Artificial intelligence (AI) is becoming increasingly popular in India. We already have many tech-savvy young people in various areas of digital technology, both services and products. According to industry group Nasscom, more than 1.5 million engineers graduate every year. The IT industry alone directly employs approximately 5.5 million engineers. India is the second largest producer of digital data after China. Currently, it is the fifth largest economy in the world and one of the largest markets for any technology, both for business and customer applications. The country ranks as the largest market for almost all major technology companies. The Union government's Digital India initiative and his strong IndiaAI mission plan, combined with the semiconductor manufacturing thrust through the PLI scheme, have put key building blocks in place.
Private sector interest is also contributing to this momentum. Large companies have been experimenting with AI for years through pilot projects and limited deployments. With the advent of Generative AI (Gen AI) and its tangible benefits, Indian companies are once again looking to scale to deliver business value and gain competitive advantage. Some companies are building their AI strategies from scratch, while others are leveraging a single use case or application to improve efficiency, manage risk, and improve core experiences.
For example, a large non-banking financial company in India built a Gen AI agent to collectively analyze balance sheets and profit and loss (P&L) documents of potential borrowers. We also collect any available business information about the company and its field. Connect to the Internet to generate credit rating notes. Therefore, insurance companies can focus on decision-making rather than gathering information about small businesses. A leading retailer in India uses customized Gen AI agents to provide customers with a much more personalized experience than previous generations of rule-based AI. Another major retailer is leveraging AI to reduce front-line employee turnover.
As a professional services firm, we too have increasingly leveraged AI to provide a better experience for our clients. For example, by integrating AI into our vast tax knowledge repository, we will be able to provide more efficient and faster analysis to our clients.
What CEOs should consider before accelerating their AI strategy: Companies that have been digitally transforming for the past few years are now leveraging AI alongside their digital, cloud, and automation capabilities. People who were moving slowly will start to accelerate. He sees four elements as particularly important in this effort. The first is to identify the areas where technology will have the greatest impact and the highest ROI (return on investment). CEOs need to assess reliability and conduct rigorous cost-benefit analysis.
As we discussed in our recent report, India's AIdea: The potential of generative AI to accelerate India's digital transformation, the cost implications of full-scale AI deployment are significant, with large one-time investments and expenses , so there is little room for error. Recurring operating costs. CEOs and senior executives need to seriously experiment with different AI tools to understand the real challenges and opportunities. Don't be surprised if you discover a new direction for your organization and the industry as a whole.
Additionally, there are too many types of AI available today, both open-source and closed-source AI models. Organizations should also compare customizing off-the-shelf solutions versus building their own solutions.
The second factor to consider is that implementing AI at scale is more than just layering technology on top of existing IT systems. For best results, companies may need to restructure their current technology infrastructure and processes. In some cases, you may need to redesign your work processes based on an AI-first perspective. Legacy data as well as generated and captured data require special attention. Most large-scale AI foundational models can use both structured and unstructured data for training, but before organizations start using data for AI training, they must ensure that the data is clean, accurate, and above all We need to make sure there is no bias.
The third aspect is having the right AI governance structures in place. While policymakers create regulations globally, companies also need to build guardrails to prevent abuse by employees and outsiders. Ethical and responsible AI also requires checking for biases that can creep into the data or weights used in algorithms.
Regarding the human capital aspect, two patterns can be said to exist. First, there are mixed signals in some regions regarding the impact on employment. A balanced, pragmatic approach that combines the best of humans and technology is not only valuable, but also the most sustainable strategy. At the same time, Gen AI is creating talent shortages that are expected to worsen as more organizations embark on transformation journeys. The best way to address talent shortages and address the impact on employment is to retrain employees in AI skill sets. Companies may need to hire talent with natural language processing (NLP) and traditional AI/ML backgrounds and then provide targeted training.
The productivity benefits of large-scale AI adoption in the private sector, combined with new AI-based business opportunities and ecosystems, will truly boost India's economy and add to India's GDP every year for decades to come. It could increase by trillions of dollars. To make the most of the opportunities of AI, governments and the private sector must continue to work together. After all, AI has the potential to change lives and economies in the same way that electricity did two centuries ago. 
Rajiv Memani is Chairman and CEO of EY India.views are personal
