Question map
What the market asks about AI Operations
The questions people actually ask when they try to operate AI, with a short answer and where to go deeper. Updated with what our weekly radar detects.
What it is
What is AI Operations?
It’s the discipline of taking AI to production, operating it and measuring it: not researching models, but getting agents and automations to work, have an owner and deliver a return.
GlossaryHow is it different from MLOps or AIOps?
MLOps operates ML models; classic AIOps uses AI to run IT systems. AI Operations operates AI applied to the business: agents and automations in real processes, with governance and ROI.
See the glossaryIs it the same as automation?
No: automation is the means. AI Operations is the function that decides what to automate, ships it to production with controls and owns the outcome.
The capabilitiesWhy it matters
Why does almost nobody see a return on AI?
Because using AI isn’t operating it: most stall at pilots with no owner, no integration and no measurement. 95% of those investing see no return (MIT NANDA, 2025).
The state of AI OperationsWhat’s the difference between using AI and operating it?
Using it is trying tools; operating it is putting them in production with an owner, SLA, governance and cost/savings measurement. That’s where the return is.
The capabilitiesWhen does it make sense to set up AI Operations?
When you have a case with clear value, accessible data and someone to operate it. Before that, build the foundations instead of hiring or buying.
Readiness checkHow to start
Where do I start with AI Operations?
With a high-volume, low-risk case, with an owner and estimated ROI. No critical decisions on day one: visibility and control first.
The capabilitiesHow do I prioritise what to automate first?
By impact × feasibility: which process gives the most value and is most doable with the data you already have. Score it cold before building.
Workflow prioritiserShould I build or buy?
Buy the standard, build the differentiator. It depends on the fit with your process, the total cost and the control you need.
Build vs buy toolRoles and team
Who operates AI in a company?
It depends on size: from a single AI Operations Manager doing it all, to a function with managers, engineers and governance.
The rolesWhat roles do I need?
The minimum: someone to prioritise and operate, someone to build, and governance. The rest (reliability, evaluation, architecture) scales with the portfolio.
See the rolesWhat does AI Operations talent cost?
It varies by role, seniority and country. The calculator gives market ranges for each role and level.
Salary calculatorRisk, governance and cost
How do I govern agents in production?
With an inventory and owner per agent, least-privilege permissions, monitoring, continuous evaluation and traceability of every decision.
Agent auditWhat does AI regulation (EU AI Act) require?
It classifies systems by risk and mandates controls, documentation and traceability. Apply it operationally — to enable with control, not to block.
Security and governanceHow do I control the cost of operating AI?
By measuring cost per execution, infra, oversight and maintenance. The estimator gives you the monthly run-rate with a breakdown.
Cost estimatorYour question isn’t here?
Write to us and we’ll answer it — and it’ll probably make the map.
Talk to us