The Gartner Data & Analytics Summit 2026 in Mumbai is bringing together data, analytics, and technology leaders as businesses look for practical ways to create value from artificial intelligence. Day 2 of the event on September 22 focuses on several issues shaping the modern data ecosystem, including AI ready data, unstructured information, data governance, and agentic AI.
The conference theme, Value at AI Velocity, reflects the growing pressure on organizations to deliver measurable business value while managing technology risks and costs. Consequently, data strategy is becoming closely connected with broader digital transformation and enterprise AI planning.
AI Readiness Depends on Better Data
One of the major themes from Gartner Data and Analytics Summit 2026 India Day 2 is that successful AI initiatives require organizations to strengthen their data foundations. Gartner highlighted the importance of preparing structured and unstructured information so that AI systems can access useful and trustworthy context.
This development is particularly important as enterprises move beyond traditional analytics toward generative AI and agentic AI. Instead of treating data management as a background IT activity, organizations increasingly need to view it as a strategic part of technology planning.
Unstructured Data Gains Greater Importance
Businesses generate enormous amounts of information through documents, emails, images, reports, conversations, and other sources. Much of this information does not fit neatly into traditional databases. However, it can contain valuable business context for AI systems.
Gartner highlighted workflows involving entity extraction, vector data embeddings, semantic data enrichment, and structured data pipelines as important elements of AI ready data management. The research firm also said that data management leaders need to bring structured and unstructured data practices closer together.
As a result, unstructured data is becoming an increasingly important part of enterprise Technology insights and the wider IT industry news landscape.
Data Governance Becomes an AI Priority
Data governance is another central issue emerging from the summit. Gartner has predicted that 60 percent of organizations that ignore data governance culture challenges will fail to govern AI successfully by 2027.
The finding highlights an important shift. AI governance cannot exist independently from data governance because AI systems depend on the quality, accessibility, security, and context of the information they use.
Therefore, enterprises need governance practices that cover data management as well as AI models and automated systems. This approach can help organizations balance innovation with security, accountability, and responsible technology use.
Agentic AI Changes Data Management
Meanwhile, agentic AI is creating another major change across the data and analytics ecosystem. AI agents are designed to perform tasks and support decision making with greater autonomy than traditional software applications.
Gartner’s Mumbai conference agenda includes discussions around AI agent risks, AI engineering, data engineering, and the development of context layers for reliable AI agents. These sessions demonstrate how data architecture and AI capabilities are becoming increasingly interconnected.
Consequently, organizations adopting agentic AI will need more than powerful AI models. They will also require reliable data pipelines, appropriate governance, strong context, and effective monitoring.
Data Strategy Is Spreading Across Business Functions
The developments discussed at Gartner Data and Analytics Summit 2026 India have implications beyond IT departments. Finance teams can use trusted data foundations for forecasting and analytics, while Finance industry updates increasingly reflect the growing role of AI in financial operations.
Similarly, sales teams can use analytics to understand customer behavior and support Sales strategies and research. Marketing departments can apply customer data to personalization and campaign measurement, strengthening Marketing trends analysis.
HR teams are also becoming increasingly data driven as organizations use technology for workforce planning and employee insights. This connects enterprise data strategies with changing HR trends and insights.
From Data Management to Business Value
A recurring message from the summit is that technology investments should ultimately create measurable business value. Gartner’s conference theme emphasizes the need for organizations to move quickly while maintaining an appropriate balance between innovation, risk, and cost.
Moreover, Gartner sessions are examining how organizations can move AI beyond productivity improvements toward innovation, new business models, and enhanced experiences.
This means data leaders are increasingly expected to work closely with business teams. The role of data and analytics is evolving from reporting and infrastructure management toward strategic decision support.
Practical Insights for the Evolving IT Ecosystem
Gartner Data and Analytics Summit 2026 India Day 2 demonstrates how closely data management, AI, governance, and digital transformation are now connected. Organizations preparing for the next stage of enterprise AI will need to pay attention to both structured and unstructured data while developing governance practices that can scale with increasingly autonomous technologies.
The broader lesson is that AI readiness starts with strong data foundations. As enterprises explore generative AI and agentic AI, reliable information, effective governance, semantic context, and responsible technology practices will become increasingly important.
For technology professionals, these developments provide valuable insight into where the IT ecosystem is heading. The combination of better data management and responsible AI adoption can help organizations turn emerging technology into practical business value.
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Source : gartner.com
