(Commonwealth_ Artificial Intelligence (AI) is no longer a futuristic concept; it’s a reality that’s already transforming industries and societies across the globe. With the rapid advancements in AI technology, businesses are unlocking new avenues for productivity, creativity, and innovation. The impact is especially profound in countries like India, where AI presents a unique opportunity to reshape its economy, society, and public services. As we move toward 2038, AI could add up to US $675 billion to India’s economy, with sectors like IT, healthcare, and manufacturing set to experience the biggest productivity boosts.
However, despite these tremendous opportunities, the actualization of AI’s full potential presents several challenges. The path to scaling AI solutions is complex, and while organizations are eager to implement AI, the execution often falls short. According to Gartner, an estimated 30% of generative AI (GenAI) projects are likely to be abandoned after the proof-of-concept (POC) phase due to factors such as poor data quality, lack of proper risk controls, and escalating costs. Furthermore, many companies struggle to implement AI projects in ways that align with their real business objectives, resulting in limited tangible outcomes.
1. Localized AI Development: The Need for Inclusivity
For AI to truly benefit India, its development must be localized to address the country’s unique needs and challenges. India is a nation of remarkable diversity, with hundreds of languages, cultures, and socioeconomic factors that influence daily life. AI solutions must reflect this diversity in order to be impactful and relevant. Currently, only a small fraction of the training data used in large language models (LLMs) comes from languages commonly spoken in India. For instance, Hindi, the most widely spoken language in India, accounts for only 0.1% of the LLM training data, hindering the effectiveness of AI systems in regions where this language is predominant.
Adopting a sovereign approach to AI, which involves training models on local data and infrastructure, has the potential to generate more relevant solutions. Localized AI strategies meet the needs of local communities by addressing healthcare challenges, improving education access, and enhancing agricultural productivity. Additionally, it enables more personalized AI applications that can understand and respond to the regional nuances in language, culture, and behavior.
2. Robust Infrastructure Investment: Building the Foundation for AI
The success of AI depends on a strong and reliable technological infrastructure. AI requires access to vast amounts of data, robust computing power, and high-speed networks, all of which form the backbone of AI solutions. However, India’s current infrastructure remains a challenge, with many regions lacking reliable internet connectivity, advanced data centers, and computing power necessary to process large datasets.
Investing in infrastructure such as high-performance computing resources, data storage facilities, and fast, secure networks is crucial for enabling AI scalability. The government and private sector must collaborate to build the digital foundation required for AI deployment, ensuring that even rural and underserved areas can access AI technologies. A strong infrastructure will also ensure that AI systems are resilient, secure, and capable of meeting the growing demands of data-driven applications.
3. Flexibility through open, modular architecture
A key factor in the success of AI initiatives lies in adopting an open, modular IT architecture. AI is a rapidly evolving field, and as such, organizations need to be able to adapt quickly to new technologies, tools, and systems. By using open and modular architectures, businesses can build AI systems that are more flexible, scalable, and resilient.
This approach allows organizations to integrate new technologies without overhauling their entire IT infrastructure, providing greater agility and flexibility in responding to changing market conditions. Open, modular architectures also encourage collaboration and innovation, enabling organizations to leverage existing resources and tools while minimizing costs and complexity.
4. A broad, open AI ecosystem drives innovation and growth.
A broad, open AI ecosystem is key to fostering innovation and growth in India’s AI sector. Open ecosystems, where businesses and developers have access to a wide range of AI tools, frameworks, and applications, are essential for accelerating the development and deployment of AI solutions. Such ecosystems allow startups, universities, research institutions, and large enterprises to collaborate and share resources, thereby spurring innovation.
