Speakers
AI is rapidly becoming a priority for Salesforce leaders – but most conversations start with features, not fundamentals. Before organizations can scale AI, they’re running into a more difficult question: can we actually trust the data that it’s working with?
In this research-led session, we move beyond hype to explore how Salesforce teams are really approaching AI today, based on insights from 323 respondents across the ecosystem. We’ll unpack where adoption stands, where confidence breaks down, and why data quality is the true constraint shaping every AI initiative.
What We’ll Cover:
- The Real State of AI Adoption in Salesforce: Why many teams are still in planning or pilot stages, and what this says about readiness across the ecosystem.
- Why Data Reliability Is the Real AI Bottleneck: How gaps in data quality and consistency are limiting AI impact, even as interest and investment grow.
- Where AI Can (and Can’t) Be Trusted Today: Practical use cases for AI in Salesforce data quality, from surfacing anomalies and duplicates to supporting prioritization, and where human control is still essential.
- Building the Foundation for Safe AI Adoption: A step-by-step approach to improving data quality, reducing noise, and introducing AI with appropriate transparency, governance, and control.
Join us to understand what 323 Salesforce practitioners revealed about AI readiness and leave with practical steps to improve data quality, reduce risk, and prepare your org for trustworthy AI-assisted automation.
