sensitive or regulated data.
Data Customization: Over time, data structures are tailored specifically to each company’s needs, making extraction and reconfiguration in a new system challenging.

High Customization and Tailored Workflows

Custom Implementations: SORs are often heavily customized to fit the exact needs of each customer’s business processes. Recreating these customizations on another platform can require significant reimplementation effort.
Third-Party Integrations: These platforms typically integrate deeply with other enterprise systems (e.g., financial software, supply chain management systems). Switching providers could break these integrations, requiring time and money to rebuild.

Ecosystem and Vendor Dependency

Ecosystem of Partners and Applications: SORs often have extensive ecosystems of third-party apps and partners that integrate seamlessly with their platforms. When a company switches providers, it may lose access to these established and critical applications or integrations, necessitating replacements.
Vendor Lock-in: Customers who rely on SORs for support, implementation, and updates are often dependent on the vendor for ongoing maintenance and system upgrades. Changing providers requires finding a new vendor ecosystem and support structure.

Switching Costs

Financial Costs: The direct cost of switching to a new platform is often high, not only in terms of the software license fees but also in terms of system integration, professional services, and the need for external consultants to ensure a smooth transition.
Risk of Business Disruption: Switching core SOR systems introduces the risk of downtime or operational inefficiencies during the transition. This risk acts as a deterrent to changing platforms.

Compliance and Regulatory Alignment

Regulatory Compliance: Many companies use SORs to comply with industry regulations. Switching to a new system requires ensuring that the new platform can meet these regulatory requirements, which could be complex and risky.

The Paradigm Shift

The emergence of agents will directly impact SORs. In contrast with traditional software, which is rule-based and requires specific programming for each task, agents are adaptable. If the LLM and the agent are robust enough to navigate the enterprise data effectively, they can answer questions and perform actions previously reserved for specialized software or custom workflows in systems like SAP.

With Cognite Data Fusion® as an SOE and Cognite Atlas AI™ as a comprehensive AI infrastructure that enables industrial AI Agents - Cognite is well-positioned to disrupt the traditional enterprise software market and bring added value to conventional SOR players. We have experience working with data from SORs like SAP, Salesforce, Aveva, ERP, CRM, and more to enable:

A Mature and Robust Industrial Knowledge Graph

Traditional SORs struggle with fragmented, siloed, and inconsistent data that complicates integration and migration. Cognite’s Industrial Knowledge Graph allows customers to rapidly model and organize their data at scale, breaking down silos and ensuring data is accurate, consistent, and governed. This unified data foundation enables SMEs and AI agents to access the right data efficiently, driving faster decision-making and improved outcomes.

Seamless Integration with Existing Ecosystems

High switching costs and the risk of disrupting established integrations deter companies from transitioning to new platforms. Cognite’s platform is designed to work in tandem with existing systems, minimizing disruptions and leveraging the customer’s current ecosystem of tools and processes. Our API-first approach and focus on interoperability ensure smooth interactions between legacy systems and new AI-driven workflows.

A Reliable Infrastructure for AI Agents

Traditional SORs lack the adaptability needed for dynamic, AI-driven automation and decision-making. Cognite’s platform provides a secure and scalable infrastructure to deploy, manage, and monitor AI agents effectively. These agents can perform complex tasks—such as analyzing maintenance data, generating operational insights, or automating repetitive processes—without needing predefined rules or workflows.

Cost-effective and Rapid Application Development

Customization and tailored workflows in legacy systems often result in high costs and long development cycles. Cognite’s tools empower SMEs to build and iterate applications quickly, meeting diverse needs. This reduces development time and cost while enabling companies to respond rapidly to changing market demands and operational challenges.

Enhanced User and Agent Collaboration

Legacy systems often lack user-friendly, interactive experiences, limiting the ability of SMEs to leverage data effectively. Cognite provides an intuitive interface designed for industrial environments, fostering self-service and collaboration between human experts and AI agents. This enables SMEs to harness the power of AI without requiring deep technical expertise, improving productivity and user satisfaction.

Improved ROI on Industrial Data Investments

The complexity and rigidity of SORs often lead to the underutilization of industrial data. By enabling companies to derive actionable insights and automate tasks through AI-driven solutions, Cognite maximizes the value of their data investments. This reduces dependency on legacy systems and aligns technology spending with measurable business outcomes.

By bringing additional value-added capabilities to traditional SORs and enabling agile, AI-driven solutions, Cognite helps companies overcome the challenges of legacy systems, reduce operational friction, and unlock new opportunities for innovation and growth.

To learn more about how Cognite meets the evolving demands of the industrial sector and the value you can bring to your traditional SORs, connect with one of our industry experts.