Research

Data Fitness for AI-Driven Operations

Data Fitness for AI-Driven Operations

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As organizations push AI deeper into operational environments, the speed and autonomy of machine-driven decision-making are beginning to outpace the data foundations built for human investigation. Traditional observability approaches were designed to help engineers reconstruct events after the fact, often across fragmented tools, sampled telemetry, and incomplete signals. But as AI systems move from analysis to action, those same limitations can introduce risk, ambiguity, and costly errors. Futurum Research argues that this shift creates a new strategic requirement: Data fitness.

Data fitness goes beyond conventional notions of data quality or observability maturity. It asks whether the data consumed by AI is sufficiently reliable, timely, contextual, and complete to support action at a given level of autonomy. As AI-assisted operations evolve into agentic operations, technology leaders must reassess whether existing telemetry strategies can support machine-speed execution responsibly. The most effective approaches will align telemetry confidence, operational context, and accountability with the growing scope of AI-driven automation.

In our latest market brief, Data Fitness for AI-Driven Operations, completed in partnership with NETSCOUT, Futurum Research examines why observability alone is no longer sufficient as AI begins to operate at machine speed. The brief explores the operational risks created by incomplete or abstracted telemetry, outlines the core attributes of fit-for-purpose data for AI-driven environments, and discusses how organizations should think about telemetry strategy as autonomy expands. It also highlights how network-derived telemetry can complement application-level observability to close critical visibility gaps across increasingly complex environments.

In this brief, you will learn:
  • Why telemetry built for human-speed investigation may not support AI acting autonomously at machine speed
  • What “data fitness” means in the context of AI-assisted and agentic operations
  • Which core data attributes matter most when AI systems are expected to act with accountability
  • How organizations should align telemetry confidence with autonomy levels and operational risk
  • How NETSCOUT positions network-derived telemetry as a complementary source of interaction visibility for AI-driven operations
If you are interested in learning more, be sure to download your copy of Data Fitness for AI-Driven Operations today.

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Author Information

Mitch Ashley is VP and Practice Lead of Software Lifecycle Engineering for The Futurum Group. Mitch has over 30+ years of experience as an entrepreneur, industry analyst, product development, and IT leader, with expertise in software engineering, cybersecurity, DevOps, DevSecOps, cloud, and AI. As an entrepreneur, CTO, CIO, and head of engineering, Mitch led the creation of award-winning cybersecurity products utilized in the private and public sectors, including the U.S. Department of Defense and all military branches. Mitch also led managed PKI services for broadband, Wi-Fi, IoT, energy management and 5G industries, product certification test labs, an online SaaS (93m transactions annually), and the development of video-on-demand and Internet cable services, and a national broadband network.

Mitch shares his experiences as an analyst, keynote and conference speaker, panelist, host, moderator, and expert interviewer discussing CIO/CTO leadership, product and software development, DevOps, DevSecOps, containerization, container orchestration, AI/ML/GenAI, platform engineering, SRE, and cybersecurity. He publishes his research on futurumgroup.com and TechstrongResearch.com/resources. He hosts multiple award-winning video and podcast series, including DevOps Unbound, CISO Talk, and Techstrong Gang.

Fernando Montenegro serves as the Vice President & Practice Lead for Cybersecurity & Resilience at The Futurum Group. In this role, he leads the development and execution of the Cybersecurity research agenda, working closely with the team to drive the practice's growth. His research focuses on addressing critical topics in modern cybersecurity. These include the multifaceted role of AI in cybersecurity, strategies for managing an ever-expanding attack surface, and the evolution of cybersecurity architectures toward more platform-oriented solutions.

Before joining The Futurum Group, Fernando held senior industry analyst roles at Omdia, S&P Global, and 451 Research. His career also includes diverse roles in customer support, security, IT operations, professional services, and sales engineering. He has worked with pioneering Internet Service Providers, established security vendors, and startups across North and South America.

Fernando holds a Bachelor’s degree in Computer Science from Universidade Federal do Rio Grande do Sul in Brazil and various industry certifications. Although he is originally from Brazil, he has been based in Toronto, Canada, for many years.

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