After a highly successful U.S. edition, Axtria Ignite Global arrived in India at a defining moment for the life sciences industry. The event took forward the conversation that AI is no longer about if AI will transform enterprises. It is about whether organizations are ready to move from experimentation to ownership.
With 100+ senior clients and partners in attendance, the India edition reflected the scale of what we are building together – deeper partnerships, stronger ownership, and AI-driven transformation across enterprises.
Ignite Global 2026 convened over a 100 global life sciences industry leaders, practitioners, and decision-makers for an honest dialogue on scaling AI and building platforms that power predictable execution. Across keynotes, power dialogues, experiential discussions, live demonstrations, and an executive roundtable, one message stood out:
The technology is ready. Enterprise systems must catch up.
From Capability-Building to Enterprise Ownership
The opening reflections set the tone for the day with capability-building has served the industry well, but it is no longer sufficient. AI must move beyond pilots and proofs of concept into scaled, embedded deployment across core business functions.
Ignite was positioned as a practitioners’ platform — a space where real lessons outweigh buzzwords and practical experiences matter more than hype.
Looking back at the early 2000s — when cloud infrastructure did not exist, connectivity was unreliable, and computing power was limited — the ambition to build scalable analytics platforms remained bold. The transition from consulting-led analytics to product- and platform-led solutions embedded with domain expertise laid the foundation for today’s transformation.
The parallels with AI today are striking. Despite technological sophistication, enterprises face familiar hurdles:
- Limited contextual understanding
- Data readiness gaps
- Semantic inconsistencies
- Lack of trust in AI systems
The conclusion was unmistakable: AI will scale only when it is contextual, domain-embedded, and trusted.
India’s Rise as a Decision-Intelligence Hub
A central theme throughout the day was India’s emergence as a global AI powerhouse. With a significant concentration of life sciences analytics talent based in India, GCCs are evolving from execution engines to strategic decision hubs.
This shift is visible in three structural transitions:
- Execution → Outcome Ownership
Teams are increasingly accountable for business impact, not just insights.
- Projects → Scalable Systems
Scaling across markets demands trust, standardization, and robust data architecture.
- Data Science → Decision Intelligence
The challenge is not building models — it is driving behavioral adoption and enterprise-wide trust
The reflection questions posed to the audience were direct:
- Are we owning decisions or only supporting them?
- Are we building scalable systems or one-off solutions?
- Are we truly AI-enabled — or still experimenting?
Future-ready GCCs must be present at every major business table, owning enterprise mandates end-to-end.
From Vision to Experience: AI in Action
One of the biggest highlights of Ignite Global India was the live demonstration of Axtria’s AI-led platforms and products.
Across dedicated experience booths, clients and partners engaged with real-world applications spanning analytics, decision intelligence, and commercial transformation. These were not conceptual prototypes — they were enterprise-ready systems addressing real operational and strategic challenges.
The response was overwhelmingly positive. There was strong curiosity, deep engagement, and multiple follow-up conversations initiated during the event itself — a clear indicator that the industry is ready to move beyond experimentation and toward adoption at scale.
The demonstrations reinforced a critical theme of the day:
AI transformation is no longer theoretical — it is operational.
Mainstage: Rise of the Thinking Enterprise
This fireside chat featured Pankaj Rai, Group Chief Data and Analytics Officer, Aditya Birla Group, and Deepak Bisht, Global Head, Corporate Centers, Novartis moderated by Lokesh Jindal, Head of Products, Axtria.
The conversation shifted toward leadership in the age of agentic AI.
For the first time, enterprise systems can make micro-decisions independently. This marks the emergence of the “thinking enterprise” — where AI agents move beyond automation to interpretation and action.
Yet a central tension emerged: AI is advancing faster than organizational readiness.
The discussion centered on deeply human questions — do we truly trust AI outputs, are our organizational cultures prepared for AI-led workflows, and are leaders personally embedding AI into their own daily decision-making? The foundations for success were equally clear: high-quality data, strong governance and guardrails, thoughtful talent and role redesign, and structured change management. Ultimately, enterprise transformation will require leadership self-transformation.
Owning the Global Mandate: Moving from Contributing Insights to Owning Enterprise Decisions
Led and moderated by Sundeep Singh, Principal, Axtria, this power dialogue brought together Srinivas Thakkal, Global Leader, Analytics, AI & Decision Intelligence, Novartis, and Madhu Krishnan, Head Data Science & BI Solutions, BI&A, GCC, BMS.
Platform ownership emerged as a decisive competitive advantage.
GCC evolution is entering a new phase — moving from support to influence, and now to ownership. True maturity means being accountable for outcomes, not just analytics.
Enterprise platforms are increasingly measured by:
- Adoption
- User experience
- Interoperability
- Speed-to-market
As tools and proofs of concept multiply, governance must act as an enabler of scale — guiding build-versus-buy decisions and ensuring systems are interoperable and enterprise-grade.
The era of isolated POCs is ending.
Scalable, global platforms must now take priority.
The Anatomy of an Agentic System: AI Only Matters When It’s Trusted
Moderated by Shikha Singhal, Principal, Decision Science, Axtria, this thought exchange featured Sravan Bhamidipati, Director, Data Science Omnichannel Analytics, Amgen; Gaurav Sawhney, Director, Regeneron Data Platform, Regeneron; and Akhil, Senior Director of Technology, Business Units (Commercial), Eli Lilly.
Many AI pilots demonstrate technical promise — yet fail to scale.
This session explored the reality of the “POC graveyard” and why AI transformation often stalls.
Barriers to scaling include:
- Data readiness
- Adoption resistance
- Ambiguous ownership
- Weak measurement frameworks
- Immature governance
The insights were powerful: AI failures are rarely technology failures. They are system and process failures.
Trust emerges as the defining factor. Without domain context, semantic layers, and embedded governance, AI outputs lack credibility.
Agentic AI introduces additional complexity. Enterprises must rethink governance across:
- Compliance
- Workflow orchestration
- Decision accountability
Legacy data environments are increasingly exposed under agentic systems. Observability, auditability, and guardrails are no longer optional.
Scaling AI is not about building better models. It is about building better enterprise systems.
The Value Jump in Moving from Productivity to Performance
Moderated by Anuj Mahajan, Senior Director (CE), Axtria, this experiential discussion featured Arvind Balasundaram and Sreemannarayana Balineni, ED BSI Data Analytics for Novartis International, Novartis.
Execution realities took center stage.
Ambitious field teams often struggle not because of strategy — but because systems are fragmented. Data is scattered. Reports conflict. Approvals slow momentum.
“Execution is what happens when strategy meets reality — and reality always wins.”
True execution excellence cannot depend on heroics. It must be engineered into unified platforms.
The value jump becomes evident when organizations move from productivity gains to performance transformation:
- Reduced manual effort
- Faster processing cycles
- Fewer field inquiries
- Improved target achievement
- Ability to scale across markets without proportional headcount growth
Beyond efficiency lies effectiveness — knowledge graphs, multimodal integration, and pattern detection driving measurable top-line impact.
Great organizations do not wait for superheroes. They build systems that make excellence repeatable.
The Moment of Choice: Embrace AI and Change or Use AI to Improve Current Processes
Moderated by Sonia Vergis, Principal, Axtria, this fireside session featured Neha Agarwal, VP – Head Data Enablement & Operations, Novartis.
The closing conversation reframed the transformation journey as a leadership choice.
Support centers have evolved into global nerve centers — influencing strategy, innovation, and enterprise value creation.
AI is no longer just accelerating tasks. It is thinking alongside humans.
The real question is not whether AI can be deployed. It is how boldly organizations are willing to reimagine processes.
Five foundational layers define an AI-enabled enterprise:
- Data
- Governance
- Platforms
- Semantic/context layers
- Agentic orchestration ecosystems
AI will not replace intuition, creativity, or imagination. Instead, it frees humans from repetitive workflows — enabling higher-order thinking and innovation.
The greatest barrier to transformation is not technology. It is leadership imagination.
Executive Roundtable: Shared Accountability
The executive roundtable reinforced several shared priorities:
- trust must be deliberately engineered into systems,
- ownership must be clearly defined, and
- governance must act as an enabler of speed rather than a constraint.
Leaders emphasized that scalable platforms must replace fragmented experimentation, and that decision accountability needs to move closer to GCCs to drive true enterprise ownership.
The Road Ahead
Axtria Ignite Global 2026 was not a celebration of AI capability. It was a call to responsibility.
The industry has moved beyond proving that AI works. The next frontier is proving that enterprises are ready — structurally, culturally, and operationally — to scale it.
The ambition is no longer capability-building. It is ownership.
And the organizations that embrace this shift will not merely adopt AI — they will redefine how decisions are made.
**The views expressed by the panelists are their own and do not necessarily represent those of their respective organizations.
