AIOps · 05 of 5

Adoption

Why AIOps, then assess, pilot, standardise and scale, with guardrails from day one.

How an engagement runs

Assessbaseline and use cases
Select & pilotlow risk, good data
Visualise & compareoptions on cost
Standardisearchitecture as code
Scale & runoperated as a service

From reactive firefighting to proactive operations

The four pain points operations teams raise most, and what AIOps changes.

Reactive operations With AIOps

Slow incident resolutionManual troubleshooting across tools; users notice first.Signals correlated, known failures fixed by runbook, engineers start from evidence.

Alert noiseA flood of alerts hides the critical ones.Alerts tuned to baselines and SLOs, grouped into incidents, each with a first action.

Hard root-cause analysisComplex dependencies, correlated by hand.Events, logs, metrics and changes correlated; AI proposes causes for engineers to confirm.

Rising operating costManual effort grows with every new system.Repeat work moves to automation and agents; people handle what needs judgement.

How an AIOps engagement runs

Strategy, implementation and operation; each phase ends at a gate.

01Assess
- Monitoring, alert volume, tickets, runbooks
- Place operations on the maturity scale
Baseline and ranked use casesPilot agreed
02Select & pilot
- A few use cases with good data, low risk
- Anomaly detection and correlation for one service
Pilot measured against the baselineResults reviewed
03Visualise & compare
- Dashboards for operations and pilot results
- Options compared on cost and complexity
Chosen approach and toolsArchitecture decision
04Standardise
- Reference architecture as code
- Runbooks and agents promoted through CI/CD
A platform other teams can use
05Scale & run
- More services and service lines onboarded
- NGT runs the AI system, or hands it over
AIOps operated as a service

What gets automated first

Where work is repetitive, data is good and a mistake is cheap to undo.

Where are your operations today?

Three maturity levels from NGT's service offering. The assessment places you on this scale.

Level	What it looks like	Focus
01 Initiate	First tools, manual or basic; little standardisation or governance	Establishing the foundation
02 Challenger	Repeatable processes, some automation and CI/CD, dashboards	Optimisation and standardisation
03 Mastery	Integrated, automated, measurable; self-healing; organisation-wide	Strategic integration and innovation

Guardrails

The questions this part raises, and their answers.

Only actions engineers approved for a known failure, that can be verified and rolled back: restarting a workload, adjusting resource limits, rolling back a deployment.

New or risky actions, and anything touching data or security, go to a person with the evidence.

SourcesNGT AI-First DevOps Transformation service offering (Oct 2026)NGT Services Offering v2.0 (Mar 2025)NGT Cloud Operation service offering v0.2 (Jan 2025)NGT Cloud, DevOps & SRE capability deck (Sep 2026)FHN AI Transformation Service (Aug 2025)FHN AI Service Introduction v0.8.5 (Nov 2025) and v0.9.3 (Mar 2026)NGT engineer profile sample, 38 CVs (2024–2026)