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Powering AI Securely: How an Entergy Company Secures Critical Operational Data Across Its Value Chain

“AI is transforming how we operate, but it also increases the risks of exposing sensitive operational data. We needed to ensure that the data fueling our systems remained protected at all times.”

The Highlights

Industry

Energy / Critical Infrastructure

Challenges

  • Increased exposure of operational data with AI adoption
  • Uncontrolled file sharing across partners
  • Limited control and visibility after data leaves systems

Solutions

Results

  • Secure AI-driven operations with continuous protection of critical data
  • Full visibility and control over data across internal teams and external partners
  • Stronger compliance and reduced risks without disrupting workflows

About The Company

A global energy provider operating across power generation, distribution, and infrastructure management is undergoing a large-scale digital transformation. With increasing adoption of AI and data-driven systems, it manages vast volumes of sensitive data, including engineering designs, operational procedures, and infrastructure documentation.

Business Challenge

As the company expanded its use of digital technologies and AI-driven systems, it increasingly relied on large volumes of operational data flowing across systems, teams, and external stakeholders. AI-assisted workflows increasingly utilize sensitive operational datasets, including plant schematics, grid operation data, and maintenance documentation, to generate accurate insights.

However, the shift significantly expanded the organization’s data exposure surface. Operational data was no longer confined to internal systems. It was continuously accessed, shared, and reused across cloud environments, partner ecosystems, and field operations. In many cases, data was extracted into files and shared externally, where traditional security controls no longer applied.

This created critical risks: sensitive data could be accessed or reused beyond intended contexts, external contractors could retain access long after projects ended, and AI-driven workflows introduced new pathways for unintended data exposure. Without visibility into how data was being used by AI-enabled processes, the organization faced growing challenges in maintaining control and ensuring compliance.

Customer's Main Requirements

To address these challenges, the company required a solution that could:

  • Protect sensitive operational data used in AI-driven workflows
  • Maintain control over files even after they are shared across systems and partners
  • Restrict unauthorized actions such as copying, downloading, and screen capture
  • Revoke or expire access to data when roles, projects, and partnerships change
  • Gain visibility into how critical data is accessed and used across both human and AI interactions

The Highlights

Industry

Energy / Critical Infrastructure

Challenges

  • Increased exposure of operational data with AI adoption
  • Uncontrolled file sharing across partners
  • Limited control and visibility after data leaves systems

Solutions

Results

  • Secure AI-driven operations with continuous protection of critical data
  • Full visibility and control over data across internal teams and external partners
  • Stronger compliance and reduced risks without disrupting workflows

Fasoo's Solution

To securely enable AI adoption, the company implemented a data-centric security strategy anchored by Fasoo Enterprise DRM (FED). FED applies persistent encryption and dynamic access control directly to files, ensuring that sensitive operational data remains protected regardless of where it is accessed or used. This allowed the company to securely provide AI systems and users with controlled access to data, while maintaining strict governance over who could view, edit, or share it.

To support AI-ready data management, the company deployed Fasoo Data Radar (FDR) to discover and classify sensitive operational data across distributed environments. FDR provided visibility into where critical data resided and how it was being used, enabling the organization to apply appropriate protection policies before data was utilized in AI workflows.

In addition, Fasoo Smart Screen (FSS) was implemented to mitigate screen-level data exposure risks, particularly in remote access and field environments where AI-generated insights and operational data are frequently viewed. By applying dynamic watermarks and preventing screen capture attempts, FSS reduced the risk of sensitive information being leaked through visual channels.

Together, these solutions ensured that data remained protected, controlled, and visible throughout its lifecycle, supporting both secure AI adoption and operational resilience.

Results

By embedding security directly into its data, the company was able to accelerate AI adoption without increasing risks. Sensitive operational data remained continuously protected across AI workflows, internal systems, and external collaborations, enabling the organization to innovate with confidence.

The company also gained end-to-end visibility into how data was accessed and used, including interactions involving AI systems. This improved its ability to enforce governance policies, detect potential risks, and meet regulatory requirements.

Ultimately, the organization established a secure foundation for AI-driven operations, balancing innovation with control and ensuring that the critical operational data remained protected across internal and external workflows.

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