India needs robust datasets to progress towards agentic future: EY Report

• Data 4.0 marks a major leap forward by treating data as a central, strategic asset essential for digital transformation.
• GenAI advancement relies on sophisticated algorithms and vast amounts of high-quality enterprise data. 

New Delhi, 24 September 2024: India is on the cusp of an AI-driven revolution, but its success depends on building a robust data ecosystem that can support the growing demands of AI. As per the latest EY report, ‘Data 4.0: Making your data AI-ready’, high-quality, trustworthy data forms the backbone of AI-driven innovations. Without data maturity, the prototyping, deployment, and effective testing of GenAI or any type of analytics become very challenging.

Sharing his thoughts, Alexy Thomas, Technology Consulting Partner, EY India, said “For India to realize its full potential as a global leader in AI innovation, we must prioritize building a robust data foundation. Data is the backbone that will enable AI systems to drive efficiency, economic growth, and transformative change across industries. By investing in data readiness today, we are not just advancing technology we are fueling the future growth of our nation."

Indian organizations are still in low data maturity. To harness the full potential GenAI applications, businesses must effectively adopt a strategic approach to balancing technology, people, and processes. Without structured datasets, the output of AI models can be flawed, leading to inaccuracies in decision-making, inefficiencies in operations, and missed opportunities for growth. 

As India prepares for an ‘agentic future’ where AI systems grow increasingly autonomous, the quality, quantity, and accessibility of datasets will define the nation's AI success. For AI agents to deliver reliable and valuable insights, they need access to well-organized, accurate, and timely data.

Whitepaper outlines several critical measures Indian organizations should adopt to prepare their data for agentic AI systems:

Implementing Modern Data Infrastructure: Building flexible, scalable, and secure data systems that can handle the complexity and volume of data required for AI systems to function autonomously.

Establishing Unified Data Access: Creating a unified data fabric, supported by a trusted data catalog, that provides seamless access to data across different platforms and ensures that AI agents can retrieve relevant information quickly and efficiently.

AI-Driven Data Governance: Automating data governance processes through AI-powered tools to ensure that data quality, compliance, and privacy are maintained across the enterprise. This step is crucial in preventing data breaches and regulatory non-compliance.

Leveraging AI for Data Management: AI will not only be the consumer of data but also the tool for managing and governing data. Automating data cataloging, metadata management, and quality assurance will streamline the process of preparing data for AI applications.

GenAI relies on a strong foundation of data maturity, which involves an organization excelling in both integrating data through processes like moving and transforming it and managing its governance. As the country moves towards a future dominated by AI agents and autonomous systems, the importance of AI-ready data cannot be overstated. With the right investments and strategies, India has the potential to lead the world in AI innovation, driving economic growth and transforming industries across the board.

Notes to Editors

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