Capabilities

The capabilities of AI Operations

Running AI in production isn’t one thing, it’s thirteen. These are the capabilities that make up the discipline: from redesigning the process to building the agent, operating it with controls and improving it with data. The reference for what you need to cover so AI reaches production, works and gets measured.

Design

Workflow redesign

Rebuild the process before automating it, so you don’t automate the waste.

Build

Agent building

Turn a use case into an agent that runs in production with an owner and an SLA.

Systems integration

Connect AI to the CRM, the ERP and the tools where the real work lives.

Evaluation (evals)

Measure whether AI is right, with real cases and a threshold, before and after production.

Operate

Observability

See what AI does in production: every run, its cost, and why it failed.

AI governance

The rules for who can deploy what, with which controls, and who is accountable.

AI security

Protect data, access and outputs against leaks, abuse and prompt attacks.

Change management

Move the organisation from "AI is being forced on me" to using it every day.

Adoption

Turn a bought tool into a habit people actually use well.

Training

Teach teams to use and supervise AI for their specific job.

Improve

ROI & measurement

Prove with numbers that AI saves or earns more than it costs.

Maintenance

Keep what works today working when the world shifts underneath it.

Optimisation

Lower the cost and raise the reliability of what’s already in production.