Conference Description
Key Takeaways
- Enterprise-focused summit examining artificial intelligence and data transformation strategies for Indian organisations
- Coverage spans generative AI, agentic AI, autonomous workflows, multimodal models and cloud modernisation
- Designed for CIOs, CTOs, data leaders and digital transformation executives from large enterprises
- Addresses practical challenges including AI return on investment measurement and legacy system modernisation
- Format includes keynotes, expert panels, live demonstrations, roundtables and structured networking
Introduction
The AI & Data Summit India brings together senior technology and business leaders to examine how artificial intelligence and data strategies are reshaping enterprise operations across the country. Organised by IDC, the research and advisory firm, this executive-level gathering addresses the practical realities of scaling AI initiatives within large organisations, from modernising underlying data architectures to demonstrating measurable business outcomes. The timing reflects a broader inflection point for Indian enterprises, where AI investment is accelerating faster than overall technology spending, yet many organisations continue to grapple with implementation challenges that prevent them from realising anticipated returns.
About This Event
The summit takes place at Taj Swarna in Amritsar, offering an in-person format designed to facilitate substantive dialogue between technology executives. The programme structure combines keynote presentations from global thought leaders with interactive elements including expert panels, live technology demonstrations, roundtable discussions and one-to-one meetings. Workshop sessions provide opportunities for deeper exploration of specific technical and strategic topics.
IDC positions the event as a platform for learning, networking and collaboration among India’s technology leadership community. The executive-level focus means content is calibrated for decision-makers responsible for enterprise-wide technology strategy rather than technical practitioners seeking implementation guidance.
Generative AI, Agentic Systems and Autonomous Workflows
The summit’s technical agenda reflects the rapid evolution of enterprise AI capabilities over recent years. Generative AI remains a central theme, but discussions extend beyond content generation to examine how these systems integrate with broader operational workflows. Agentic AI represents a significant area of focus, referring to AI systems capable of autonomous decision-making and task execution with minimal human intervention. These systems differ from traditional automation by their ability to adapt to changing conditions and handle complex, multi-step processes.
Multimodal models, which process and generate multiple types of data including text, images and audio, feature prominently in the programme. For enterprises, multimodal capabilities open possibilities in customer service, document processing and operational monitoring that single-mode systems cannot address. The summit examines how these technologies translate from research demonstrations into production deployments within enterprise environments.
Autonomous workflows represent the practical application layer where these AI capabilities deliver operational value. The progression from assisted automation, where AI supports human workers, to autonomous systems that operate independently raises questions about governance, reliability and organisational change that the summit addresses through its panel discussions and case study presentations.
Data Architecture and Cloud Modernisation
Effective AI deployment depends fundamentally on underlying data infrastructure, a relationship the summit explores in depth. Many Indian enterprises operate with legacy data systems that were designed for traditional analytics workloads rather than the demands of modern AI applications. These systems often struggle with the volume, velocity and variety of data that AI models require for training and inference.
Cloud modernisation features as both an enabler and a challenge. While cloud platforms provide the computational resources and managed services that simplify AI deployment, migration from on-premises systems involves significant complexity. Data engineering practices, including pipeline development, quality management and governance frameworks, determine whether organisations can actually leverage their data assets for AI initiatives.
The summit addresses big data and analytics alongside emerging technologies including blockchain and Web3. While these technologies serve different purposes, they share common requirements around data management, security and integration with existing enterprise systems. Understanding these relationships helps technology leaders make coherent infrastructure investments rather than pursuing disconnected initiatives.
Measuring Return on Investment from AI Initiatives
One of the most persistent challenges facing enterprise AI programmes is demonstrating measurable business value. The summit dedicates significant attention to ROI measurement, recognising that many organisations have invested substantially in AI capabilities without establishing clear frameworks for evaluating outcomes. This gap between investment and demonstrated return creates pressure on technology leaders to justify continued spending.
The difficulty stems partly from the nature of AI benefits, which often manifest as productivity improvements, quality enhancements or risk reductions rather than direct revenue generation. Customer service applications may reduce handling times and improve satisfaction scores, but translating these operational metrics into financial terms requires careful analysis. Development and operations improvements similarly deliver value through efficiency gains that compound over time rather than producing immediate, easily quantified returns.
Expert perspectives at the summit address both measurement methodologies and organisational approaches to building business cases for AI investment. For technology leaders facing board-level scrutiny of AI spending, these discussions offer practical frameworks for articulating value in terms that resonate with business stakeholders.
Industry Context and Market Dynamics
The Indian enterprise technology market presents distinctive characteristics that shape AI adoption patterns. Rapid digital transformation across sectors including telecommunications, retail and IT services has created both opportunity and competitive pressure. Organisations that successfully operationalise AI capabilities gain advantages in customer experience, operational efficiency and product development that translate into market position.
IDC’s research indicates that AI spending in India is projected to outpace overall digital technology investment, reflecting strategic prioritisation by enterprise leaders. However, this aggregate growth masks significant variation in maturity levels across organisations and sectors. Some enterprises have progressed to production AI deployments delivering measurable outcomes, while others remain in experimental phases or struggle with foundational data challenges.
The summit provides a venue for organisations at different maturity levels to learn from peers who have navigated similar challenges. This knowledge transfer function proves particularly valuable given the relative novelty of enterprise AI at scale and the limited availability of documented best practices specific to Indian market conditions.
Who Should Attend
The summit targets senior technology and business leaders with responsibility for enterprise-wide strategy and investment decisions. Chief Information Officers and Chief Technology Officers represent the primary audience, alongside heads of IT, data and analytics leaders, and digital transformation executives. The content assumes familiarity with enterprise technology environments and focuses on strategic and operational considerations rather than technical implementation details.
Decision-makers from large enterprises, particularly those in telecommunications, retail and IT services sectors, will find the programme most directly relevant to their operational contexts. The networking opportunities provide value for leaders seeking to benchmark their approaches against peer organisations and establish relationships with technology partners and industry experts.
Organisations in earlier stages of AI adoption may benefit from exposure to more mature implementations, while those with established programmes can explore emerging capabilities in agentic AI and autonomous systems that represent the next phase of enterprise AI evolution.