Conference Description
Key Takeaways
- One-day conference focused on scaling enterprise AI beyond pilot projects to deliver measurable business outcomes.
- Designed for CIOs, CTOs, Chief Data Officers, data scientists, analytics leaders, and business strategists.
- Sessions cover data strategy for AI, sustainable operating models, enterprise integration, and measuring AI investment returns.
- Awards continuing education credits including CPE, CEU, PDU, and CISSP.
About the Event
AI / Data Innovation Strategies is an in-person conference held at the Donald E. Stephens Convention Center in Chicago (Rosemont/O’Hare), Illinois. The event brings together business and technology leaders to examine how organizations can transition from isolated AI experiments to enterprise-wide adoption that generates measurable value.
The format combines keynote sessions, panel discussions, and networking breaks. Product presentations are excluded from the talks, maintaining a focus on knowledge sharing and peer discussion. Representatives from sponsoring companies will be available during breaks for informal conversations.
Key Topics
The agenda addresses the practical challenges of enterprise AI deployment. Sessions examine how to develop data strategies that support AI initiatives, transform raw data into actionable insights, and build AI operating models that remain sustainable as organizations scale. Additional sessions explore methods for integrating AI into existing business operations and frameworks for measuring the business impact of AI investments.
A panel discussion features AI and data leaders sharing lessons learned from their implementations and discussing future strategies for data-driven innovation.
Who Should Attend
The conference targets executives and senior practitioners from large and mid-sized enterprises, particularly those working in IT, data, analytics, and business transformation. Attendees seeking to align AI investments with business priorities, improve collaboration between business and technology teams, or establish governance frameworks for scaling AI across business functions will find relevant content.