In a recent interview with CIO&Leader, Arun ‘Rak’ Ramchandran, CEO of QBurst, outlines a more grounded perspective on enterprise AI.

Rak notes that success lies in addressing both the “first mile of data readiness” and the “last mile of AI adoption”, ensuring data is usable and AI is embedded within core business processes. At QBurst, this is operationalized through strong data engineering, system integration, and orchestration.

He points to tangible outcomes as proof. In one instance, QBurst transformed a struggling AI chatbot for a global retailer into a production-grade system—not by changing the model, but by re-engineering data pipelines, improving backend integration, and enabling continuous optimization.

As adoption matures, the focus is shifting toward deeper integration. AI is no longer an overlay, but an integral part of workflows. More advanced systems, including agentic AI, are gaining traction, but with a strong emphasis on control, governance, and clearly defined roles.

How organizations measure ROI is changing. Beyond cost savings, the focus is increasingly on speed, accuracy, and scalability.

Ultimately, enterprise AI is entering a phase defined by discipline, Rak notes. Competitive advantage will come not from experimentation alone, but from the ability to integrate, operationalize, and scale AI effectively.