The integration of AI into the enterprise sector in India has advanced significantly, becoming a cornerstone for companies looking to raise product performance, streamline supply chains and reduce time to market.
Recent research highlights the growing operate of artificial intelligence in the Indian enterprise landscape. A study conducted by Morning Consult on behalf of IBM found that around 59% of enterprise-scale organizations in India are actively using AI in their operations. Moreover, the IBM Global AI Adoption Index 2023 report shows that early adopters are not only adopting AI, but also doubling down on investment, especially in areas key to future growth such as research and development and workforce reskilling.
The AI discussed here includes what is called classical, conventional, or discriminative AI, as opposed to the emerging wave of generative artificial intelligence (GenAI) introduced by OpenAI, especially through the development of ChatGPT.
In just two months since its December 2022 launch, ChatGPT has amassed over 100 million users. Today, OpenAI is valued at over $100 billion and has approximately 180.5 million users.
In comparison, it took the Internet 10 years to reach 500 million users, while mobile phones took six years. It could take just three years for ChatGPT to reach 500 million users, which would mean it would become a mainstream technology.
The main reason is that while conventional machine learning, an artificial intelligence technique, was largely narrow to observing and classifying patterns in content using predictive models, GenAI models rely on self-supervised learning (deep learning, which is also similar to machine learning) to pre-train on huge amounts of data and not only analyze the data, but also create up-to-date designs and propose ways to improve existing ones.
The result: today we have many so-called “Gigantic Daddy” technology AI models that include huge language models (LLM), huge multimodal models (LMM), and miniature language models (SLM) – GPT-4 and Sora OpenAI, Google’s Gemini, LLaMa Meta, Anthropic’s Claude-3, and Elon Musk’s Grok, to name a few.
India’s entry into the GenAI field is both ambitious and challenging, especially due to its luxurious linguistic diversity. With over 400 languages, the need for India-specific Huge Language Models (LLM) is of utmost importance. This imperative has become a focal point for local innovators, from tech giants to startups, that aim to transform conversational AI by shifting from rule-based chatbots to LLM-based models.
However, the journey is elaborate, marred by high computational costs and a paucity of comprehensive Indian datasets. Despite these obstacles, there is a concerted effort in the Indian technology ecosystem to overcome these challenges, leveraging GenAI for both commercial success and public good.
India is home to 113 unicorns across sectors with a combined valuation of over $350 billion. But it only has two AI unicorns – Fractal Anaytics and Krutrim, Ola Electric founder Bhavish Aggarwal’s India-based Krutrim is developing an India-based LLM, so is technically a GenAI unicorn.
Companies like Krutrim and Tech Mahindra claim to be building local LLMs from scratch. Sarvam AI said it will work with Indian enterprises to co-create domain-specific AI models on their data. It also hopes to leverage GenAI on top of the India Stack (Aadhaar, UPI, Account Aggregator, etc.) “specifically for public good applications.”
The Bengaluru-based Artificial Intelligence and Robotics Technology Park (ARTPARK) and the Indian Institute of Science are collaborating with Google India to launch an LLM called Project Vaani. CoRover has a BharatGPT, while the Bharat GPT program (comprising seven IITs, two IIITs and healthcare company Vizzhy) is building Hanooman series.
India’s AI ambitions are set in the context of global competition and cooperation. While the US and China lead the AI race in terms of investment and innovation, India is carving out a niche for itself by focusing on areas where it can make a significant impact. The Government of India’s allocation of approximately $1.1 billion towards AI policy signifies a powerful commitment to nurturing an AI ecosystem that can propel the nation forward.
These intentions are on point, considering that by the end of 2024, according to Gartner, approximately 40% of enterprise applications will include GenAI. The key factors driving this adoption in India include the availability of AI tools, the need for cost reduction and automation, and the integration of AI with easily accessible business applications.
India’s AI trajectory mirrors the global trend towards deeper, more integrated technology innovation. However, it also highlights a path specifically tailored to India’s strengths and challenges.
