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Schedule 2024

Session 405: Case Studies in Successful AI and ML - A Transformation Roadmap

Jeff Rumburg  (Managing Partner, MetricNet, LLC)

Date: Thursday, October 24

Time: 10:15 am - 11:15 am

Pass Type: Standard + Workshop + Site Tour, Standard Conference Pass, Training + Standard Conference Pass - Get your pass now!

Track: Maximize Productivity and Operations, Revolutionize the Experience

Session Type: Session

Vault Recording: TBD

In this session, Jeff Rumburg will explore the transformative potential of Artificial Intelligence (AI) and Machine Learning (ML) in redefining the landscape of contact centers. The presentation will focus on how AI and ML technologies can revolutionize business processes, enhance operational efficiency, and drive significant growth. Jeff will discuss the journey from assessing readiness for AI/ML implementation to realizing a substantial return on investment through improved customer satisfaction, cost savings, and increased productivity.

Jeff will highlight how these technologies streamline operations, enhance efficiency, and keep businesses ahead of the competition. He will also cover the critical stages of AI/ML implementation, including strategy design, model development, deployment, and optimization.

Attendees will gain insights into the importance of a successful go-live strategy, including employee training and system integration. The presentation will emphasize the value of ongoing support, continuous improvement, and adaptation to evolving business needs and goals. Through real-world examples, Jeff will demonstrate how AI and ML are not just futuristic concepts but practical tools for driving innovation and long-term success in contact centers.


1. Understanding the transformative impact of AI and ML in contact centers.
2. Developing and implementing a tailored AI/ML strategy for maximum ROI.
3. Navigating the stages of AI/ML implementation from readiness assessment to go-live.
4. Strategies for optimizing AI/ML technologies post-implementation.
5. Emphasizing the importance of continuous improvement and adaptation in AI/ML initiatives.