The Analytics Gap: Why AI Architecture Matters
4/9/2026 1:00 PM Eastern
4/9/2026 2:00 PM Eastern
Event details
Organizations continue to invest heavily in data platforms and AI, yet many business users still wait days for answers, and AI initiatives struggle to deliver measurable value. This webinar will examine why enterprise analytics underdelivers and explore what a modern, governed data foundation requires to produce reliable results.
A Crowe specialist will explain why architecture often matters more than the AI model itself, how governance determines whether AI outputs can be trusted, and what a purpose-built, multi-agent AI design enables. The session will conclude with a live demonstration of Crowe Data Concierge to show how business users can access trusted, real-time answers from enterprise data in plain language in seconds.
As a result of participating in this webinar, you should be able to:
- Describe why enterprise analytics initiatives fail to deliver expected value
- Explain how data governance influences the reliability and risk profile of AI outputs
- Differentiate between generic AI deployment and governed, multi-agent AI architecture
- Identify the core components required to enable trusted, self-service analytics
Continuing professional education
Prerequisites: None
Program level: Overview
Advance preparation: None
Delivery method: Webinar (group internet based)
Field of study: Information technology
This session is recommended for 1.0 hour of CPE credit.
Note: All participants MUST be logged into the webinar INDIVIDUALLY to receive CPE credit. CPE credit will only be granted in the name of the individual logged into the LIVE presentation. Crowe is unable to grant CPE credit for groups viewing the webinar or for viewing on-demand recordings of the webinar.
There is no registration fee for participating in this webinar; therefore, there is no cancellation fee.
Presenter
- Trent Teister, Consulting
Who should attend
Chief data officers, chief information officers, analytics leaders, finance leaders, operations leaders, and other decision-makers responsible for data strategy and AI initiatives
Additional information
For additional information, please contact Lyndi Lloyd.