Artificial intelligence is pushing networks into a new era, and the impact is showing up first at the edge. As organizations place AI-driven workloads closer to where data is created and acted on, expectations around speed, security, and reliability continue to climb.
To understand how IT leaders are managing this shift, technology strategist and industry analyst Bill Kleyman has released “AI and the New Edge of Resilience,” an in-depth look at how AI adoption is reshaping infrastructure strategy, where new pressure points are forming, and how resilience must evolve in a world of distributed intelligence.
Drawing on real-world examples, current market signals, and insights from global technology leaders, the report highlights what teams are encountering today and what they should be planning for next.
Here are a few of the themes inside.
AI Is Moving to the Edge Faster Than Expected
AI workloads are no longer limited to large, centralized environments. They’re rapidly moving to the edge, where low latency, real-time inference, and localized processing are essential.
Kleyman notes the accelerating pace behind this shift as organizations scale edge deployments to support:
- Real-time analytics and inference across industrial, financial, and retail environments
- AI-enabled automation that depends on immediate, reliable decision-making
- More autonomous edge sites capable of operating without constant human intervention
As this movement picks up speed, it brings a new set of resilience requirements for infrastructure teams.
Resilience Is Becoming the Core Requirement for AI
AI-driven operations amplify both the value and risk of today’s networks. As environments become more distributed and automated, downtime carries greater operational impact. Kleyman points to several signals:
- Decentralized workloads increase the blast radius of outages, with decisions happening across multiple layers
- AI systems depend on large, always-available datasets, making disruptions more costly
- Many edge locations are unmanned, so recovery hinges on remote access that works even when primary connections fail
The report underscores a central idea: AI may expand what infrastructure can deliver, but resilience determines what it can sustain.
The Edge Is Now a Strategic Priority
As organizations grow their AI capabilities, the edge is shifting from a peripheral layer to a strategic focal point. Kleyman’s research shows a strong alignment around:
- Bringing processing closer to data sources to reduce latency
- Building distributed architectures that support rapid AI scale
- Designing networks that remain available under stress, whether from outages, cyber events, or system overload
These trends reflect what many IT teams already see in the field: the edge is now a critical part of how AI will operate moving forward.
Why Resilience Must Quickly Evolve
The report outlines several ways infrastructure teams can strengthen their posture as AI adoption accelerates, including:
- Designing distributed systems that avoid single points of failure
- Improving remote visibility and control at unmanned sites
- Increasing the independence of management access
- Expanding automation while maintaining human oversight
Kleyman notes that as AI brings added complexity, infrastructure must be ready to withstand that complexity, not strain under it.
A New Era, Defined by AI and Resilience
Kleyman closes with a succinct observation: “AI will redefine what networks can do. Resilience will define which ones survive.” The balance between AI’s potential and the infrastructure required to support it is shaping the next phase of IT strategy. Organizations that prioritize resilience today will be positioned to scale AI with confidence and control.
Get the Full Report
Bill Kleyman’s “AI and the New Edge of Resilience” offers a detailed look at where AI is heading, how edge computing is evolving, and what IT teams should prioritize as they architect modern, distributed environments.
Download the full report to explore the complete findings and recommendations.
