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
Download Now
Author Information
Mitch Ashley is VP and Practice Lead for the CIO & Technology Buyers and Software Lifecycle Engineering practices at The Futurum Group. A multi-time CIO and CTO with 30+ years leading technical organizations, Mitch built and operated production systems spanning cybersecurity for the U.S. Department of Defense, PKI services for the broadband and 5G industries, SaaS platforms, large-scale telecom and banking systems, and a national broadband network. His work with AI began early, developing expert systems that diagnosed and repaired complex mainframe environments. That operator foundation grounds his analysis in operational consequence, covering the technology buyer's world of software engineering, cybersecurity, DevOps, cloud, and AI.
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.
