How to Evaluate an Intelligent Agent Assist Platform

Last Updated September 22, 2026

An intelligent agent assist platform uses AI to help contact center agents understand customer needs, find accurate information and complete service tasks more efficiently. The platform may support real-time conversation guidance, post-contact summaries, workflow assistance and performance analytics within the same agent experience.

Core platform capabilities

• Live intent and topic recognition.
• Knowledge recommendations.
• Suggested responses.
• Next-best actions.
• Customer-context summaries.
• Workflow guidance.
• Automated notes and dispositions.
• Quality and coaching signals.
• Analytics and reporting.

Real-time and post-interaction AI

Agent desktop integration

Agent assist should be embedded in the workflow where agents already manage interactions. If recommendations require switching windows or copying information between systems, the tool can create more work than it removes.

The platform should use customer and interaction context already available in the contact center and CRM.

Knowledge quality determines trust

Agents quickly lose confidence in AI recommendations that are outdated or irrelevant. A strong platform should retrieve from approved content, show enough context to validate the recommendation and provide feedback mechanisms when an answer is wrong.

Knowledge governance and model quality are therefore part of agent-assist operations.

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Questions to ask vendors

• Which channels can be analyzed in real time?
• How is enterprise knowledge connected?
• How does the platform use CRM and customer context?
• Can recommendations trigger workflows?
• How are models and prompts evaluated?
• Can agents provide feedback?
• How are permissions and sensitive data handled?
• How is ROI measured?

Measure agent-assist impact

Track resolution, repeat contact, handle time by comparable intent, transfer rate, after-call work, quality and agent adoption. Measure whether the system saves time without reducing service quality.

Agent feedback is also useful for identifying where suggestions are distracting, late or inaccurate.

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