AI Analytics: Powering Decision Intelligence for the CX Industry

Telecom AI Analytics: Powering Decision Intelligence for the CX Industry

Improving CX Performance


RELEASE DATE
13-Jan-2026
REGION
Global
DELIVERABLE TYPE
Market Research

RESEARCH CODE
KBAE-01-00-00-00
SKU
TE_2026_34269
Yes
SHARE
$2,450.00
In stock
SKU
TE_2026_34269

AI Analytics: Powering Decision Intelligence for the CX Industry
Published on: 13-Jan-2026 | SKU: TE_2026_34269

Need more details?
$2,450.00
Need more details?

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.

Author: Bernardin Arnason

Research Objectives and Methodology of Customer Survey

Respondent Profile

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 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

Growth Opportunities Fuel the Growth Pipeline Engine™

Why Is It Increasingly Difficult to Grow?

Benefits and Impacts of Growth Opportunities

Next Steps


Have questions about this research or need deeper insights?
Speak directly with our analytics experts for tailored recommendations.

Recent related Contact Centers research

17 Jul 2026   |   Latin America   |   Frost Radar

Frost Radar™: Customer Experience Platforms in Latin America, 2026

Customer experience (CX) platforms orchestrate the complexity of modern customer interactions across multiple channels and touchpoints along the entire customer journey, delivering seamless, consistent, and personalized customer experiences. Frost & Sullivan research on this industry includes close ...

03 Jul 2026   |   Global   |   Frost Radar

Frost Radar™: EMEA Customer Experience Platforms, 2026

Customer experience (CX) platforms serve as the operational and intelligence layer through which organizations manage, orchestrate, and continuously optimize customer interactions across every channel and touchpoint. As contact center boundaries expand to encompass digital self-service, AI-driven re...

01 Jul 2026   |   Global   |   Market Research

Global Customer Experience Platforms Market (Premise-based and CCaaS), Forecast to 2030

Abstract: The global Customer Experience Platforms market achieved solid growth in 2025, driven by an acceleration of AI-based and advanced capabilities in contact center implementations. As organizations increasingly realize that providing superior CX is fundamental for competitive differentiation,...

29 Jun 2026   |   Global   |   Market Research

Growth Opportunities in Global Workforce Engagement Management, 2026

Workforce engagement management (WEM) drives performance, agent engagement, and an improved customer experience (CX) in the contact center industry. Frost & Sullivan defines WEM as a strategy to integrate disparate contact center workforce applications, monitor and analyze customer and agent interac...

28 May 2026   |   Global   |   Customer Research

CX Growth Opportunities in the Banking, Financial Services, and Insurance (BFSI) Industry 2025 to 2026

The BFSI sector is in a disruptive state as customer needs and technologies rapidly evolve. Uncertain economic conditions make financial decisions more volatile.

When interest rates drop, consumers have more buying power. In the BFSI industry, this impacts growth in consumer spending for big...

 

Purchase includes:
  • Report download
  • Growth Dialog™ with our experts

Growth Dialog™

A tailored session with you where we identify the:
  • Strategic Imperatives
  • Growth Opportunities
  • Best Practices
  • Companies to Action

Impacting your company's future growth potential.

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.

Author: Bernardin Arnason
More Information
Deliverable Type Market Research
Industries Telecom
No Index No
Is Prebook No
Keyword 1 ai analytics cx market
Keyword 2 decision intelligence platforms
Keyword 3 customer experience analytics
Podcast No
Predecessor None
WIP Number KBAE-01-00-00-00