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EMA Releases Report on AI-Driven NetOps Adoption and Execution Challenges


EMA Releases Report on AI-Driven NetOps Adoption and Execution Challenges
  • by: Source Logo
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  • January 21, 2026

Enterprises are rapidly embracing AI-driven network management solutions, both from commercial vendors and through internal development, as they seek to achieve greater automation, efficiency, and insight in increasingly complex network environments. Enterprise Management Associates (EMA), a leading IT research and consulting firm, has published a new report titled "AI-Driven NetOps: How Enterprises are Embracing Intelligent Network Management Solutions," authored by Shamus McGillicuddy, Vice President of Research for Network Infrastructure and Operations.

Quick Intel

  • Only 35% of surveyed organizations consider their AI-driven network management initiatives completely successful, despite high levels of engagement.
  • Data quality emerges as the primary barrier, with issues including collection errors, poor documentation, and proprietary formats directly correlating with lower success rates.
  • 59% of organizations use AI features from network management vendors, and 52% train AI models on their own IT and security data.
  • Confidence remains moderate: 39% fully trust their ability to evaluate AI solutions, and 44% express complete confidence in network data quality for AI use.
  • Adoption has accelerated significantly since 2023, driven by mainstream large language models (LLMs), AI agents, and vendor innovation toward autonomous operations.
  • Network engineers and architects now expect AI capabilities from strategic vendors, marking a major shift from skepticism five years ago.
  • The report identifies emerging best practices to close the execution gap and realize benefits from AI in NetOps.

"Network data quality is the AI killer," McGillicuddy said. "Success with AI-driven networking correlates very strongly with confidence in data quality. Today's network operations struggle with a variety of data issues, including data collection errors, poor documentation, and proprietary data formats. IT organizations must clean up their network data before they invest in AI."

The research tracks the evolution of AI in network operations since 2023, noting a dramatic industry shift fueled by LLMs and AI agents. Vendors are heavily investing in sophisticated AI capabilities beyond traditional machine learning, moving the sector closer to autonomous network management. Enterprises are applying AI across monitoring, troubleshooting, optimization, and predictive analytics, yet challenges in data readiness and evaluation confidence continue to limit full realization of benefits.

EMA's independent study, sponsored by BlueCat, Broadcom, EfficientIP, Gigamon, IBM, Infoblox, and Riverbed, provides a current snapshot of adoption trends, technologies in use, application areas, challenges, realized benefits, and recommended best practices for successful AI integration in network operations.

A free webinar on January 27 will feature Shamus McGillicuddy presenting key findings and actionable steps to bridge the AI execution gap in NetOps. The full report is available for download from EMA's website.

 

About EMA

Founded in 1996, EMA is a leading IT research and consulting firm dedicated to delivering actionable insights across the evolving technology landscape. Through independent research, market analysis, and vendor evaluations, we empower organizations to make well-informed technology decisions. Our team of analysts combines practical experience with a deep understanding of industry best practices and emerging vendor solutions to help clients achieve their strategic objectives.

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