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Assessing AI opportunities and systems
AI assessment services
AI assessment services examine an organisation, a proposed use case or an existing AI system and give a clear verdict on what to do next.
predeploy offers three kinds of assessment and helps you choose the one that answers your current question.
Choose the right assessment for your question and get a verdict with ranked actions.
NIST describes its AI risk framework as voluntary guidance for design, use and evaluation. NIST: AI Risk Management Framework ↗
ICO guidance covers AI accountability, transparency and fairness; the guidance is currently under review. ICO: AI and data protection guidance ↗
New to the topic? Read the background on artificial intelligence.
Assessing AI opportunities and systems
which AI assessment services are available?
Readiness, use-case and system assessments.
A readiness assessment checks whether data, people and governance can support AI work; see AI readiness assessment.
A use-case assessment compares candidate tasks and recommends which to pursue; an AI assessment consultant leads it.
A system assessment evaluates an AI tool or workflow already built; see AI evaluation consultant.
Readiness.
Use case.
System.
Assessing AI opportunities and systems
which assessment should we choose?
Choose between AI assessment services by matching the assessment to your current uncertainty.
If you are unsure whether the organisation is ready, choose readiness.
If you have several ideas and need to pick, choose a use-case assessment.
If something is built and you are unsure whether it works well enough, choose a system assessment.
The assessment report records the evidence behind each finding, so your own team can check and challenge the conclusions.
Assessing AI opportunities and systems
what evidence does an assessment use?
AI assessment services use interviews, documents, data and, for systems, test results.
All assessments interview the owners involved and review relevant policies.
Readiness and use-case assessments sample real data to confirm what interviews suggest.
System assessments run representative test cases; LLM evaluation describes how.
| Check | What to establish |
|---|---|
| 1 | Interviews. |
| 2 | Data samples. |
| 3 | Test cases for systems. |
Assessing AI opportunities and systems
which standards inform AI assessment?
AI assessment services draw on recognised frameworks and UK guidance.
The NIST AI Risk Management Framework offers a voluntary structure for mapping and measuring AI risk.
The ICO guidance on AI and data protection informs data protection findings.
Assessments cite the guidance used so findings can be checked.
Assessing AI opportunities and systems
what happens after an AI assessment?
After AI assessment services report, you act on ranked findings or stop.
Findings are ranked by how much they block progress.
The next step may be a fix, a proof of concept, implementation or a decision not to proceed.
To arrange an assessment, contact predeploy.
Ranked findings.
Clear next step.
Stopping is valid.
Assessing AI opportunities and systems
how long does an AI assessment take?
The length of AI assessment services depends on the type of assessment and the evidence available.
A readiness or use-case assessment depends on how many owners need interviewing and how quickly data can be sampled.
A system assessment depends on building a representative test set and running it.
predeploy agrees the scope and end date before starting, so the assessment does not drift.
Delays usually come from access to data or people, so arrange those early.
Scope agreed first.
End date set.
Access arranged early.
Make the decision concrete
What does the current task cost in time?
Choose a task connected to ai assessment services 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 assessment services.
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.
NIST describes its AI risk framework as voluntary guidance for design, use and evaluation. NIST: AI Risk Management Framework ↗
ICO guidance covers AI accountability, transparency and fairness; the guidance is currently under review. ICO: AI and data protection guidance ↗
Background reading on the broader field of artificial intelligence. Wikipedia: artificial intelligence ↗
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