Overview
The next big step towards AI
Shaping the AI-Native enterprise: Moving beyond experiments to enduring impact
Artificial Intelligence has reached a decisive inflection point for large enterprises. What began as experimentation and isolated pilots is now rapidly becoming a determinant of long-term competitiveness, resilience, and relevance. As AI systems increasingly influence core decisions, customer experiences, and operational efficiency, the responsibility on large ecosystem players has expanded-from adoption to stewardship.
The next phase of enterprise AI will be defined not by who experiments fastest, but by who institutionalises AI responsibly, securely, and at scale. Regulatory expectations, data sovereignty considerations, talent readiness, and trust frameworks are converging faster than anticipated. Data modernisation is emerging as a clear prerequisite for AI scale-requiring enterprises to strengthen data foundations and create resilient data platforms. Organisations that act now-by embedding AI into operating models, governance structures, and value chains-will shape industry standards and unlock sustained advantage. Those that delay risk fragmentation, inefficiency, and strategic irrelevance.
An invitation-only boardroom dialogue for CXOs shaping India’s largest enterprises. This closed-door roundtable is designed to move beyond hype and pilots and instead examine the shared responsibility of ecosystem leaders in driving systemic, enterprisewide AI transformation-securely, responsibly, and at scale.
HCLTech, with OpenAI and NVIDIA, brings to the table its role as a global systems integrator delivering full-stack AI solutions at the forefront of enterprise AI adoption – translating frontier AI capabilities into repeatable operating models, sovereign-ready architectures, and measurable business outcomes.
Key Highlights
Enterprise-wide adoption within 12-18 months when leadership, talent, and operating models evolve together
- Faster time to value across enterprise programmes enabled by AI-native delivery and automation
- Productivity uplift and operational cost efficiency achieved through AI-driven orchestration of core enterprise processes.
- Reduction in AI risk exposure while accelerating time to value, through governance-led design and workforce skill readiness.
- 2–3x scale readiness when enterprises move from use-case thinking to platform-led AI operating models
- 14 February 2026, New Delhi
- 03:15 PM onwards
Speakers
Agenda
- AI as a structural shift, not a technology upgrade
- Why large enterprises now carry disproportionate responsibility in setting benchmarks for trust, scale, and governance
- Framing the outcomes for the discussion
- AI adoption the question before us in not why or when, the real question is how
- Journey towards the Digital Transformation has enriched & enabled the Data paving a transition the Knowledge Enterprises
- Defining the contours of the AI journey, setting the expectations
- Data moderation as a prerequisite for AI Scale: Strengthening Enterprising Data foundation through robust data lakes or federated data lakes strategies
- Building resilient data platforms to accelerate adoption through Enterprise-wide Data Modernisation
- Balancing innovation velocity with regulatory and datasovereignty expectations
- Building trust with regulators, customers, and internal stakeholders
- Why ecosystem leaders must shape standards-not wait for them
- What enterprise leaders do next
- Collective responsibility, collective advantage
- Key takeaways, shared priorities, and leadership commitments




