Agentic Operations
Agentic Operations
Automation handles the routine. Agentic operations handles the exceptions.
Agentic operations overview
What is agentic operations?
Agentic operations — agentic ops for short — is AI that observes, reasons and acts within governance boundaries you control. Most IT organizations have hit the ceiling of scripted automation: scripts handle what's known, and everything outside the playbook still lands on a person. Agentic operations is the roadmap from that ceiling to self-healing IT.
3%
Of the ~2,000 alerts a typical enterprise sees each week, only 3% need action.
Source: PagerDuty research, via DevOps.com
50%
AIOps plus observability can cut resolution time in half.
Source: Forrester Consulting study, commissioned by IBM
157%
Three-year ROI for a composite organization.
Source: Forrester Consulting TEI study, commissioned by ScienceLogic
Components of Agentic Ops
Four pillars
AIOps is the diagnostic layer. Agentic operations is the resolution layer built on top of it, and the gap between the two is where most operations teams get stuck today.
Single Source of Truth
Fragmented visibility and unreliable data force IT teams into reactive, all-hands response every time something breaks. This pillar establishes the source of truth agentic AI depends on. Governance requires visibility; automation requires reliability.
Repeatable & Reliable
Before AI can act on its own, automation must be safe, consistent and governed. Policy-as-code makes every action defined, auditable and repeatable. This is the action layer agents execute through, and the layer that earns expanded authority.
360 Perspective
Monitoring silos leave enormous volumes of signal unanalyzed across closed platforms. Unified telemetry and event correlation give agents context spanning application, infrastructure and network. Agents act on the full picture, not a partial one.
Trusted Automation
Rule-based automation stops at the playbook's edge; the exceptions still need judgment. AI agents reason through incidents and execute approved actions inside boundaries your team defines. Autonomy is earned incrementally.
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Capabilities
Where agentic operations fits
Agentic operations unifies automation, AIOps and AI under a single operating model. It runs through four familiar domains:
Observability & AIOps
Cross-domain signal correlation as the control plane for agentic AI. No single-domain monitoring tool can power an agent that acts across your entire environment.
Infrastructure Automation
The action layer agentic AI executes through. Deterministic, policy-as-code automation is the prerequisite for trusted autonomous action.
Enterprise Service Management
Agentic ITSM: autonomous ticket resolution, routing, and workflow management powered by ServiceNow Action Fabric.
Platform Engineering & DevOps
AI-powered software delivery and the agentic SDLC, where agentic operations meets the development pipeline.
Methodology
The operating cycle for agentic operations
We apply a six-stage operating cycle to every agentic ops engagement:
Observe
Telemetry pipelines collect and normalize metrics, logs, traces, alerts and events across the infrastructure.
Correlate
Cross-domain correlation surfaces true incidents from noise and eliminates alert storms and fragmented escalations.
Reason
Agents draw on your source of truth, runbooks, CMDB history and configuration data to work through ambiguity the way a seasoned engineer would.
Decide
Options get evaluated against your policies, risk guardrails and governance rules, with a full audit trail.
Execute
Approved actions run reliably at machine speed: remediation, provisioning, configuration management, ITSM updates.
Validate
Outcomes get confirmed and fed back into the system, so accuracy improves with every cycle.
How WWT can help
How does an Agentic Ops engagement work?
Every engagement follows the same arc: start from the foundations you have, prove value before production and expand autonomy as it's earned.
Start where you stand
An AIOps maturity assessment maps your automation, data and observability foundations, showing what's ready to support agentic AI today, what needs hardening first and the shortest path to trusted autonomy.
Prove it before production
Your use cases run against your architecture in the Advanced Technology Center. You see agents resolving real incidents in a real environment before anything touches production, so the decision to commit is based on evidence, not a demo.
Expand as trust builds
Low-risk, high-value workflows come first. Agent authority widens as outcomes earn it, inside the governance and risk boundaries your team defines. Autonomy is a result, not a starting point.
One team, start to finish
The people who design your operating model are the people who implement it. Strategy, engineering and operations work as one team, so nothing is lost in the handoff from plan to production.
Industries
Financial Services
Autonomous incident response and operational resilience within regulated, audited environments.
Utilities
Autonomous monitoring and incident response across geographically distributed energy infrastructure, reducing outage risk and bridging the gap between OT and IT operations.
Global Service Provider
Autonomous IT operations at carrier scale, reducing MTTR and operational overhead across complex, multi-tenant network environments with continuous SLA visibility.
Manufacturing
Protecting physical operations and the OT systems that run them, with agentic AI as the monitoring layer.
Retail
Managing IT risk and operational continuity across distributed, high-volume environments at scale.
Healthcare
Proactive IT operations that protect care delivery without disrupting clinical workflows.
Partners
The power of partnerships
For many organizations, performing critical R&D functions devours a tremendous amount of time, talent and money. We host our PoC engagements in the Advanced Technology Center (ATC) — a physical campus of data centers and labs where agentic workflows run against multi-vendor, production-like environments before anything touches yours.
Agentic operations experts
Meet our experts
FAQs
Monitoring is the set of foundational, tool-based capabilities used to watch the health and performance of the stack — things like application performance monitoring, end user monitoring, infrastructure monitoring, network monitoring, database monitoring, cloud monitoring, public internet monitoring, and security monitoring
Observability is more than monitoring — it's the ability to collect and correlate telemetry from across systems, tools, and domains into one actionable, enterprise-wide view so teams can reduce noise, surface root cause faster, and enable intelligent automation/self-healing.
AIOps and Agentic Operations are related but distinct. AIOps uses ML and AI to surface insights and recommend actions — a human still decides what to do. Agentic Operations adds agency: AI systems that reason through problems and take approved actions autonomously. Think of AIOps as the diagnostic layer and Agentic Operations as the resolution layer built on top of it. Most clients already have AIOps. Agentic Operations is where it goes next.
No. WWT's approach starts with what you have. The foundation-first methodology adds a data truth layer, strengthens policy-as-code automation, and unifies observability before introducing agentic AI. In most engagements, existing tooling becomes more valuable — not obsolete. The goal isn't a rip-and-replace; it's making your investments compound.
Most agentic ops engagements begin with an AIOps maturity assessment or an AI Proving Ground session — a structured evaluation of where your observability, automation, and data foundations stand today, followed by a prioritized roadmap for introducing agentic AI safely. First use cases are typically low-risk: root cause analysis acceleration, alert noise reduction, or ITSM streamlining. The goal of the first engagement is demonstrated value and organizational trust, not full autonomy.