Introduction

A major utility enterprise operating critical energy infrastructure across multiple regions set out to prepare its workforce for an AI-driven future. With more than 17,000 employees and a newly defined AI strategy in place, leadership recognized that technology and governance alone would not be enough. Long-term success depended on building the right skills, mindsets, and organizational structures to enable people to confidently adopt and scale AI across the business.

The Story

While the organization had made strong progress defining its AI vision and strategic priorities, execution revealed a different challenge. AI initiatives depended heavily on a small number of experts, while most teams lacked the confidence or knowledge to engage meaningfully with AI-driven projects.

Kibit Solutions partnered with the organization to focus on the human side of transformation. Over a twelve-month People, Process & Enablement program, the emphasis shifted toward developing internal talent, breaking down silos, and fostering a culture where experimentation and learning were actively encouraged.

Rather than treating enablement as a one-time training effort, the program embedded AI capability into everyday work, combining structured learning, hands-on experimentation, and clear career pathways tailored to the utility sector.

The Challenge

Several people- and culture-related barriers slowed AI adoption.

AI talent was scarce, and the organization lacked a clear strategy for deciding which capabilities to build internally versus source externally. AI literacy varied widely, from engineers unfamiliar with AI tools to leaders unsure how to assess opportunities and risks. Knowledge from pilot projects remained isolated within small teams, limiting reuse and organizational learning.

A risk-averse culture discouraged experimentation, and training efforts were fragmented, often driven by vendors and disconnected from real business needs. Without addressing these challenges, the AI strategy risked underperforming due to limited execution capability.

The Results

By focusing on people, skills, and culture, the organization achieved sustainable, enterprise-wide impact:

Talent development: More than a dozen employees transitioned into formal AI roles, reducing reliance on external consultants by 60% within the first year.

AI literacy: Over 90% of 10,000+ employees completed AI training, creating a shared language and enabling leaders to proactively identify AI opportunities.

Innovation culture: More than 70 AI pilots were launched in the first year, supported by a safe experimentation environment and internal innovation funding.

Collaboration and alignment: Cross-functional delivery became standard practice, with rotational programs improving collaboration between domain experts and data teams.

Sustainable capability: An internal AI Academy now trains over 300 employees annually, cutting external training costs by 70%.

Business impact: New capabilities enabled AI initiatives delivering more than €15 million in measurable savings and efficiency gains within 18 months.

Cultural shift: A traditionally risk-averse organization evolved into one that values experimentation, continuous learning, and shared ownership of innovation.