How to Validate Agentic AI in the Contact Center

Virtual agents no longer just answer questions. They make decisions, call tools, and execute workflows on their own. Most QA programs were built to check what a system says, so the failures that matter most, like incorrect actions and inconsistent decision paths, slip through to production.

Kenway Consulting spent four months validating Cyara Botium's agentic testing capabilities across three virtual assistants, from a foundational onboarding chatbot to an agentic assistant orchestrating Salesforce workflows. This white paper shares the framework, the findings, and a practical roadmap for putting it to work.

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Four Risks Traditional QA Misses

1. Hallucinated Actions
Agents execute incorrect decisions that spread across workflows before anyone notices.

2. Decision Pathway Drift
The same objective produces different execution paths from run to run.

3. Evaluator Risk
LLM-based evaluation adds its own variability without active governance.

4. Configuration Sensitivity
Small setting errors produce wrong results with no visible error signal.

Why Download This White Paper?

The full technical whitepaper gives QA, CX, and technology leaders a detailed look at how objective-based testing works in practice. You will learn:
How to shift QA from validating responses to validating decisions
How one framework tests every AI type, from IVR to agentic
A four-phase roadmap to continuous, scalable validation

Start With the Executive Overview

Our free executive overview summarizes the key findings, business value, and implementation roadmap in a quick, scannable format. It is a good fit for leaders who want the big picture before diving into the technical detail.
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