The journey towards effective agentic AI implementation is frequently obstructed by insufficient data quality. Before enterprises can fully embrace multi-agent orchestration, they need to ensure their data infrastructure is robust. Patricia B. Moore, AI field chief technology officer at Boomi LP, emphasized this during an interview at Boomi World 2026, noting the widening gap between ambitious AI goals and operational capabilities.
The Importance of Data Trust
Moore asserts that trust is foundational for deploying agentic solutions that deliver genuine value. "It starts with trust. You have to have context in order to have that trust to have agentic solutions that are actually going to deliver value; you need your data to be connected, you need your systems to be automated," she stated. This highlights the need for a stable data management framework that integrates existing systems and automates processes to ensure accurate data flow.
Moving Beyond Legacy Systems
Transitioning from traditional data management systems—designed for human interpretation—to an agentic framework requires organizations to surface and codify undocumented knowledge. Moore pointed out that without a cohesive understanding, agents might make decisions based on conflicting information. For instance, if finance, operations, and sales departments each define an "active customer" differently, this inconsistency can lead to agents acting on misleading data.
Addressing the Challenges with Meta Hub
To address these challenges, Boomi has introduced Meta Hub, a tool aimed at alleviating what Moore calls the "tribal knowledge tax." This term refers to critical business knowledge locked away in undocumented silos. By creating a semantic layer that reconciles varying definitions within an organization, Meta Hub enables more coherent decision-making by agents operating independently of human oversight.
https://www.youtube.com/watch?v=gPpDJv4-OqE
Moore explained, "When you have agents making decisions without a human in the loop, they need to understand the things that aren’t normally documented." Moving to a more agentic world requires a shift in mindset: organizations must document knowledge that has historically rested within their workforce. This could involve creating business glossaries or similar resources to provide valuable context to AI agents.
The Path Forward
With over 30,000 customers, Boomi is well-positioned to help enterprises navigate the complexities of integrating agentic AI into their existing frameworks. By applying principles from API management directly to agent management, the company promotes a crawl-walk-run approach to success. This strategy allows organizations to build on their current integrations as they advance towards the more complex demands of multi-agent orchestration.
While many enterprises are eager to adopt agentic AI, the road to successful implementation is fraught with challenges, primarily rooted in data trust and quality. As businesses strive to innovate, establishing a solid foundation of data governance and management will be crucial in realizing the full potential of agentic solutions.
The stories that move AI & crypto markets — before the market reacts.
Free. 7am ET. Five stories. 62,400 readers.
