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.

Explore opportunities

See where AI is being applied effectively

Pressure-test ideas

Understand what makes a use case viable or risky

Build alignment

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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