PART III: THE AGENTIC AI QUALIFICATION FRAMEWORK

The Agentic AI Use Case Qualification Framework

Moving from standard Generative AI to Agentic AI changes the selection process entirely. You are no longer asking “What information can this model look up?” — you are asking “What workflow can this system manage autonomously?”

The Four-Parameter Qualification Model

An ideal Agentic AI use case should require high scores in Orchestration and Reasoning, while maintaining a manageable Risk Profile. Run every candidate use case through all four parameters before committing to development.

   [ Use Case Idea ]
          │
          ▼
┌────────────────────────────────────────────────────────┐
│ 1. Orchestration Depth — Crosses multiple systems/APIs? │
├────────────────────────────────────────────────────────┤
│ 2. Non-Linear Reasoning — Handles edge cases & retries? │
├────────────────────────────────────────────────────────┤
│ 3. Data Entropy — Deals with messy, unstructured inputs?│
├────────────────────────────────────────────────────────┤
│ 4. Governance & Risk — Clear Human-in-the-Loop gates?   │
└────────────────────────────────────────────────────────┘
          │
          ▼
   [ GO / NO-GO Decision ]

Parameter Deep Dive

Parameter 1: Orchestration Depth — System & Tool Integration

Agentic AI earns its keep when it must orchestrate actions across multiple legacy environments in a single coherent workflow. The integration complexity is where agents provide asymmetric value relative to human operators, who must context-switch between systems manually.

The Rule: The more systems a workflow requires, and the more state-dependent the sequence of calls, the stronger the case for an agent

The Test: Does the task require reading from a database, invoking an external API, updating a core system, and sending a confirmation? If it only requires reading and writing text within one interface, standard GenAI or a basic RAG setup is sufficient

Parameter 2: Non-Linear Reasoning & Exception Handling

Healthcare, airlines, and insurance are defined by exception cases. The 80% standard workflow is manageable by RPA. The 20% of exceptions — missing data, failed API calls, conflicting information, ambiguous edge cases — is where enormous human time is consumed and where Agentic AI provides transformative value.

The Rule: If a workflow follows a rigid “If X, then Y” script with no exceptions, use traditional RPA. Agents are over-engineered for deterministic processes

The Test: Does the process require semantic judgment when a tool fails or when information is missing? Agentic AI excels when it has to figure out an alternative path — like realising a passenger’s connection is impossible and calculating three alternative routes based on real-time crew availability

Parameter 3: Data Entropy — Handling Chaos

The most expensive and time-consuming part of insurance underwriting, clinical prior auth, and airline irregular operations is not the decision itself — it is assembling the information needed to make the decision from disparate, unstructured sources.

The Rule: High variability in input formats defeats traditional automation but is where agents thrive

The Test: Is the core data trapped in unstructured clinical charts, complex commercial insurance schedules, or disparate flight status updates? Agents can interpret intent, normalise the data, and make context-aware decisions based on it

Parameter 4: Risk Profile & Governance Complexity

The single most common cause of failed Agentic AI deployments in regulated industries is insufficient governance design. Risk profile definition is not a post-build activity — it is a prerequisite for architectural decisions, tool access scoping, and HITL gate placement.

The Rule: High autonomy requires strict boundaries. You must design explicit Human-in-the-Loop handoff parameters before a single line of agent code is written

The Test: What is the blast radius if the agent makes an error? High-risk actions must be scoped as “Agent proposes, Human disposes.” Low-risk tasks can run on autopilot

Cross-Domain Application Matrix