Why AI projects fail without the right data — and what it means for telecoms.

The message is clear: without strong data foundations, even the most ambitious AI strategies are likely to fail.

For telecoms providers, this insight is especially urgent. As networks become more complex and customer expectations rise, AI is increasingly relied upon for predictive maintenance, anomaly detection, and service assurance. Yet traditional data management practices — often siloed, rigid, and slow — are no longer fit for an AI-driven environment.

Gartner emphasizes that real-time, high-quality, and context-rich data, built on an AI-ready data infrastructure, is critical to future-proofing data-driven operations. To achieve this, telecoms organisations should focus on four key capability areas that align with Gartner’s guidance:

• Data observability: Continuously monitoring data quality and flow across network layers.

• Metadata enrichment: Making data more discoverable, contextual, and usable for AI models.

• Governance and compliance: Ensuring data used in AI is ethically sourced, secure, and legally compliant.

• Live data pipelines: Feeding AI systems with up-to-date insights to enable faster, smarter decisions.

It can’t be a whim. It has to become regular business practice.

As Gartner advises, AI-ready data is not a one-time fix; a continuous, business-as-usual discipline that evolves alongside AI use cases, is the only

With Numo Data, telecoms providers can mature their data foundations in line with Gartner’s recommendations — unlocking the full potential of AI for intelligent network assurance and delivering a truly seamless customer experience.

_{*Source: Gartner®, Lack of AI-ready Data Puts AI Projects At Risk, Q&A with Roxane Edjlali, STAMFORD, Conn., February 26, 2025. GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.}