Organizations scale enterprise AI by moving from isolated pilots to production-grade solutions supported by a repeatable AI operating model, governance, MLOps practices and clear business ownership. That is the central conclusion DS Stream took from the Nasscom Agentic AI Confluence 2026 in Bangalore, where 920+ delegates from 560+ companies asked the same question: not whether AI creates value, but how to scale it.
In September, a 4-person DS Stream leadership team spent several days in Bangalore, India, visiting our local office and participating in the conference. The trip combined client and partner meetings with time spent alongside the people who build DS Stream every day.
What does it mean to scale enterprise AI?
Scaling enterprise AI means integrating AI into business processes in a way that delivers sustainable, measurable results – rather than running a growing number of disconnected experiments. Across industries, the focus is shifting toward three capabilities: sustainable Enterprise AI capabilities, effective AI operating models, and measurable business value from Data & AI investments.
To be honest, most of the discussions we had were actually focused on how to create autonomous Agentic solutions for very well-defined business areas. We touched the need for efficient data delivery directly to the Agents, we were evaluating with audience need for having strong semantic layer and how AI Context layer is slowly appearing as the major need to scale Agentic platforms.
Nasscom Agentic AI Confluence 2026 in numbers
Nasscom Agentic AI Confluence 2026 gathered 920+ delegates, 560+ companies, 60+ speakers and 45+ sessions and experiences in Bangalore, making it one of the largest Agentic AI gatherings in India this year.
| Nasscom Agentic AI Confluence 2026 | DS Stream at the event | |
|---|---|---|
| Scale | 920+ delegates from 560+ companies | 4-person team onsite |
| Program | 60+ speakers, 45+ sessions & experiences | 3 roundtable sessions attended |
| Engagement | Business and technology leaders across industries | Hundreds of visitors at the DS Stream booth |
| Outcome | Shared focus on moving from pilots to production | Dozens of business & data conversations |
From AI pilots to production: the main theme of Nasscom Agentic AI Confluence 2026
The clearest theme at Nasscom Agentic AI Confluence 2026 was market maturity: for most organizations, the question of whether AI can create value has been answered. The challenge today is how to move from AI pilots to production.
From the opening hours until the end of the conference, hundreds of visitors came to the DS Stream booth, and the team took part in 3 roundtable sessions alongside industry leaders. Across dozens of business and data conversations, participants asked practical questions about implementation, scalability, governance and business value rather than treating AI as a buzzword:
- how to move beyond isolated pilots,
- how to operationalize AI across the organization,
- how to ensure AI investments deliver measurable outcomes rather than short-term experimentation.
Key takeaway: conversational AI, talking to the data, those are the main topics of interest today. We realized that most companies are still looking for the right experts to explain those topics, especially when it comes to large scale solutions.
Discussions repeatedly touched on Enterprise AI strategy, AI governance, Generative AI vs traditional AI, data readiness and the organizational capabilities required to scale AI responsibly.
AI pilots vs. production AI: what changes
| Dimension | AI pilot | Production enterprise AI |
|---|---|---|
| Goal | Prove that AI can create value | Deliver Autonomous Agentic Solutions |
| Scope | Isolated use case | Integrated into organization |
| Delivery | One-off initiative | Repeatable AI operating model (AI Factory) |
| Governance | Minimal | Defined AI governance and MLOps practices |
| Ownership | Isolated team | AI COE with strong business ownership and prioritized use cases |
Leaders at the conference were looking for frameworks, methodologies and operating models that make the right-hand column achievable – which matches what DS Stream sees in client work.
The AI Factory operating model: a repeatable path to production
An AI Factory operating model enables teams to move consistently from ideas and proofs of concept to production AI solutions, supported by appropriate governance, MLOps practices and strong business ownership. Organizations increasingly look for this kind of repeatable approach to AI delivery instead of one-off initiatives.
The real differentiator is no longer access to technology. Modern cloud platforms, AI services and increasingly powerful models are more accessible than ever. What separates successful organizations is the ability to combine technology, data, processes and people into a scalable AI operating model that delivers business outcomes consistently and responsibly.
Agentic AI governance and generative AI at enterprise scale
Agentic AI creates the greatest value when it is supported by robust Data & AI platforms, well-defined governance frameworks and a clear path from experimentation to production deployment. Interest in autonomous and semi-autonomous systems continues to grow, and participants understood that technology alone is not enough.
Successful adoption requires a combination of strong data foundations, governance, domain expertise and a clear focus on business objectives. Many conversations at the conference focused specifically on how to operationalize generative AI and how to establish effective AI governance for agentic AI ahead of larger-scale adoption.
Technology matters. People matter more.
The most successful AI initiatives are driven by teams that demonstrate professionalism, accountability, expertise and a commitment to quality – not by technology alone. Every meaningful conversation DS Stream had during the week pointed back to people.
The pace of innovation in AI is extraordinary: new models, platforms and capabilities emerge at an unprecedented rate. As AI becomes more accessible and powerful, qualities such as trust, craftsmanship and responsibility become more important, not less. They are often the difference between a successful transformation and another unfinished experiment.
One company across time zones: DS Stream India
DS Stream operates as one organization united by shared goals, values and ambitions – not as separate teams in different locations. Spending time in person with the DS Stream India team reinforced this.
The hospitality, energy and commitment of the team made a lasting impression, as did the level of ownership with which colleagues approach both client work and the growth of the company. Strong relationships and collaboration remain the foundation of long-term success, regardless of how quickly technology evolves.
What's next for enterprise AI adoption
Agentic solutions, fully automated workflows, semantic and context layers of course. What else – the real experience on how to adopt those technical AI capabilities inside business parts of the Organizations. That was our big advantage; we were able to advise on how to support CMO, CDO, Supply Chain, eCommerce, and so many more areas. Hopefully some of the hints will save the money that you would spend on failed AI initiatives.
DS Stream thanks everyone who visited our booth and shared their perspectives, and the entire DS Stream India team for making the visit memorable. The conversations started in Bangalore will continue long after the event.
