Generative AI use cases by department: a practical map
By TechlyUpUpdated 2 min readLeaders planning AI pilots
Quick answer
Most departments have lower-risk generative AI uses (drafting, summarising, internal knowledge) and higher-risk ones (decisions about people, customer-facing automation, regulated content). Map both for each department, start pilots with the lower-risk, high-frequency tasks, and build controls before moving to higher-risk uses.
Lower-risk starting points
Internal, reviewable, and frequent.
- HR: job description drafts, policy summaries, onboarding plans.
- Marketing: briefs, first drafts, repurposing.
- Sales: account research, call prep, CRM summaries.
- Finance: variance commentary drafts, formula help.
- Operations: document extraction with review, process documentation.
- IT: knowledge-base articles, script drafts with review.
Higher-risk uses
Automated screening or evaluation of people, customer-facing bots without escalation, and outputs in regulated areas need stronger controls and review.
Prioritise with a simple score
Score each candidate use.
Use case | Frequency (1–5) | Time per task | Risk (1–5) | Ease of measuring | Owner
Sequence the pilots
Begin with two or three high-frequency, lower-risk uses, then expand as controls and skills mature.
Prioritisation mistakes
These lead to poor pilot choices.
- Choosing the most exciting use rather than the most valuable.
- Starting with high-risk uses.
- Ignoring frequency — rare tasks give little return.
- No owner for the use case.
Worked example: scoring five uses
A company scores five candidate uses. Automated candidate ranking scores high on time saved but very high on risk. Meeting summaries and knowledge-base drafting score well on frequency with low risk.
They start with meeting summaries and knowledge-base drafting, building skills and controls. Candidate screening is deferred until governance and fairness testing are in place.
Try it yourself
Fill in the scoring table for five use cases in your organisation and pick your first two pilots.
Frequently asked questions
Which department benefits most from AI?
It varies by organisation. Departments with high volumes of text and documents often see early value.
Should every department start at once?
Starting with a few pilots lets you learn and build controls before scaling.
Do we need custom AI solutions?
Many early uses work with approved off-the-shelf tools; custom solutions come later for specific needs.
Want a suggested next step for your situation?
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Sources and further reading
Examples are authored practice material, not measured learner outcomes. Tool behavior can change. Found an error? Contact TechlyUp with the page URL and correction.