Accelerating the AI Revolution in India

In an exclusive interview with Industry Outlook magazine, AmitKumar Shrivastava, Head - AI Unit, Fujitsu India, shares his view on the scope of AI in India and offers his opinions on multifaced AI aspects. He is a public figure, a visionary and a thought leader in AI. He is recognized as a Global Fujitsu Distinguished Engineer, among 33 worldwide, and one of the 6 in AI. He also holds the prestigious title of Fujitsu Fellow, an honour bestowed upon only 18 individuals. 

Given your expertise in AI, how do you see the current trajectory of AI in India, and what are your views on the government initiatives addressing challenges and developments?

India is progressing well in AI, supported by the growing pool of AI talent. This growth is driven by the introduction of numerous AI-related certification programs, including Ph.D. diplomas and bachelor’s degrees offered by many IITs. These educational opportunities are increasing the number of AI specialists and fueling innovation in the field.

In my view, AI knowledge should be integrated at a school level, like in classes 6 or 7, and the framework for that is being worked out now. I was an Industry Advisor for the National Program on AI skilling Framework, and I worked in this direction and was Instrumental in developing Gen-AI standards, including National Occupational Standards (NOSs), micro-credentials, qualifications, and a curriculum tailored for AI for all, many, and few, spanning from students, professionals, and homemakers. Also, I am contributing to the AICTE initiative, developing specialized post-10th diploma courses to enhance youth employability in the country. This initiative will boost the talent pool, and jobs even further, and more solutions can be seen in the future, which will be brought forward by AI. 

The government is actively promoting and investing in AI, including AI missions, and establishing AI Centers of Excellence. The Prime Minister frequently discusses AI's challenges and opportunities, as evidenced in the G20 and GPAI summits and recently in discussions with Bill Gates. In GPAI, he proposed using AI to enhance agriculture, improve multilingual communication, integrate AI into governance, revive ancient languages like Sanskrit, and address deepfakes. This clearly recognized AI's potential and challenges at the leadership level.

Also, the Digital India Campaign aims to position India as a global Hub by emphasizing social and inclusive growth. The government has a strong sense of confidence that AI can support the country. This is evident from the initiatives we are seeing for AI in India.

As we discussed Indian government initiatives in Generative AI, we learned that they allocated 10,000 crores for INDIAai, which can potentially transform India's AI ecosystem. What are your thoughts on this?

The Government is creating a national occupational standard around AI, so they are serious about the potential of Gen-AI. It’s not just the domain experts that are talking about this, everyone is talking about this, it is now almost used everywhere. For example, developers are using Gen-AI to make themselves productive, healthcare professionals are also using this to improve diagnostic accuracy, personalize treatment plans, and streamline administrative processes.  

The recent investments in AI show that there is traction around this. Recognizing this, the government is actively supporting startups and upskilling initiatives to ensure India remains competitive in the global AI landscape.

Considering the projected CAGR of the global AI TAM through 2027, how should companies strategize their investments in AI to capitalize on this growth?

Firstly, companies should avoid the trap of FOMO and carefully select use cases that are crucial for their operations, planning with ROI in mind. Investing in talent and skill development is crucial, yet a common issue is that while many employees take AI courses, they often struggle to apply their knowledge to real projects. Organizations should focus on identifying relevant use cases first, and then tailor their training programs to these practical needs to enhance project delivery.

Start with a pilot project, leveraging cloud technology to easily access the necessary infrastructure. Establishing a center of excellence within the organization can foster a culture of innovation and set the stage for broader success.

Companies should collaborate with academia and engage in cross-industry partnerships. Today, working in isolation is no longer viable.

In what ways can companies leverage the Six-dimensional AI Acceleration Framework to enhance their AI capabilities and align with client expectations?

When we talk about six-dimensional AI, it is meant for Data, Algorithm, Compute/Infrastructure, Talent, business focus use cases, and responsible AI development.

Data is crucial in AI, but quality and diversity matter more than quantity for building generalized models. It's also important to manage changing or new data, and data privacy and security. Also, Incentivizing data owners and monetizing data can promote ethical usage and generate additional revenue streams for organizations.

For example, an autonomous car trained only in Pune's driving conditions excels locally but may falter in Chennai due to different traffic patterns and roads. This illustrates the need for diverse training data to create generalized AI models. Techniques like federated learning can enhance model robustness and address data privacy concerns by enabling collaborative, secure data usage across varied locations.

From an algorithmic perspective, we see breakthroughs almost every day in AI. This is exciting because it may even help you increase your productivity. With minimal AI knowledge, you can leverage open-source tools, cloud-based AI services, and low/no-code platforms, simplifying the use of advanced algorithms. Think about Generative AI; while a few players develop models from scratch, many are consuming it for customized solutions.

Computers have become more affordable partly due to cloud computing. Despite the rising demand for AI chips and the challenging to meet fully, cloud services offer access to high-performance computing, enabling individuals and businesses to use advanced AI without major investments in hardware. This shift democratizes access to AI tools and stimulates innovation across sectors by reducing the entry barrier to advanced technologies.

From talent, there is an urgent need to upskill employees, ideally through on-the-job training. Companies should encourage their employees to attend AI conferences to gain a deep and diverse understanding. Also, picking young leaders to bring fresh perspectives is crucial, breaking the traditional mindset. 

It is a must to identify the right problem for your business. Don’t get trapped into doing something to show yourself in this AI game. Remember that many AI projects never go to production. So, identify your business problem aligning with the need to use AI.

Finally, growing concerns around AI explainability, security, and safe deployment highlight the need for an AI governance team or office within organizations. This team would oversee AI development, enforce internal guidelines, and ensure transparency in processes that need customer visibility—without compromising confidentiality. Also, providing explainability reports for model decisions can play a big role in enhancing customer trust.

These six dimensions will not only help your organization grow but can help overall AI democratization.