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AI Analytics: Powering Decision Intelligence for the CX Industry

Publisher Frost & Sullivan
Published Jan 13, 2026
Length 35 Pages
SKU # MC20763543

Description

One of the most powerful applications of AI technology in CX today is AI-powered analytics. The introduction of AI analytics can supercharge contact center business intelligence, transforming it from a tool that tells a story of the past to an instrument that informs the future. AI analytics enable a range of new capabilities, including:

Automated insight generation that autonomously analyzes large, complex datasets to identify patterns, trends, and anomalies, all of which are capabilities that previously required a data scientist to implement.

Predictive and prescriptive analytics through machine and deep learning which enables BI tools to move beyond populating dashboards to delivering forecasts, risk assessments, and actionable insights that drive proactive decision making.

Natural language querying and conversational analytics that enable teams to interact with BI systems using natural language, democratizing access to business insights and decision intelligence.

Real-time data analysis that continuously processes and analyzes streaming data, providing real time insights that enhance operational agility and responsiveness to changing market or customer conditions.

Advanced customer and sentiment analysis that can process customer interaction data (e.g., voice, text, chat) to extract customer sentiment, intent, and experience signals enabling more comprehensive and nuanced insights from customer behavior.

This study explores important contact center applications and reveals how AI analytics has transformed from a reporting layer to become the operational nervous system of the modern contact center, connecting customer experience optimization, virtual agent performance, and human agent enablement into a unified intelligence fabric. Contact center application analysis includes:

AI Analytics as a Driver for Identified CX Priorities

Addressing Customer Frustrations with Virtual Agents

Addressing Customer Frustrations with Live Voice

Using AI Analytics to Inform Improving Agent Experience Priorities

Addressing Omnichannel Integration Challenges with AI Analytics

Leveraging AI Analytics for Contact Center Outsourcing Decisions

Additionally, this study outlines the AI analytics capabilities of 22 contact center software vendors, plotting their solutions on an AI analytics capabilities matrix.

Table of Contents

35 Pages
Research Objectives and Methodology
Research Objectives and Methodology of Customer Survey
Respondent Profile
Key Findings
AI Analytics in CX
AI Analytics Introduction
AI Analytics vs. Traditional BI
Generative AI as a Key Enabler of AI Analytics
AI Analytics Tech Stack
AI Analytics in CX Use Cases
Strategic CX Benefits From AI Analytics
AI Analytics Impact on CX
AI Analytics as a Driver for Identified CX Priorities
Addressing Customer Frustrations with Virtual Agents
Addressing Customer Frustrations with Live Voice
Using AI Analytics to Inform Improving Agent Experience Priorities
Addressing Omnichannel Integration Challenges with AI Analytics
Leveraging AI Analytics for Contact Center Outsourcing Decisions
AI Analytics in CX Capabilities Matrix
AI Analytics in CX Capabilities Matrix
Appendix
Growth Opportunities Fuel the Growth Pipeline Engine™
Why Is It Increasingly Difficult to Grow?
The Strategic Imperative 8™
Next Steps
Benefits and Impacts of Growth Opportunities
Next Steps
List of Exhibits
Legal Disclaimer

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