AI remembers what happened. Does it remember why?
Enterprise AI is not struggling because organizations lack AI models or data. The challenge is that enterprises continue to solve problems as individual “stars” rather than interconnected “constellations,” while their systems, processes, and decision-making structures were never designed for the scale and complexity of AI.
In this conversation with Ashley Braganza, Professor, Brunel Business School, on The AI Adoption Podcast, Dhiraj Rajaram, Founder and CEO of Mu Sigma, explores what it takes to move AI beyond isolated use cases and toward enterprise-scale impact. He introduces the Field of Context — an organizational intelligence layer that captures not just what happened, but the perceptions, decisions, and reasoning behind it. Because scaling AI requires more than smarter models or more data; it requires the context and systems that allow AI to reason, learn, and act across the complexity of the enterprise.
Key Takeaways
- Why is enterprise AI struggling to deliver?
- Stop solving problems one by one. Start seeing the bigger picture.
- Does your AI have a Field of Context?
- From Resilient to Antifragile: What should enterprises aim for?
- What does it really take to make Agentic AI work?
- Beyond what happened: Understanding Perception, Decisions, and Actions.
- Are siloed AI initiatives creating more complexity?
- Can intelligence exist without intuition?
- Is dark context the missing piece in enterprise AI?
Speaker Info
