Answers
Questions the category actually asks
Each page below answers one question directly, in the first two or three sentences, then goes deeper. Every competitor claim carries a source. Where we have no evidence for something, the page says so.
- Updated September 6, 20264 sources
What is AIOps?
AIOps is the use of machine learning and statistical analysis on monitoring and event data to cut alert noise, correlate signals, and speed detection and diagnosis in IT operations. It is an analysis discipline, not an action discipline, and the field is now shifting toward agentic operations, where software also proposes or takes action under governance.
- Updated October 4, 20264 sources
What is agentic operations?
Agentic operations lets software agents not only detect and diagnose problems but propose, and sometimes take, remediating action under human or policy oversight. Gartner names this shift explicitly as moving "from AIOps to Agentic Ops." Most 2026 platforms ship the propose stage and gate the act stage behind approval, because trust, not capability, is the field's stated blocker.
- Updated October 4, 20264 sources
What is the difference between AIOps and observability?
Observability is instrumenting systems with metrics, logs, and traces so you can ask arbitrary questions about their internal state. AIOps is the analysis layer that watches those signals to reduce noise and infer a probable cause. Observability platforms increasingly ship their own AIOps-style reasoning, which blurs the line in the product but not in the definition.
- Updated October 4, 20261 source
How do you measure MTTR honestly?
MTTR is only a fair number when its formula, start and end events, sample window, and exclusion rules are published alongside it, because a shortened MTTR can just mean stricter ticket-closing rules rather than faster fixes. Before comparing an MTTR figure across vendors, ask for the clock definition, the sample size, and whether it is self-reported or independently measured.
- Updated October 4, 20262 sources
What is an AI control plane?
An AI control plane is the layer that governs what AI agents may know, decide, and do, kept separate from the agents' own reasoning. It holds the role and permission model, the policy that gates a consequential action, and the record of what happened, borrowing the control-plane and data-plane split from networking.
- Updated October 4, 20262 sources
How do you audit an AI agent?
Auditing an AI agent means checking five things independently of what the agent or its vendor claims: identity and authority ceiling, what it may read, what it may act on and under whose approval, whether outputs carry a receipt to a source, and whether it says "not measured" honestly. Ask to operate the audit yourself rather than watch a narrated demo of one.
- Updated October 4, 20261 source
What is AI-native compliance?
AI-native compliance means the evidence an auditor needs is produced as a byproduct of the system running, not assembled afterward from screenshots and interviews. It means continuous, tamper-evident records of decisions and approvals rather than periodic manual attestation, applied to how AI agents are governed as much as to the systems they operate.
- Updated October 4, 20263 sources
What does separation of duties mean for autonomous systems?
Separation of duties prevents one principal from performing incompatible steps on the same action. In HELM by LockedIn Labs, the proposer cannot approve their own proposal; role permissions separately control execution, policy editing and audit access. An authorized independent approver may also execute.
- Updated October 4, 20265 sources
How do you evaluate an AIOps or agentic-operations vendor?
Evaluate a vendor on what you can operate yourself, not watch demonstrated: the permission and separation-of-duties model, the basis behind every headline number, whether autonomy is a visible gated dial, and whether the agent's reasoning is a replayable trace rather than a narrated claim. A vendor that shows only finished claims and stays silent about gaps is worth treating with suspicion.
- Updated October 4, 20262 sources
What does "AI-native" mean in operations software?
AI-native in operations means a decision, with its evidence and accountability attached, is the system's core object, produced by the operating loop itself, rather than an AI feature added onto a dashboard or ticketing tool built for a human to type into. A useful test: does removing the AI leave a coherent product, or leave nothing.
- Updated October 4, 20262 sources
How do you calculate the return on an AI operations platform?
Price each benefit using a measured quantity, a rate and an annual multiplier, then remove overlap before comparing the total with fully loaded costs. Calculate cash-flow payback separately from upfront investment and net monthly realized benefit after recurring costs. Publish the assumptions and distinguish modeled benefit, recovered capacity and cash savings.