Agent AI

Intelligent AI assistant for contact center agents to boost productivity.

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Overview

Agent AI provides real-time assistance to human agents:

• Suggested responses based on conversation context
• Automated call and chat summaries
• Knowledge base search integration
• Next-best-action recommendations

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How It Works

┌─────────────────────────────────────────────────────────────────┐
│                    Live Conversation                             │
│                                                                  │
│  Customer: "I received the wrong item in my order"              │
└─────────────────────────────────┬───────────────────────────────┘
                                  │
                                  ▼
┌─────────────────────────────────────────────────────────────────┐
│                       Agent AI Engine                            │
│                                                                  │
│  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐              │
│  │  Context    │  │  Knowledge  │  │  Response   │              │
│  │  Analysis   │  │  Search     │  │  Generation │              │
│  └─────────────┘  └─────────────┘  └─────────────┘              │
└─────────────────────────────────┬───────────────────────────────┘
                                  │
                                  ▼
┌─────────────────────────────────────────────────────────────────┐
│                    Agent Desktop Widget                          │
│                                                                  │
│  Suggested Response:                                             │
│  "I apologize for the inconvenience. I can help you with a      │
│   replacement or refund. Let me pull up your order details..."  │
│                                                                  │
│  Relevant Knowledge:                                             │
│  • Wrong Item Policy (confidence: 95%)                          │
│  • Return Process Guide (confidence: 87%)                       │
│                                                                  │
│  Recommended Actions:                                            │
│  [Create Return] [Issue Refund] [Escalate to Supervisor]        │
└─────────────────────────────────────────────────────────────────┘

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Features

Real-Time Suggestions

Contextual response suggestions during conversations:

Feature	Description
Auto-suggest	Suggestions appear as customer speaks
One-click use	Insert suggestion with single click
Edit before send	Modify suggestions as needed
Learn from edits	System improves from agent modifications

Configuration:

Suggestions:
  trigger: continuous
  display_count: 3
  confidence_threshold: 0.7
  sources:
    - knowledge_base
    - canned_responses
    - conversation_history
  tone: professional

Automated Summaries

Generate conversation summaries automatically:

Summary Type	When Generated
Real-time	Updated as conversation progresses
After-call	Complete summary at interaction end
Disposition	Structured outcome summary

Summary configuration:

Auto-Summary:
  format: structured
  sections:
    - customer_issue
    - resolution
    - follow_up_required
  length: concise
  auto_save_to_crm: true

Knowledge Assistance

Integrated knowledge search:

• Search triggered automatically by conversation context
• Manual search with natural language queries
• Results ranked by relevance
• Source citations included

Next-Best-Action

Recommended actions based on context:

NBA Rules:
  - condition: sentiment == "frustrated" AND issue_unresolved
    action: offer_supervisor_escalation
    priority: high

  - condition: customer_tier == "premium" AND wait_time > 5min
    action: offer_compensation
    priority: medium

  - condition: issue_type == "billing"
    action: show_billing_tools
    priority: normal

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Configuration

Enable Agent AI

1. Navigate to Agent AI → Configuration
2. Enable Agent AI for desired queues
3. Configure feature settings
4. Test with pilot agents

Feature Settings

Setting	Options
Suggestion mode	Continuous, On-demand, Disabled
Auto-summary	Enabled, Disabled
Knowledge search	Auto, Manual, Both
NBA	Enabled, Disabled

Integration

Connect Agent AI to:

• Search AI — For knowledge retrieval
• CRM — For customer context
• Case management — For action execution
• Quality AI — For coaching feedback

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Agent Experience

Desktop Widget

Agent AI appears as a widget in the agent console:

┌─────────────────────────────────────┐
│  Agent AI                    [─] [×]│
├─────────────────────────────────────┤
│                                     │
│  💡 Suggested Response              │
│  ┌─────────────────────────────────┐│
│  │ I understand your concern about ││
│  │ the billing charge. Let me...   ││
│  └─────────────────────────────────┘│
│  [Use] [Copy] [👍] [👎]              │
│                                     │
│  📚 Knowledge                       │
│  • Billing FAQ (95%)                │
│  • Refund Policy (88%)              │
│  [Search manually...]               │
│                                     │
│  ⚡ Quick Actions                   │
│  [Refund] [Credit] [Escalate]       │
│                                     │
└─────────────────────────────────────┘

Feedback Loop

Agents can rate suggestions:

• Thumbs up — Good suggestion
• Thumbs down — Unhelpful suggestion
• Edits — System learns from modifications

Feedback improves suggestion quality over time.

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Analytics

Agent AI Metrics

Metric	Description
Suggestion acceptance	% of suggestions used
Time saved	Handle time reduction
Knowledge utilization	Searches and clicks
NBA conversion	Recommended actions taken

Quality Impact

Track quality improvements:

• First contact resolution rate
• Customer satisfaction scores
• Quality evaluation scores
• Handle time trends

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Best Practices

Deployment

1. Start with a pilot group of agents
2. Gather feedback and iterate
3. Roll out gradually by queue/team
4. Monitor adoption and adjust

Knowledge Quality

• Keep knowledge base current
• Remove outdated content
• Add content for common queries
• Monitor search failures

Agent Training

• Introduce Agent AI in agent training
• Explain feedback mechanism importance
• Show how to use suggestions effectively
• Address concerns about AI assistance

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Related

• Contact Center AI — Agent desktop and routing
• Routing — How agents receive conversations
• Skills Management — Agent skill configuration
• Search AI — Knowledge retrieval for suggestions
• Quality AI — Evaluate agent performance