Introduction

A leading national utility company with more than 10,000 employees set out to bring structure and clarity to its growing use of artificial intelligence. Operating across semi-autonomous regional branches responsible for power generation, transmission, and distribution, the organization faced increasing regulatory pressure and rising expectations for operational efficiency. As AI initiatives multiplied across the business, leadership recognized the need for a unified strategy and governance model to ensure compliance, scalability, and measurable business value.

The Story

AI adoption had emerged organically across the organization, driven by local teams experimenting with data-driven solutions to improve operations. While this bottom-up innovation created momentum, it also introduced fragmentation. Different regions pursued similar use cases using incompatible tools, platforms, and external partners, making it difficult to scale successful initiatives or maintain consistent oversight.

Kibit Solutions partnered with executive leadership to shift the organization from isolated experimentation to a coordinated, enterprise-wide AI approach. The engagement focused on aligning AI initiatives with corporate strategy while establishing clear governance, shared technology foundations, and internal capabilities that could support long-term transformation.

Through executive workshops, maturity assessments, and collaborative planning, the organization began building a common understanding of how AI should be developed, governed, and scaled across all regions.

The Challenge

Several structural challenges limited the organization’s ability to realize value from AI.

Independent initiatives across regional branches led to duplicated efforts, inconsistent tooling, and incompatible platforms. Without a unified AI vision, leadership lacked visibility into the overall portfolio and struggled to link projects to strategic objectives. AI expertise varied widely across the organization, resulting in heavy reliance on external consultants and limited knowledge transfer.

At the same time, the absence of governance frameworks created risks. There were no standardized processes for evaluating, prioritizing, or scaling AI initiatives, and compliance and ethical considerations were handled inconsistently. Without intervention, the organization risked inefficient investment, limited value realization, and potential regulatory exposure.

The Results

By establishing a structured AI Strategy & Governance framework, the organization achieved significant improvements:

Strategic alignment: A unified AI vision and three-year roadmap provided leadership with clear visibility into initiatives, investments, and outcomes across all regions.

Governance and risk control: Standardized approval workflows, risk classification, and ethical AI policies reduced duplication and strengthened compliance.

Technology enablement: A unified enterprise AI architecture reduced system fragmentation and enabled scalable, compliant operations across cloud and on-premise environments.

Capability development: Structured upskilling and the establishment of an AI Center of Excellence strengthened internal expertise and reduced dependency on external advisors.

Financial impact: Consolidation and improved coordination delivered an estimated 30–40% reduction in total AI investment costs.

The organization is now positioned to scale AI initiatives confidently, balancing innovation with governance while delivering measurable value across its operations.