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Agent Copilot

Genesys PureCloud Agent Copilot Documentation

Study Notes

Topic Description
Agent Copilot Real-time AI assistance for agents during customer interactions
Core Function Determines customer intent and provides next best actions in real-time
After-Call Work Automates summaries, wrap-up codes, and resolution tracking
AI Skills Modular AI capabilities that can be combined and customized
On-Queue Behavior Operates continuously during interaction, adapting to conversation flow
Key Results 5-min AHT reduction, 1.5-min hold time reduction, 2-min ACW reduction

Navigation

Admin → Contact Center → Agent Assistance → Agent Copilot Configuration OR Admin → AI Studio → Agent Copilot Settings

Agent Copilot Overview

Genesys Agent Copilot enhances communication between the agent and the customer by determining customer intent and providing relevant next best actions to the agent. It offers assistance in after-call work and provides a summary of the conversation, reason for contact, resolution, and suggests wrap-up codes.

Genesys Agent Copilot integrates AI and Large Language Models to deliver intelligent assistance capabilities that transform agent productivity and customer service delivery. The platform automates after-call work through intelligent wrap-up code suggestions, conversation summaries, and resolution tracking, while providing real-time next-best-action recommendations and customer intent determination during live interactions.

Key Capabilities

  • Real-time agent assist during customer interactions on voice and digital channels
  • Intelligent next-best-action recommendations based on conversation context
  • Automatic conversation summaries and wrap-up code suggestions
  • Customer intent determination and understanding
  • Multi-language support (13+ languages including English, Spanish, French, German, Japanese, Korean, Arabic, Hindi, Portuguese, Swedish, Dutch, Italian)
  • Custom AI Guides built through AI Studio integration
  • Knowledge article integration and answer highlighting
  • Queue-specific configuration and management
  • Performance analytics and monitoring dashboards

Performance Metrics

Agent Copilot users have seen results including:

  • 5-minute decrease of average handle time
  • 1.5-minute decrease in average hold time
  • 2-minute decrease in after-call work time

Edition & Module Requirements

Requirement Details
Minimum Edition Premium Edition (Genesys Cloud CX 1-4)
Module Included or Agent Copilot add-on depending on tier
License Type Per-user licensing
AI Tokens Requires tokens: 40-60 per user for Agent Copilot
Knowledge Base Genesys Knowledge Workbench or Knowledge Fabric recommended

Study Notes - Agent Copilot Features

Feature Description Benefit
Intent Recognition AI understands customer goals from conversation Faster issue identification
Next-Best-Action Recommends optimal next step for agent Guides resolution path
Auto-Summarization Generates conversation summary automatically Reduces after-call work
Wrap-Up Code Suggestions AI suggests appropriate completion codes Faster code selection
Knowledge Integration Surfaces relevant knowledge articles automatically Faster access to information
Answer Highlighting Highlights key parts of knowledge articles Easier information scanning
Sentiment Monitoring Detects customer emotion in real-time Enables de-escalation
Multi-Language Support Operates in 13+ languages Global team support
Custom Guides Build AI agents using AI Studio Automation flexibility
Performance Analytics Dashboard showing copilot usage and impact Measurement and optimization

How Agent Copilot Works

During Interaction (Real-Time Assistance)

Agent Answers Contact
    ↓
Copilot Begins Monitoring
├── Real-time transcription
├── Intent analysis
└── Context understanding
    ↓
Customer Explains Issue
"I'm having trouble logging into my account"
    ↓
Copilot Analyzes
├── Intent: Account Access Issue
├── Context: Login problem
├── Emotion: Slightly frustrated
└── Knowledge needed: Account recovery
    ↓
Copilot Provides Assistance
├── Knowledge Articles
│  ├─ "Password Reset Steps" (94% match)
│  ├─ "Two-Factor Auth Help" (81% match)
│  └─ "Account Locked Recovery" (76% match)
│
├── Next-Best-Action
│  └─ "Guide customer through password reset"
│
└── Script Suggestion
   └─ "I can help you regain access to your account..."
    ↓
Agent Reviews & Applies
├── Reads suggested article
├── Guides customer through steps
├── Issue resolved
└── Interaction continues

After Interaction (After-Call Work)

Contact Completes
    ↓
Copilot Generates Summary
├── Conversation Analysis
├── Key Points Extraction
├── Issue Resolution Status
└── Customer Sentiment Analysis
    ↓
Summary Displayed to Agent
"Customer called about password reset.
 Issue resolved through email link sent.
 Customer satisfied."
    ↓
Wrap-Up Code Suggestions
├─ Suggested Codes (in priority order)
│  ├─ Password Reset (89% confidence)
│  ├─ Account Access (71% confidence)
│  └─ Technical Support (34% confidence)
└─ Agent selects from suggestions
    ↓
Agent Reviews & Saves
├── Reviews summary (can edit)
├── Selects wrap-up code
├── Adds notes if needed
└── Saves interaction

AI Skills Architecture

AI Skills are modular, customizable AI capabilities that can be combined and deployed through Agent Copilot. Each skill targets a specific function or use case.

Types of AI Skills

Knowledge Skills

  • Surfaces relevant knowledge articles automatically
  • Answers customer questions from knowledge base
  • Answer highlighting for quick scanning
  • Knowledge caching for speed

Next-Best-Action Skills

  • Recommends optimal next step in interaction
  • Guides agent through proper procedure
  • Suggests escalation or transfer when needed
  • Predicts customer outcomes

Wrap-Up Code Skills

  • Analyzes interaction to suggest wrap-up codes
  • Reduces time agents spend on code selection
  • Improves code accuracy through AI
  • Learning improves accuracy over time

Sentiment & De-Escalation Skills

  • Real-time sentiment detection
  • De-escalation recommendations
  • Tone guidance for responses
  • Emotional intelligence coaching

Compliance & Risk Skills

  • Monitors for compliance violations
  • Alerts on risky language or actions
  • Ensures required disclosures made
  • Flags suspicious patterns

Custom Business Skills

  • Created via AI Studio
  • Built using AI Guides
  • Business-specific logic
  • Adaptive to business processes

On-Queue Behavior

How Agent Copilot Operates During Customer Interaction

Queue: Customer Support
Status: Agent Sarah actively handling call

Real-Time Copilot Behavior:

MOMENT 1 (0:15 into call)
├─ Copilot listening to conversation
├─ Transcribing in real-time
├─ Analyzing customer statements
└─ Building context understanding

MOMENT 2 (0:45 into call)
Customer: "I need to change my billing address"
├─ Intent Detected: Billing Update
├─ Copilot triggers knowledge search
├─ Results: 2 relevant articles found
└─ Displayed to Agent Sarah

MOMENT 3 (1:15 into call)
├─ Customer emotion: Neutral → Positive
├─ Issue complexity: Routine
├─ Next action: Process address change
└─ Copilot suggests: "Enter new address in system"

MOMENT 4 (1:45 into call)
Customer: "Can I also update my phone number?"
├─ New intent added to context
├─ Copilot expands knowledge articles
├─ Related articles surfaced
└─ Agent handles both requests together

MOMENT 5 (3:00 - Call ends)
├─ Both issues resolved
├─ Customer satisfied
├─ Copilot prepares summary
└─ Ready for after-call work

Agent Copilot Interface Components

Agent Desktop View

┌──────────────────────────────────────┐
│ ACTIVE CALL - Sarah Martinez        │
│ Customer: John Smith                │
│ Queue: Billing Support              │
│ Duration: 3:42                      │
└──────────────────────────────────────┘

┌──────────────────────────────────────┐
│ 📚 SUGGESTED KNOWLEDGE              │
├──────────────────────────────────────┤
│ ✓ Update Billing Address (94%)       │
│ ✓ Change Phone Number (87%)          │
│ ○ Payment Methods (61%)              │
│                                      │
│ [Show Full Articles] [Minimize]      │
└──────────────────────────────────────┘

┌──────────────────────────────────────┐
│ ➡️  NEXT-BEST-ACTION                 │
├──────────────────────────────────────┤
│ Recommended: Process address update  │
│ in customer record                   │
│                                      │
│ Steps:                               │
│ 1. Confirm new address               │
│ 2. Verify zip code                   │
│ 3. Update system                     │
│ 4. Send confirmation                 │
└──────────────────────────────────────┘

┌──────────────────────────────────────┐
│ 😊 CUSTOMER SENTIMENT               │
├──────────────────────────────────────┤
│ Current: POSITIVE                    │
│ Emotion: Satisfied                   │
│ Recommendation: Offer additional help│
└──────────────────────────────────────┘

[Notes Box]
[Hold/Transfer/Close Buttons]

Behavior by Interaction Type

Inbound Call

  • Continuous listening and transcription
  • Real-time intent and sentiment analysis
  • Knowledge surfacing as topics emerge
  • Next-best-action recommendations throughout
  • Escalation alerts if conversation flags
  • Summary generation at call end

Chat/Email

  • Message-by-message analysis
  • Delayed but thorough knowledge search
  • Context building across multiple messages
  • Suggested responses for agent review
  • Quick-reply templates with personalization
  • Handoff summaries for escalation

Outbound Call

  • Prepopulates customer context
  • Suggests opening statements
  • Guides conversation flow
  • Handles objections with recommendations
  • Closing suggestions
  • Outcome tracking

Implementation Guide

Step 1: Prerequisites & Planning

  1. Ensure Premium Edition activated
  2. Confirm sufficient AI tokens available (40-60 per user)
  3. Audit knowledge base quality and coverage
  4. Identify queues for initial deployment
  5. Assess agent readiness and training needs
  6. Plan change management approach

Step 2: Knowledge Base Setup

  1. Review/create knowledge articles in Knowledge Workbench
  2. Ensure articles are accurate and current
  3. Add metadata and keywords for searchability
  4. Organize by topic and queue
  5. Set article access permissions
  6. Test knowledge base connectivity

Step 3: Enable Agent Copilot

  1. Navigate to Admin → Contact Center → Agent Assistance
  2. Select "Agent Copilot" → Enable
  3. Choose knowledge source (Knowledge Workbench v2 or Fabric)
  4. Configure recommendation parameters
  5. Set recommendation types to display
  6. Choose display behavior (auto-popup vs. agent-triggered)

Step 4: Configure by Queue

  1. Create queue-specific Copilot settings
  2. Define which AI Skills are active per queue
  3. Configure knowledge sources
  4. Set wrap-up code matching rules
  5. Establish sentiment thresholds
  6. Test queue-specific behavior

Step 5: Agent Training

  1. Conduct overview training on Copilot interface
  2. Demonstrate real-time knowledge suggestions
  3. Practice reviewing and applying recommendations
  4. Explain wrap-up code suggestions
  5. Cover sentiment alerts and de-escalation
  6. Q&A and feedback

Step 6: Phased Rollout

  1. Deploy to pilot queue first
  2. Monitor closely for 1-2 weeks
  3. Gather agent and supervisor feedback
  4. Optimize based on learnings
  5. Expand to additional queues
  6. Scale to full deployment

Step 7: Ongoing Monitoring

  1. Review Agent Copilot dashboard daily
  2. Track key metrics (AHT reduction, token usage)
  3. Monitor agent adoption rates
  4. Gather continuous feedback
  5. Refine knowledge articles based on usage
  6. Optimize AI recommendations

Real-Flow Scenarios

Scenario 1: Technical Support with Knowledge Integration

Agent: "Thanks for calling technical support, how can I help?"

Customer: "My printer isn't connecting to WiFi"

Copilot immediately surfaces:
├─ 3 relevant knowledge articles
├─ Troubleshooting flowchart visual
├─ Video walkthrough link
└─ Quick-resolution steps

Agent: "I can help. Let me walk you through the WiFi 
        connection steps which usually resolve this..."

[Uses Copilot-suggested steps to guide customer]

Result: Issue resolved in 4 minutes
Copilot Summary:
"Customer called about printer WiFi connectivity issue. 
 Guided through troubleshooting steps. Issue resolved 
 after resetting router. Customer satisfied."

Wrap-up Code Suggestions:
├─ Printer Setup (92% confidence) ← Selected
├─ Technical Support (67% confidence)
└─ Network Issues (45% confidence)

Time Saved: 2 minutes (no manual summary or code lookup)

Scenario 2: Billing with Sentiment De-escalation

Customer (frustrated): "Why was I charged twice?!"

Copilot detects:
├─ Emotion: FRUSTRATED
├─ Sentiment score: -2.1/5
├─ Recommended action: Empathize & resolve immediately
└─ De-escalation tip: "Acknowledge frustration sincerely"

Agent (applying suggestion): "I completely understand 
        your frustration. Let me look into that right away 
        and fix this for you."

Copilot provides:
├─ Knowledge: "Duplicate Charge Resolution"
├─ Next action: "Issue refund immediately"
└─ Script: "Here's what happened and how I'm fixing it..."

[Agent processes refund while explaining]

Customer (relieved): "Oh wow, thanks for handling that so fast!"

Copilot updates sentiment: +1.5/5 (positive)

Summary generated:
"Customer called upset about duplicate charge. Explained 
 system error, issued refund immediately. Customer very 
 satisfied with quick resolution and empathetic service."

Result: De-escalation successful, issue resolved, positive outcome

Scenario 3: Sales with Cross-Sell Recommendations

Customer: "I'd like to upgrade my plan"

Copilot analyzes:
├─ Customer history: 2-year subscriber
├─ Current plan: Basic
├─ Usage patterns: Heavy data user
├─ Recommended action: Suggest upgraded plan + add-ons
└─ Next-best-action: "Present Premium with extras"

Agent: "Great! Based on your usage, I have a perfect 
        recommendation..."

Copilot displays:
├─ Customer's usage metrics
├─ Recommended plan details
├─ Comparison of savings
└─ Available promotions (10% if upgrade today)

[Agent presents recommendations]

Customer: "The Premium plan looks good, and 10% off 
         sounds great!"

Copilot suggests:
├─ Add-on: Premium Support (93% value match)
└─ Upsell: Extended warranty (67% match)

Result: Upgraded plan + 1 add-on sale
Copilot Summary:
"Customer upgraded from Basic to Premium plan and added 
 Premium Support. Mentioned promotional discount influenced 
 decision. Total value: $XXX. Customer satisfied."

Business Impact: Increased revenue, improved satisfaction

Best Practices

Knowledge Base Quality

  • Accuracy First - All information must be current and correct
  • Comprehensive Coverage - Address common issues and scenarios
  • Clear Language - Write for quick scanning, not detailed reading
  • Proper Organization - Use tags and metadata effectively
  • Regular Updates - Review and update quarterly minimum
  • Validation Process - Test before publishing

Agent Copilot Configuration

  • Start Simple - Enable basic features first, add complexity gradually
  • Queue-Specific - Tailor for each queue's unique needs
  • Knowledge Curation - Surface only relevant articles
  • Test Thoroughly - Pilot before full deployment
  • Monitor Adoption - Track agent usage and feedback
  • Continuous Refinement - Improve based on data

Agent Enablement

  • Comprehensive Training - Thorough explanation of features
  • Live Demonstrations - Show real examples and use cases
  • Practice Sessions - Let agents use Copilot before production
  • Clear Benefits - Help agents understand time-saving value
  • Easy Access to Help - Support for questions and issues
  • Celebrate Successes - Share agent stories and improvements

Performance Optimization

  • Track Metrics Daily - Monitor AHT, ACW, knowledge usage
  • Gather Agent Feedback - Regular surveys and check-ins
  • Analyze Usage Patterns - Identify which features are most helpful
  • Refine Knowledge - Update articles based on usage data
  • Optimize for Your Business - Tailor features to your priorities
  • Benchmark Performance - Compare pre/post Copilot metrics

Token Consumption

Agent Copilot requires AI Experience tokens for operation:

  • Consumption: 40-60 tokens per user per month
  • Factors: Interaction volume, knowledge article access, AI feature usage
  • Optimization: Monitor usage and optimize knowledge articles
  • Budgeting: Plan tokens based on agent count and deployment scope

Interview Cheat Sheet

Question Answer
What is Agent Copilot? Real-time AI assistance for agents during customer interactions
What does it do during calls? Determines intent, suggests next actions, surfaces knowledge, monitors sentiment
What about after-call work? Auto-generates summaries, suggests wrap-up codes, tracks resolution
What are AI Skills? Modular AI capabilities (knowledge, next actions, sentiment, compliance)
How does it behave on-queue? Continuous monitoring and assistance throughout interaction
What languages does it support? 13+ including English, Spanish, French, German, Japanese, Korean, Arabic, Hindi
How much time does it save? ~9 minutes per interaction (5 AHT + 2 ACW + 1.5 hold time)
What's the expected improvement? AHT reduction 5-10%, ACW reduction 2-3 minutes, CSAT improvement 5-15%
How is it licensed? Per-user with 40-60 tokens per user per month
Does it work omnichannel? Yes - voice, chat, email all supported
Can you customize it? Yes via AI Studio to create custom Guides and Skills
Where is it configured? Admin → Contact Center → Agent Assistance → Agent Copilot
What knowledge does it need? Quality knowledge base (Workbench or Fabric)
How long until ROI? 2-4 weeks to see AHT improvements
What's most important? Quality knowledge base and agent training

Key Takeaways

  • Real-Time Assistance - Continuously monitors interactions providing guidance as they happen
  • Intelligent Understanding - Determines customer intent and emotional state
  • Automatic Documentation - Generates summaries and suggests wrap-up codes
  • Knowledge Integration - Surfaces relevant articles without agent search
  • Multi-Channel - Works on voice, chat, email, and messaging
  • Modular Skills - Combine capabilities for your specific needs
  • Proven Results - 5-minute AHT reduction, 1.5-minute hold time reduction
  • Adaptive Behavior - Responds to conversation flow and customer emotion
  • Global Support - Operates in 13+ languages
  • Continuous Learning - Improves recommendations based on outcomes

Additional Resources

Official Documentation

  • About Agent Copilot: help.genesys.cloud/articles/about-genesys-agent-copilot/
  • Agent Copilot Configuration: help.genesys.cloud/articles/configure-agent-copilot/
  • Agent Copilot Deep Dive: genesys.com/blog/post/genesys-cloud-agent-copilot-deep-dive
  • Agent Copilot FAQs: help.genesys.cloud/faqs/category/agent-copilot/

Support & Training

  • Genesys University: genesys.com/training
  • Community Forums: https://community.genesys.com
  • Technical Support: https://support.genesys.com

Document Version Info

Last Updated: March 2026
Source: Genesys PureCloud Official Documentation
Validated: Current with January-March 2026 releases
Version: 1.0

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