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AI implementation advisor
AI implementation consultant
An AI implementation consultant takes a workflow your business has already chosen and carries it into daily use.
predeploy embeds the consultant with the people who do the work: they interview the process owner, shape the build, set up evaluation, support the release and hand the running workflow to a named owner, so the engagement ends with something in use rather than a recommendation.
Get one AI-assisted workflow in use, with evaluation evidence, documentation and a named internal owner.
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.
AI implementation advisor
what does an AI implementation consultant do day to day?
They work through the task with its owner, then make the build, checks and release fit that task.
Early days are spent with the people doing the work: how inputs arrive, what a good output looks like, where judgement is required and where errors are costly.
That understanding shapes what is built and how it is checked.
The consultant then coordinates engineering, writes or reviews the evaluation set, agrees acceptance criteria and supports early users.
LLM evaluation describes the checks in more detail.
For the firm-level service and its stages, see AI implementation consulting; for the bundled delivery work itself, AI implementation services.
Interview the task owner.
Shape build and checks to the task.
Support early users directly.
AI implementation advisor
what should be decided before the consultant starts?
Which workflow, who owns it and who can review early outputs.
An implementation consultant is most effective once the workflow is selected.
If that choice is still open, an AI strategy consultant or AI assessment consultant should settle it first.
Confirm that the people who will review outputs have time allocated; implementation stalls more often for lack of reviewer time than for lack of technology.
The NCSC secure AI development guidelines are a useful checklist for your security owner to review alongside the consultant before build begins.
AI implementation advisor
how is implementation different from integration?
Implementation delivers a working task; integration connects systems so the task can run.
Integration covers data access, permissions and handoffs between systems; it is usually part of implementation but not the whole of it.
Implementation also covers evaluation, release, training and ownership.
If your challenge is mostly connecting existing systems, AI integration services is the narrower scope; if it is mostly releasing an existing build, an AI deployment consultant is the narrower role.
Being clear about which you need avoids paying for a broad engagement when a narrow one would do.
| Check | What to establish |
|---|---|
| 1 | Integration: systems and permissions. |
| 2 | Deployment: releasing an existing build. |
| 3 | Implementation: the whole working task. |
AI implementation advisor
how do we know the implementation worked?
Compare observed use and output quality against the baseline recorded at the start.
Record how the task is handled before the work begins: volume, time, quality checks and common errors.
After release, observe the same measures rather than relying on a forecast.
A workflow baseline is evidence; a projected saving is an assumption until observed.
The NIST AI Risk Management Framework describes measurement and management functions that apply after release as much as before it.
If the measures show the workflow is not helping, the consultant should say so and recommend whether to adjust or stop.
AI implementation advisor
what does the handover include?
A runbook, an evaluation set, an access list and an owner who has accepted them.
The handover should let your team operate, review and improve the workflow without the consultant.
That means documented prompts or configuration, the evaluation set and how to rerun it, the people with access and the escalation route when output quality drops.
Users need preparation on the deployed workflow itself; AI training for employees can be scoped around exactly that task.
To discuss a selected workflow, contact predeploy with a short description of the task and its owner.
Document configuration and checks.
Name the accepting owner.
Train users on the real workflow.
Make the decision concrete
What does the current task cost in time?
Choose a task connected to ai implementation 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 implementation 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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