From Hype to Reality: 4 AI Use Cases to Implement Today
Artificial Intelligence has crossed an important threshold.
Organisations are no longer asking whether to adopt AI — they’re asking where it delivers value today without increasing operational, regulatory, or data risk.
Salesforce’s executive research shows that Agentic AI has entered the mainstream, with leaders prioritising productivity, sales, marketing, and service use cases over experimental applications.
If you’re trying to move from pilots to production, the fastest path is to focus on use cases that are:
- Operationally measurable
- Supported by your current systems
- Grounded in trusted, unified data
If your customer and operational data is still fragmented, start here: How to unify customer data for smarter decisions
1. Productivity & Workflow Automation
Productivity is the top priority use case for Agentic AI, cited by 59% of executives.
This is the most practical place to start because it reduces friction inside the business before you scale AI to customer-facing workflows.
What organisations are implementing now
Case / task triage and routing
Follow-ups and next-step recommendations
Cross-system workflow orchestration
2. Sales Process Enablement
Sales enablement is the second-highest AI priority, at 50%.
Sales teams don’t need more dashboards — they need clarity on:
- Who is most likely to convert
- What to do next
- How to reduce cycle time without losing quality
What AI is doing in sales today
Lead / opportunity prioritisation using first-party signals
Next-best action recommendations aligned to rules and approvals
Forecast assistance using unified pipeline + customer context
3. Marketing Campaign Optimisation
Nearly half of executives (49%) prioritise AI for marketing optimisation.
The bigger value is:
- Better audience selection
- More relevant journeys
- Continuous optimisation while campaigns are live
What to implement now
Data-backed segments (propensity + recency + value)
Consent-aware personalisation
Journey optimisation based on outcomes (not opens/clicks alone)
4. Proactive, Personalised Customer Support
Customer support is shifting from reactive to anticipatory, with 48% of executives prioritising proactive, personalised service.
Practical support use cases
Deflecting repetitive enquiries with grounded answers (knowledge + policy)
Agent assist: summarisation, suggested replies, next steps
Early-warning triggers (service risk signals before a ticket escalates)
Salesforce’s report also reinforces the human/AI partnership: AI improves productivity and decision-making, but humans remain essential for judgement and exceptions.
Data before AI
Across all four use cases, one pattern is clear: AI success depends on trusted, connected data.
In the report, 79% of leaders say turning unstructured data into business value is a high priority — but only 64% say that data currently informs business decisions, signalling a gap between aspiration and execution.
If you’re evaluating platforms and implementation pathways, here’s a practical lens for APAC organisations:Why Choosing the Right Salesforce Partner Unlocks Long-Term ROI
If you want to implement one of these use cases in a governed, production-ready way, Aether Global can help with:
- Use case selection + value sizing
- Data foundation (unification, consent, governance)
- Salesforce-aligned architecture and delivery
