The journey from raw data to meaningful decision-making is rarely linear. It is shaped by incomplete information, unclear ownership, shifting context, and systems that are often more implicit than intentional.
In this discussion, we step away from the surface narrative of tools and dashboards to examine the underlying mechanics of how decisions are actually formed. What does it mean for data to be reliable? Where do most initiatives quietly fail? And why does an increase in data often introduce more ambiguity rather than less?
By bringing together community perspective, technical depth, and strategic thinking, this session explores how humans, processes, and AI can be aligned into systems that are not only effective, but also transparent and adaptable over time.
What You’ll Take Away
Participants can expect a more grounded understanding of:
- The structural reasons behind poor decision outcomes, even in data-rich environments
- The importance of context, ownership, and data integrity in shaping trust
- The gap between theoretical AI capability and practical implementation
- How to design decision-making loops that evolve with changing inputs
- When data should be relied upon, and when it should be questioned
- Practical ways to bring coherence between human judgment, process, and AI systems
Speakers & Host
Leslie Gestautas (Speaker)
Leslie Gestautas is a Salesforce professional specializing in solution architecture and business transformation. She works at the intersection of strategy and execution, helping organizations translate technical capabilities into decisions that create measurable impact.
Eric Dreshfield (Speaker)
Eric Dreshfield is a Salesforce MVP Hall of Fame inductee and a globally respected leader within the Salesforce ecosystem. His work has consistently focused on community building, knowledge sharing, and shaping how professionals engage with evolving technology landscapes.
Suren Reddy Katta (Speaker)
Suren Reddy Katta is a technology leader with a strong focus on enterprise architecture and digital transformation. His work centers on designing scalable systems that bring structure to complexity and enable organizations to make more informed, outcome-driven decisions.
Atisha Rajpurohit (Host)
Atisha Rajpurohit is an AI engineer and statistical analyst at EY, focused on applying data and artificial intelligence in ways that translate into tangible business outcomes. She is an active voice in the AI community and is particularly interested in how emerging technologies intersect with real-world decision-making.
Who This Is For
This conversation is intended for individuals who work closely with data and are responsible for translating it into decisions.
It will be particularly relevant for those who recognize that the challenge is not access to data, but understanding the systems, assumptions, and trade-offs that shape how decisions are ultimately made.
Join the conversation
Join here: https://studio.restream.io/end-brzr-uxc
Clarity in decision-making does not come from data alone. It emerges from how data is structured, interpreted, and challenged within a system. This session offers a closer look at that system. Join the conversation.