1. Sales prioritisation and lead scoring
AI can rank opportunities using intent, fit and behaviour signals. The aim is to focus commercial judgement, not replace it.
- Outcome: faster, better follow-up
- Data: CRM, activity and historical conversion
- Control: explainable signals and bias review
2. Customer service assistants
An assistant connected to approved documentation can suggest answers, summarise conversations and escalate complex cases. Quality depends on trusted sources, permissions and a clear human hand-off.
3. Document processing
Invoices, contracts, requests and reports contain information that is often copied manually. Assisted extraction reduces effort while allowing sensitive fields to be validated before integration.
4. Demand and operations forecasting
Historical data, seasonality and business variables can anticipate demand, workload or inventory. Every forecast should communicate uncertainty and be compared with the current method.
5. Marketing personalisation
AI can support segmentation, adapt messages and create brand-governed variants. The opportunity is to increase relevance without losing editorial control.
6. Internal knowledge search
Search across policies, projects and documentation reduces time spent locating information. Recency, permissions and source traceability must be solved before launch.
7. Software development and quality
Assistants can accelerate documentation, tests, review and repetitive development tasks when integrated with quality, security and technical ownership.
How to choose the first one
Score each case by impact, frequency, data availability, integration difficulty and risk. Begin with an opportunity that supports a meaningful decision within weeks.