I recently sat down with Manasi Vartak, Cloudera’s chief AI architect, and Mike Gualtieri, vice president and principal analyst at Forrester Research, for Cloudera’s 2026 Trends in Data and AI webinar to discuss how to deploy agentic AI at scale.
While our conversation had a forward-thinking, future-oriented slant, I kicked off the webinar by posing this retrospective question: What is one belief about AI that died in 2025?
Between the three of us, we discovered that in 2025, several long-held beliefs about AI finally collapsed. I want to share with you the philosophies Manasi and Mike identified that we are leaving behind as we step into this new and exciting year in AI development.
The Beliefs That Died: The Intellectual Gatekeeping of Agentic AI
2025 began with the belief that agentic AI would be accessible only to a select few. With novel technologies, it is a basic instinct to defer to the tried-and-true experts: PhDs, engineers, and so on.
However, we are now seeing regular business users build their own functional AI pipelines. Manasi recalled the “lightning strike moment” from last year that sparked this realization—at a hackathon in our Agent Studio, an employee from our strategy department built a complete pipeline that had the potential to save $3 million a year. This was an incredible feat performed by someone without specialized training in agentic AI strategy.
To Manasi, this was the sign that agentic AI is truly being democratized across the board.
The Beliefs That Died: Ubiquity of AI Hallucinations
This past year, Mike noticed a marked reduction in AI hallucinations. He acknowledged they still occur but pointed out that, in the past, conversations surrounding AI use focused heavily on them as a threat to its dependability. Now, these fears are much less common.
Mike posited that people now have a better understanding of how to control the scope of an LLM model through prompting, RAG techniques, and other methods. Enough users now understand the circumstances in which these issues arise, as well as the mitigating and eliminating techniques to reduce this phenomenon.
The Bigger Pattern
AI has become genuinely actionable because it is now reliable and usable at scale. As agentic AI becomes more democratized, autonomous systems are no longer limited to elite technical teams—they can be deployed across organizations to execute defined tasks end-to-end. Improved accuracy and fewer hallucinations mean these systems can operate with minimal human oversight, shifting AI from an advisory role to an operational one.
Operational AI truly stands out because it reliably eases manual work while achieving impressive results like quicker cycle times, cost savings, and better decision-making. It’s exciting to see how automation brings real value to daily operations, making them smarter and more efficient, rather than just being limited to isolated tests.
Why These Belief Shifts Matter Going Into 2026
As trust in AI becomes informed rather than aspirational, the question is no longer whether AI can act, but where it is allowed to act. With increased confidence in data integrity and greater output reliability, AI can now move beyond isolated silos into core business processes and decision-making loops.
The real challenge now is whether organizations are structured to support this democratization. Spreading AI throughout the entire company means shifting away from bottlenecks that restrict experimentation to just a few technical teams. When operational leaders can safely access data across different environments, they’re empowered to build, test, and launch AI-powered tools that truly meet business needs. Without wider, well-managed access to data, AI stays centralized and disconnected from daily operations.
Organizations stuck in old beliefs or unwilling to adapt to new ones risk stalling and falling by the wayside of technological advancements. Cloudera’s platform is designed to avoid this outcome and weather these changes in the ever-volatile AI landscape. Whether your data resides in the cloud, in data centers, or at the edge, Cloudera provides universal access to data for AI across the entire enterprise, with governed, enterprise-wide intelligence.
These themes and more are covered in detail by Manasi, Mike, and me in our talk, and I invite you to explore these shifts in greater depth with us in our 2026 Trends in Data and AI webinar. For more insight into what these observations mean in practice and how your organization can make the most of democratized AI in your own environment, explore Cloudera’s latest resources.
