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Gartner® Market Guide for Utility CIS 2025

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IUCX 2026
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Gartner® Market Guide for Utility CIS 2025
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Why do AI projects fail in utilities?

  • Industry articles

Throughout the adoption of artificial intelligence, utility companies face several challenges that must be addressed to achieve optimal results.

Many utilities operate with legacy systems that are not compatible with the advanced requirements of AI tools. Upgrading to a scalable, cloud-based, and modern infrastructure is crucial for supporting AI integrations, managing large datasets, and ensuring reliable performance. Moreover, due to the large volume of data processing, utilities need systems with a single database and repository to ensure cohesion.

Another major challenge is regulatory compliance and cybersecurity. As utilities adopt AI technologies that often involve sensitive information and automation, they must ensure that all processes comply with industry regulations, data privacy laws, and cybersecurity standards. Equally important is workforce readiness, where employees must be effectively trained to use new tools and understand the insights they generate.

AI succeeds when utilities align modern infrastructure with clear processes, secure data practices, and teams equipped to act on insights.

Is your utility ready to lead with AI—cutting costs and improving CX without a full overhaul?

Discover the transformative vision of a fully integrated, AI-powered utility—efficient, intelligent, and ready for the future.

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