Context is becoming the missing layer in enterprise AI
The enterprise AI market is entering a new phase. For the past several years, the focus has been on larger models, faster inference and broader deployment of generative AI capabilities. Yet despite growing investment, many organizations continue to struggle with governance, accuracy, operational scalability and measurable business outcomes.
The challenge is becoming increasingly clear: Better models alone do not guarantee better results.
According to theCUBE Research, organizations are rapidly moving from AI experimentation to production deployments, but many are discovering that the gap between what AI models can do and the value they actually deliver remains stubbornly wide. Increasingly, the conversation is shifting from model performance to context.
In the latest episode of the AppDevANGLE podcast, theCUBE Research’s Paul Nashawaty spoke with Molham Aref, founder and chief executive officer of RelationalAI, about the growing AI value gap, the importance of contextual intelligence, and why the next wave of enterprise AI may depend more on relational understanding than model advancement.
