The Rise of Generative AI in India: Leading the Way in Technological Advancements

There's no denying that Generative Artificial Intelligence (GenAI) has become a mainstream technological phenomenon. India is at the forefront of this trend, surpassing the global average in AI adoption. With a remarkable 57% of Indian companies actively using AI, India is leading the way in embracing generative AI technologies. In this article, we will explore the impact of AI adoption in Indian organizations and the essential role of data infrastructure in preparing for long-term generative AI adoption.

The Growing Adoption of Generative AI in India

Discover how Indian companies are actively embracing generative AI technologies and surpassing the global average in AI adoption.

India is leading the way in the adoption of generative AI technologies, with approximately 57% of Indian companies actively using AI, surpassing markets like Australia, the US, and the UK.

Indian startups are also proactively investing in generative AI ventures, with over $475 million committed between 2021 and 2023. This growing adoption of generative AI in India showcases the country's commitment to leveraging advanced technologies for innovation and growth.

The Importance of Data Infrastructure for AI Readiness

Explore the significance of building capable data and technology infrastructure to prepare for long-term generative AI adoption.

Organizations must recognize that the quality of insights obtained from generative AI directly depends on the quality of data employed. Building a capable data infrastructure is crucial for long-term generative AI adoption.

This entails developing access to high-quality, well-coordinated data, supporting scalable data architectures, and implementing governance and security measures. Leading organizations understand that a trusted data foundation is essential to fuel insights and advanced use cases where the power of generative AI and traditional AI come to life.

The Role of Data Governance in Responsible AI Usage

Learn how data governance frameworks and lineage solutions enable responsible and effective use of data in the context of generative AI.

A robust data governance framework is essential for the responsible and effective use of data, particularly in the context of large language models used in generative AI. Businesses can streamline this process by utilizing catalog and lineage solutions, which automatically identify and document relationships between datasets.

Furthermore, AI systems benefit from access to a broad spectrum of intelligence by aggregating data from diverse sources and integrating it into a centralized warehouse or data lake. This integration allows AI models to uncover valuable insights, identify patterns, and make informed predictions.

The Power of Hybrid AI Approaches

Discover how combining generative AI with traditional AI can scale the impact of AI across organizations.

While generative AI is gaining traction, traditional AI still brings ongoing value in areas like predictive analytics. Organizations are now looking to adopt a hybrid approach that incorporates generative AI with traditional AI to scale its impact across their operations.

By combining the power of both approaches, organizations can unlock deeper insights, find new ways to solve problems, and drive innovation at a faster pace. This hybrid AI approach democratizes AI capabilities, making them accessible to a larger population within the organization.