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Running AI workflows day to day
AI operations consultant
An AI operations consultant helps an organisation run AI workflows reliably once they are in daily use.
predeploy provides that consultant to set up monitoring, review routines, incident handling and ownership, so workflows keep working after the project team has gone.
Get monitoring, review routines and incident handling in place for AI workflows already in use.
NCSC guidance covers design, development, deployment and operation. NCSC: secure AI system development ↗
NIST describes its AI risk framework as voluntary guidance for design, use and evaluation. NIST: AI Risk Management Framework ↗
New to the topic? Read the background on artificial intelligence.
Running AI workflows day to day
what does an AI operations consultant do?
Sets up the routines that keep AI workflows working.
The consultant reviews how each workflow is monitored, reviewed and supported today.
They set up routines for checking output quality, handling incidents and updating configuration.
The firm-level service is described on AI operations consulting.
Review current operation.
Set up routines.
Hand over ownership.
Running AI workflows day to day
what should AI operations monitor?
An AI operations consultant monitors output quality, usage, cost and incidents.
Output quality is checked by rerunning an evaluation set and sampling live outputs; see LLM evaluation.
Usage shows whether people actually rely on the workflow.
Cost and incidents show whether it remains worth running.
Operations work is often forgotten once a project team moves on, which is why workflows that launched well can quietly degrade over the following months.
Running AI workflows day to day
how should incidents be handled?
An AI operations consultant sets up a clear route to report, pause and fix.
Users need a simple way to report a bad output.
Owners need authority to pause a workflow while a problem is fixed.
The NCSC guidelines include secure operation and maintenance.
| Check | What to establish |
|---|---|
| 1 | Easy reporting. |
| 2 | Authority to pause. |
| 3 | Recorded fixes. |
Running AI workflows day to day
who owns AI operations?
An AI operations consultant makes sure each workflow has a named business owner with technical support.
Each workflow needs a business owner who decides on changes and a technical contact who carries them out.
Without named owners, workflows degrade unnoticed.
AI operating model consulting addresses ownership across many workflows.
Running AI workflows day to day
when do we need an AI operations consultant?
When workflows are live but nobody is sure they still work well.
Signs include no recent evaluation, unclear owners and complaints handled informally.
The NIST AI Risk Management Framework treats ongoing measurement and management as part of the lifecycle.
To review your live workflows, contact predeploy.
No recent evaluation.
Unclear owners.
Informal complaints.
Running AI workflows day to day
what routines should an AI operations consultant set up?
Regular evaluation, sampled review, change control and reporting.
Regular evaluation reruns a test set to check quality has not drifted.
Sampled review has a person check a share of live outputs.
Change control records who changed prompts, configuration or data sources and why.
Reporting summarises quality, usage, cost and incidents for the business owner.
Regular evaluation.
Sampled review.
Change control and reporting.
Make the decision concrete
What does the current task cost in time?
Choose a task connected to ai operations consultant and enter its current workload. This gives you a baseline to discuss before buying training or commissioning a build.
A baseline is useful even if you decide to keep the process manual. Measure the work that matters, then compare quality and review effort as well as time.
Assess the workflow before changing it, or plan business AI training if the gap is how people use existing tools.
Your current workload
Estimate how much time the existing task takes before discussing ai operations consultant.
16 hours per week
People × minutes × weekly tasks ÷ 60. A workload baseline from your inputs, not a prediction of AI time savings. Include review and support time when comparing a proposed workflow.
A useful AI investment leaves your team able to do the work and judge the result.
Continue with the right question
Where should you go next?
Use the overview for context, then follow the pages that match your delivery decision.
See our ai consultancy service or read the ai implementation consulting overview.
FAQ
Questions, answered
Evidence and further reading
Which sources support the guidance?
Source links support the specific background described here. The practical checklists and illustrative examples are predeploy’s guidance.
NCSC guidance covers design, development, deployment and operation. NCSC: secure AI system development ↗
NIST describes its AI risk framework as voluntary guidance for design, use and evaluation. NIST: AI Risk Management Framework ↗
Background reading on the broader field of artificial intelligence. Wikipedia: artificial intelligence ↗
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