Generative AI has the potential to revolutionize industries and transform the way we live and work. However, with great power comes great responsibility - and the potential risks of generative AI cannot be ignored, most notably with respect to data governance, privacy, IP, bias, ethics, workforce usage, and much more. That said, before an organization can dive into the generative AI pool on a business level, it’s mission critical to better understand what the risks maybe, so to determine if it’s indeed a technology your organization or functional areas can use at scale, or if silo usage is best at this time.

In this session, topics of discussion will include, yet will not be limited to:

• Rewards, benefits, and potential
• Risks – governance, oversight, audit, compliance

IA Maturity Level: Early Adoption & Various

Lines of Business Functional Focus: Technology, Operations & Business-Wide

This session explores how to leverage data to create a robust foundation for your automation and generative AI programs. 

We'll delve into the importance of "good and clean data" and how strong data management practices ensure its availability, quality, integrity, and security. This eliminates the "garbage in, garbage out" problem, empowering automation teams to build effective solutions. 

Key Discussion Points: 

• Creating a Data-Driven Strategy: Learn a step-by-step process to map your business using first principles, identify early indicator data, and leverage it to inform strategic automation decisions. 
• Establishing "Good & Clean Data": We'll discuss defining data ownership, establishing data quality standards, and implementing security protocols to safeguard sensitive information. 

IA Maturity Level: All & Various

Lines of Business Functional Focus: Technology, Operations & Business-Wide