The Artificial Intelligence (AI) and data analytics industry in India has been growing rapidly, with a strong focus on leveraging data-driven insights and machine learning for various applications. The country has also emerged as one of the leading countries in terms of AI and data analytics adoption, with a significant number of companies investing in India. 

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Several Indian companies have made significant strides in the domain and Data analytics company Tredence is no exception. The company has set its eyes on achieving the unicorn status by 2024. Pratap Daruka, Chief Financial Officer at Tredence stressed on diversifying the company's portfolio by introducing innovative service offerings. The company aims to reach previously uncharted sectors and broaden the client spectrum. "We have already incubated 2 new verticals this year: banking, financial services, and insurance (BFSI) and (Healthcare and Life Sciences) HLS. We are expanding globally, starting with Europe and Latin America, with more regions to follow. "We invest 10-12 per cent of our revenue in innovation," Daruka pointed. He further explained that India, historically a global IT powerhouse, has long been a leader in AI and data analytics growth and innovation. 

 

 

According to a report by NASSCOM, India’s AI industry was projected to grow at a CAGR of 30 per cent through 2025, positioning the nation as a crucial player in the global data and AI market. An uptick in the adoption of AI and data analytics can be observed across several sectors, from algorithms that predict consumer behavior in e-commerce to healthcare platforms that leverage AI for better diagnostics. 

Thanks to government support in initiatives such as the National Strategy for Artificial Intelligence, there's a clear roadmap for research, development, and subsequent adoption of AI-driven technologies. As an innovator for data, analytics, and AI research and development, India is helping to shape the future of global technology. 

Daruka opined that India's transformative journey in the AI and data analytics arena is shaped by demographic strength, historical expertise, and a significant consumer base. With more than half of its population under 25 years old, India boasts one of the world's largest pools of potential tech enthusiasts and professionals. 

India's IT sector, representing more than 50 per cent of the global IT services market, provides a robust foundation for AI training and development. Likewise, the vibrant Indian consumer landscape has emerged as a goldmine for data-driven insights. 

Furthermore, India's reputation for delivering high-quality technology solutions at competitive price points extends into AI and analytics. With revenues exceeding $3 billion and an impressive 30 per cent plus CAGR, the analytics industry underscores this trend. India is not only harnessing AI for local growth and innovation but is also establishing itself as a hub for global businesses seeking top-tier, cost-effective AI and data analytics solutions. 

Tredence operates across 10 offices in four countries, with more than 2,300 employees, 80 per cent of whom are based in India. The company focuses on a range of verticals, including Retail, CPG, Telecom, Travel, and manufacturing, providing innovative solutions to clients facing market disruptions.

India's fast-paced growth in the AI and data analytics world entails several formidable challenges, chiefly a pronounced skills gap. "This trend underscores the urgent need for enhanced specialized training in order for India to maintain its competitive edge in the global AI landscape. On the infrastructure front, particularly in rural regions, where over 65 per cent of the population resides, consistent and high-speed internet access is a serious issue. India is also grappling with data privacy and security concerns. While the Personal Data Protection Bill of 2019 was a step in the right direction, the practical implications and effectiveness of its provisions remain in a state of flux. Additionally, India's vast data pool, while a potential goldmine for analytics, is often fragmented. Disparate sources, varying standards, and integration challenges necessitate the adoption of rigorous data management practices to unlock the full potential of AI and data-driven insights," he added.