How Nagarro bridges the gap between AI ambition and enterprise reality

Nagarro's Viyom Jain explains how ambition meets reality in enterprise AI, and why trust, culture, and human context matter as much as algorithms.

- By Shrikanth G

Enterprise Al is no longer short on ambition. What it often lacks is realism. As organisations race to deploy personalised, AI-led systems, the real challenge lies not in algorithms, but in data quality, human adoption, and trust. In this conversation with Dataquest, Viyom Jain, MD and Global Business Unit Head for Enterprise Products at Nagarro, reflects on moments where expectations ran ahead of reality, how a flat culture enables ethical course correction, and why future-ready technology leaders must think beyond stacks and systems. His insights offer a grounded view of what it truly takes to make Al work at enterprise scale.

Experimentation is core to how we work. We encourage teams to fail fast so they can quickly identify ideas that are not worth pursuing.

At Nagarro, our flat and non-bureaucratic structure shapes how we work every day. Decisions are guided by ideas rather than titles.

Al personalisation is touted as a Nagarro strength, but the industry often over-promises. Can you share a recent project where ambition ran ahead of reality—and how you recalibrated client expectations without slowing innovation?

The industry often speaks of instant transformation, whereas AI maturity evolves over time. We have seen this in several projects ourselves. For example, we partnered with a global specialty chemicals company to use AI for generating structured meeting summaries, extracting action items, and speeding up decision-making. The challenge was not the AI itself but the fragmented inputs such as emails, handwritten notes, and whiteboard images, which led to early outputs that were promising but inconsistent.