Industry Uses for Generative AI
Start with a concrete artifact or decision that a team needs, then identify which steps AI can assist. The examples below are illustrative designs, not verified customer case studies or measured business outcomes.
#Document processing
For invoices or purchase orders, combine text extraction with structured field validation. A useful result includes supplier, date, amount, supporting page or region and an unresolved state for unreadable fields. Route low-confidence or inconsistent records to review.
Do not equate a generated summary with financial approval. Compare extracted amounts with source documents and existing business records before any consequential action.
#Marketing
An assistant can draft descriptions from approved product facts or create concept imagery. Preserve factual specifications, brand requirements and usage rights. Show the complete draft so an editor can assess it before publication.
Do not invent traffic improvements, conversion lifts or customer numbers. Measure changes with an appropriate baseline and clearly separate generated examples from real campaigns.
#Customer support
Retrieve current authorized policies, answer with sources and escalate unresolved cases. A useful support artifact explains what the customer can do next and which policy supports it. Emotion classification alone should not determine priority or access to a human.
#Choose a pilot
| Candidate | Useful acceptance result |
|---|---|
| Invoice extraction | Correct fields with source references and review exceptions |
| Product copy | Complete draft consistent with the approved catalog |
| Support assistance | Supported answer or a clear escalation, without unauthorized writes |
Use synthetic or authorized data, compare with the existing workflow and measure error handling as well as time saved. Avoid claims of automatic compliance or guaranteed outcomes based on a prototype.
