Registration is required to participate in the Datablazer Mastery Onsite: Agentforce Edition. Check in with our staff in the lobby before heading up to the event. 

Get ready to settle in for a full-day of learning.

Explore the potential of Enterprise AI and the key capabilities required to make it successful. During this session, we will walk through the five stages of Enterprise AI adoption maturity, ensuring that our journey — from use case definition through planning and execution — is grounded in a solid understanding of what it takes to deliver trustworthy, high-value outcomes.

Hear directly from a real customer about their Enterprise AI journey — starting with exploratory analytics, moving through the use of stand-alone generative AI solutions, and culminating in a Sales Agent. Learn how they assessed the need, secured organizational buy-in, and overcame challenges to deliver a deployed, value-generating solution.

The minimum impactful scope is the smallest set of data and capabilities that delivers value. It also informs decisions and supports quick iteration. During this session, attendees will learn how to identify the data needed for the use case, the data management capabilities to support it, and integration approaches that enable delivery, creating a clear path from first win to future expansion.

In a simulated Service Cloud use case, attendees will work with messy Contact and Case data to assess data readiness, uncover issues, and determine whether there is business value in proceeding. Using these insights, attendees will build a clear business case and define MVP scope that can deliver meaningful value while setting the stage for quick iteration.

Lunch will be provided in the Social Lounge for all registered attendees.

Focusing on the Contact object as a common use case, this session will demonstrate proven practices for addressing source data challenges in Data Cloud. We will explore how to design and apply transforms — such as filtering, normalization, and deduplication — to deliver trusted, consistent, complete, and correct data that supports downstream AI and activation use cases.

Building on the first exercise, participants will load CRM data into Data Cloud, create interim DLOs and data transforms to clean and standardize the data, and validate improvements in profile quality metrics. The results will be tied back to the fictional customer scenario introduced in the morning.

Participants will configure an agent to use unified profile data for its responses, incorporating logic that enforces reliability thresholds before taking action. Test scenarios will demonstrate how incomplete or unreliable data changes the agent’s behavior.

We will discuss how we, as business executives, business application owners, consultants, and practitioners, are navigating rapid change and investment complexities.