Skip To Main Content

State of AI in CX Report: Third Edition

See what hundreds of CX leaders and practitioners reveal about how they use AI for CX and what makes a program successful.

Get an inside look at the systems, strategies, and operating practices behind higher resolution rates, lower cost per resolution, and better customer outcomes.

Get your copy of the report now!
Download Now
Thank you for checking out Forethought resources!

You’re one step closer to transforming your support team into an unstoppable force for customer experience.

Check your inbox for a permanent link to your requested resource, and get ready to lead the next wave of CX innovation.

- The Forethought Team

PS. Don't see it in your inbox? Be sure to check your spam/promo folders!
Download Content
Oops! Something went wrong while submitting the form.

AI adoption is no longer enough. Impact is today's standard.

As AI adoption in CX nears 70%, only 2% of AI-using organizations reach excellence. Discover what separates programs that simply deploy AI from those that keep improving performance over time.

AI that takes action drives stronger results

Nearly 74% of programs using action-taking AI report improving resolution rates, compared with 43% of assistive programs. That 31-percentage-point difference marks the largest performance gap across AI maturity stages.

The operating model shapes the outcome

Compare purpose-built, embedded, and DIY approaches across resolution, cost, time to value, and ROI clarity. Learn where each model performs best.

Training and feedback compound performance

Organizations that train AI on historical service data are nearly twice as likely to report an improving resolution trend. Learn how leading teams use QA, feedback loops, and human judgment to sustain gains after launch.

“AI for CX success is no longer measured by whether you’ve deployed AI, but by whether it keeps improving autonomously. The leaders in this area are building systems that learn from service data, preserve context across channels, and use feedback to drive measurable gains in resolution, CSAT, and cost.”

Aakash Kumar
Director, AI Customer Success