Gartner Warns AI Operations Will Drive Tool Sprawl and More Frequent IT Failures

According to analyst firm Gartner, by 2030 approximately 25 percent of the tasks currently performed by IT infrastructure and operations staff will be handled by artificial intelligence, even as AI introduces greater complexity and raises the risk of outages.

The prediction was published on July 10 in Gartner’s 2026 Hype Cycle for AI in IT Operations, which outlines the firm’s outlook on AI-powered infrastructure management tooling.

Gartner expects significant challenges before automation delivers meaningful returns.

“Many AI-for-IT-operations narratives promise tool consolidation. Agents will query multiple systems, reason across silos and reduce dependence on specialized tools,” the report states, before forecasting “the opposite outcome in the near term.”

For at least the next few years, organizations will contend with “more layers, more control points, and more specialized observability, orchestration and management capabilities.”

The strain will ease only after “future market and vendor consolidation reduce the overall tooling footprint.”

In the interim, Gartner advises operations teams to plan strategically for a higher probability that AI will contribute to service disruptions.

“By 2028, 40 percent of I&O organizations that use agentic I&O at scale in production will experience a business-critical service disruption, up from less than 1 percent of organizations in 2026,” the document notes.

Despite this risk, adoption is expected to accelerate. Gartner projects that by 2029, 60 percent of enterprises will have deployed agentic AI within IT infrastructure operations, compared with fewer than ten percent today. In that same year, only 20 percent of AI-suggested actions will require human-in-the-loop approval, down from 80 percent in 2025. The shift will be enabled by broader use of “deterministic guardrails” — policy-based rules defining permitted AI behavior.

By 2030, Gartner expects half of all infrastructure and operations teams to have been restructured following investments in agents for complex management work. Remaining staff will use AI for every manual task: “75 percent will be done by humans augmented with AI, and 25 percent will be done by AI alone.”

Gartner identifies the following technologies as near-term maturing enablers of this transition:

Generative AI from “native” vendors that build GenAI into IT ops tools rather than bolting it onto existing products.

GenAI Virtual Assistants offering conversational self-service remediation by connecting with agents to initiate fixes.

Generative AI-Augmented CloudOps that analyze logs, metrics, traces, configuration, and change events to produce scripts or infrastructure-as-code templates, write runbooks, and draft post-incident reports. Cloud providers are developing these tools to address their own complex environments.

Autonomous endpoint management that configures machines to user profiles and applies patches, helping teams keep pace with AI-generated software fixes.

Network AI and Automation that monitors networks, recommends resilience improvements, and provides conversational interfaces for networking equipment. Service providers benefit directly, with downstream performance gains for broader users.

Gartner rates four tools likely to mature within two to five years — Agentic AI Observability, Agentic NetOps, Augmented FinOps, and Multiagent Systems — as the most impactful.

Agentic AI Observability monitors AI agents and flags failures, becoming essential for governance and cost control. Agentic NetOps automates network management. Multiagent Systems coordinate multiple agents on shared tasks. Augmented FinOps applies AI to “algorithmically driven cloud budget planning and financial operations,” automatically optimizing resources and reducing wasteful cloud spend.

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