AI Value Gap Explained

In this conversation, Dhiraj Rajaram, Founder and CEO of Mu Sigma, joins Tessa Burg, CTO at Mod Op, for one of the most honest conversations about why enterprise AI is failing. He makes the case that AI isn’t the bottleneck, the problem is in the organizational foundations and ways problems are solved. 

If your AI initiatives are stalling between isolated use cases, this is the conversation that explains why.

Key Takeaways

1. We are in an AI bubble, and the trough of disappointment is coming whether you’re ready for it or not.

2. Organizations have become expert at solving problems  function by function, but customers experience the whole journey. AI needs to connect the dots across the enterprise, too. 

3. Businesses capture what happened but not the why behind those decisions. AI trained on incomplete memory will always produce incomplete/inaccurate decisions.

4. Before deploying AI, you need to build a Field of Context: the organizational intelligence layer that gives agents the reasoning foundation they need. 

5. You can’t make new food in an old kitchen: the organizations that win will invest in building the right infrastructure, not just adding new tools to old foundations.