Why getting AI‑ready is now critical

Electric and water utilities are entering an era of higher demand, aging infrastructure, workforce constraints, extreme weather, and rising expectations from regulators and customers. Deloitte’s latest industry outlook notes mounting reliability pressure as utilities race to deliver firm capacity while modernizing grids and balancing affordability—conditions that make smarter operations and faster decisions indispensable.

At the same time, leaders are recognizing that AI will only deliver its full value when built on a foundation of trusted data and governance. Accenture’s Technology Vision Utilities research finds that “74% of utility executives believe that AI’s full potential can only be realized when it is built on a foundation of trust.” 

For utilities—where safety, compliance, and service continuity are non‑negotiable—being “AI‑ready” isn’t a buzzword; it’s a critical corporate strategy.

How to get AI‑ready: Build data trust across the full information lifecycle for utilities

A practical approach to becoming AI-ready starts with a trusted data foundation: Unify, govern, and activate enterprise information so AI operates with context, auditability, and confidence. This framework spans five capabilities—discover, derive insights, manage, protect, monitor—that utilities can apply across assets, operations, customer service, and compliance.

• Discover
  Surface and connect the data hiding in silos—engineering files, asset histories, SCADA logs, work orders, permits, and customer records—so it’s accessible and searchable. Discovery establishes lineage and metadata so teams know what information exists and where it came from.
• Derive insights
  Turn raw content into intelligence with analytics and AI to spot patterns (leaks, outages, transformer stress), predict failures, and optimize crews. OpenText’s data discovery and analytics tools are designed to handle petabyte‑scale information and create auditable, explainable outputs that operations can trust.
• Manage
  Govern content and data across lifecycles—from engineering drawings to maintenance records, supply chain information, and financial controls—to ensure the right context, access controls, retention, and interoperability.
  
  Unifying information management at its source reduces rework, accelerates approvals, and provides the traceability regulators require, while ensuring information accurately reflects not only the physical assets in the field but also the business processes that support them across all departments.
• Protect
  Wrap security and identity around sensitive operational and customer data, enforce policies, and maintain compliance across cloud and on‑premises environments. Trusted AI outcomes depend on consistent governance, rights management, and audit trails, especially in critical infrastructure.
• Monitor
  Monitoring closes the loop—keeping AI reliable as conditions change and giving teams evidence to improve processes and retrain models. Observe data flows, apps, and infrastructure across multi‑cloud and hybrid environments. Measure data quality, model performance, and service levels.

AI-ready utilities start with trusted data that is unified, governed, and secure. Building data trust across the lifecycle enables AI to act with context and confidence, driving smarter decisions, resilient operations, and measurable savings in an era of rising energy supply and reliability demands.

The payoff: AI‑enabled utilities will create measurable savings

Utilities don’t have to guess at the value of utilizing information management technologies and best practices to become AI-ready. OpenText is applying these same principles internally using our own technology and expects to save $1 billion USD over the next 10 years by consolidating and rationalizing systems, automating processes, and upgrading digital operations.

Here are the key steps utilities can follow to realize similar results:

1. Data center consolidation and cloud optimization
   Streamline infrastructure, reduce technical debt, and adopt a multi‑cloud strategy to cut costs and improve resilience while putting data closer to the AI services that need it.
2. System rationalization
   Eliminate redundant tools and hardware; standardize on integrated platforms for content, analytics, and observability. Rationalization not only saves money, it simplifies governance and speeds AI deployment.
3. Process improvement through automation and AI
   Automate repetitive tasks (ticket routing, document generation, meter exceptions, outage triage) so teams can focus on innovation, safety, and reliability.
4. Efficiency and productivity enhancements
   Integrate toolchains for developers and operations. A single delivery platform, shared data, and common controls will reduce cycle time and improve service quality.
5. Customer experience transformation
   Use integrated digital operations to improve accuracy, shorten restoration times, and personalize communications for customers, regulators, and field partners.

Ready to start your AI‑readiness journey?
Visit the OpenText AI‑ready information website for practical steps and resources.

Want to see how $1B in savings is possible for AI-enabled utilities?
Download OpenText’s $1 billion savings strategy white paper.