Nearly 100 Indian companies use big data to develop artificial intelligence models

According to IANS, a partner of TV BRICS, in 2024, at least half of the data collected by Indian enterprises would be used to develop artificial intelligence models.

Data has become one of the most valuable resources of our time. With the development of the Internet and digital technologies, we generate and accumulate enormous amounts of information every day.

Experts clarify that big data machine learning (ML), sometimes referred to as learning AI on big data, is a technique for learning AI utilising massive volumes of data. With this approach, models and algorithms may adjust and get better with the accumulation of fresh data. The primary objective is to identify important patterns and knowledge from massive amounts of data so that more precise decision-making, complicated dependency recognition, and future event prediction are possible.

India is the global leader in artificial intelligence (AI) and cloud innovation, with 70 per cent of companies either implementing or intending to implement AI projects. Punit Gupta, Vice President, stated that it is therefore not unexpected that India is a global leader and that businesses are utilising AI to boost their IT programmes.

For this topic of study, interviews were conducted with over 1,000 IT executives from major global markets, such as the US, UK, France, Germany, Spain, Australia, New Zealand, Japan, Singapore, and India.

As to the survey, whereas 36 per cent of AI-developed countries have AI initiatives in place or in the pilot phase, 60 per cent of AI-leading countries do not. Approximately 87 per cent of Indian businesses have AI-ready IT spaces, and there are even AI-ready IT spaces in other nations where AI is still in its infancy.

According to experts, data organisations with the greatest possibilities of success are those that link and integrate huge structured and unstructured datasets into intelligent data infrastructure. Moreover, 53 per cent of Indian businesses stated that they were more likely to reduce or eliminate other IT-related tasks in order to make room for AI initiatives.

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