AI Use Cases
Practical AI Use Cases That Create Business Value
AI use cases are everywhere — but without strategy, most remain ideas instead of impact. This is a growing library of practical insights drawn from our work and research.
Use Cases We've Identified
Real examples from our client engagements showing how AI delivers measurable business value.
Manufacturing Client
Assessed:
Oracle EBS + legacy MES systems
Recommendation:
Predictive maintenance using AWS SageMaker + Oracle data
ROI:
15% reduction in unplanned downtime
Healthcare Client
Assessed:
Oracle HCM Cloud
Recommendation:
HR chatbot using OpenAI + Oracle Digital Assistant
ROI:
40% reduction in tier-1 HR tickets
Distribution Client
Assessed:
Oracle ERP + custom APEX apps
Recommendation:
Invoice automation (Tesseract OCR) + Select AI queries (Claude)
ROI:
$150K annual savings, 85% time reduction
These examples represent a fraction of the AI opportunities we've identified across industries. Each engagement is tailored to the client's specific Oracle environment and business objectives.
How to Use This Library
The content here is designed to support different stages of AI decision-making. Our intent is simple: help leaders understand where AI creates value and why it works.
See where AI is being applied effectively
Understand what makes a use case viable or risky
Use shared examples to align teams
Pro Tip
"While individual use cases can stand alone, real value comes from connecting them to a broader AI strategy."
Inside an iteria Use Case
Real-world examples of how we bridge strategy and execution.
AI Readiness & Roadmap: Mid-Market Distributor
Moving from stalled ideas to a funded, actionable roadmap.
Client Context
Mid-market distributor running Oracle ERP with multiple line-of-business systems. Leadership had 5+ AI ideas (demand forecasting, invoice automation, churn prediction) but no clear view of feasibility. Data was fragmented across ERP, CRM, and spreadsheets with unknown quality. Security concerns regarding financial data were blocking pilots, stalling attempts to move from boardroom ideas to execution.
The Opportunity
To break the deadlock of "Do we have the data?" and "Is this safe?" The goal was to objectively prioritize high-value use cases based on feasibility and build a roadmap that addressed the specific data and security blockers preventing them.
The Approach
Iteria delivered a 6–10 weekAI Readiness & Data Architecture Assessment:
- Prioritized 4 high-value use cases via workshops.
- Cataloged 20+ data sources with quality scorecards.
- Mapped manual pipeline bottlenecks blocking real-time AI.
- Defined practical security controls to unblock pilots.
Why It Works
Instead of a generic "data cleanup" project, the roadmap linked specific remediation tasks (data quality fixes, pipeline redesigns) directly to the top three use cases. This gave data engineering and analytics a clear, prioritized backlog tied to business value.
Value & Impact
Within 60 days, the client had:
- A funded "anchor" pilot (demand forecasting).
- Two fast-follower use cases (invoice automation, churn).
- Executive sign-off on a 12–24 month roadmap & budget.
Critical Success Factor: Practical Governance
Security teams were initially blocking progress. By defining aminimal, practical control set(role-based access, masking rules, audit) aligned with existing policies, we were able to satisfy compliance requirements without waiting for a multi-year governance overhaul.
Strategic Framing
Use cases alone do not create value. Without prioritization, ownership, and governance, even strong ideas can stall or fail to scale. That’s why iteria always frames use cases within a broader AI strategy.
Start the Conversation
If a use case here reflects a challenge or opportunity you’re exploring, we should talk.
AI works best when ideas are paired with clarity, discipline, and execution.
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