By Sajeev Viswanathan, Founder & CEO, New Street Tech
AI is becoming a bigger part of how businesses operate. With 87% of enterprises actively using AI solutions and the country’s AI skill penetration reported at 2.5 times the global average, adoption is growing quickly. Yet India’s situation is different from ageing economies facing labour shortages. With a large young workforce and deep expertise across services and knowledge industries, we need to think beyond automation and focus on how AI can expand the contribution of people across the economy.
This calls for a different way of thinking about AI-led productivity. Instead of viewing AI primarily as a substitute for human labour, India can use it to multiply human capability. This is the thinking behind JAI, or Janata-AI, India’s Human-AI Collaboration Framework. Its central principle is that AI must multiply the value of people, not minimise the need for them. JAI brings machine intelligence together with human judgement, creativity, empathy and domain expertise to create stronger outcomes than either humans or AI could achieve independently.
Such an approach can help preserve employment and accelerate productivity, while also allowing the country to monetise its vast repository of process knowledge and behavioural intelligence. The aim is to build on the strengths of people and technology together and establish India as a global leader in collaborative AI.
The important next step is to make this approach measurable. This is where the JAI Index becomes central. Rather than evaluating AI initiatives only by efficiency, automation or cost savings, the Index can assess whether these efforts create broader economic and social value. It proposes five measurable dimensions that can help determine whether an AI initiative is contributing to our larger development goals.
J1, Human Value Addition, asks whether AI augments rather than replaces human capability. This is fundamental to the JAI approach. AI can take on repetitive or data-intensive tasks while people continue to contribute judgement, creativity, empathy and contextual understanding. The objective is not to prevent automation, but to ensure that technology expands what people are capable of doing.
J2, Employment Multiplier, looks beyond immediate job numbers to examine whether AI creates new jobs, skills and income opportunities. An AI system that improves productivity can create additional capacity for businesses to serve more customers, enter new markets or develop new products. Measuring these wider opportunities can provide a more complete picture of AI’s impact on employment.
J3, Indian Knowledge Contribution, focuses on whether AI initiatives leverage India’s domain expertise, process knowledge and data assets. We have built significant knowledge across technology, financial services, healthcare, consulting and business processes. AI can help capture, enhance and scale this expertise, creating solutions that are rooted in Indian experience and capable of addressing global needs.
J4, Global Competitiveness, asks whether AI initiatives can create exportable, industry-specific AI solutions from India. This shifts the conversation from India being a large consumer of AI to becoming a creator of AI-enabled products, services and intellectual capital for global markets. A combination of technical talent, domain expertise and scale can provide a strong foundation for this ambition.
J5, Inclusive Impact, considers whether AI promotes accessibility, trust, ethical practices and broad-based societal benefit. As AI becomes embedded in areas that affect everyday lives, its value cannot be measured only through productivity gains. Access, trust and responsible deployment will also determine whether the benefits of AI reach a wider section of society.
Together, these five dimensions create a framework for assessing AI initiatives through an Indian lens. The Index could also be linked to government incentives, public procurement and regulatory support, encouraging investment in AI systems that create broader economic and social value.
The goal is not to hold back automation, but to make its gains more productive. As AI takes on repetitive tasks and improves efficiency, businesses can use the resulting capacity to expand, enter new markets and create new opportunities. At the same time, workers can move towards roles that rely more on judgement, creativity and specialised knowledge, making skilling an important part of the transition.
The larger opportunity is to turn our demographic scale into an AI advantage. While leading AI economies compete to build increasingly intelligent machines, the country can develop a model centred on Collaborative Intelligence, where human capability and machine intelligence reinforce each other. JAI can provide a framework for making that model measurable, inclusive and globally relevant.
For the country, the future of AI-led productivity need not be defined by how much work machines can take away from people. It can be defined by how much more people can accomplish with machines. By measuring AI through human value, employment, knowledge, global competitiveness and inclusion, the JAI Index can help India build an AI economy that is more innovative, inclusive and globally competitive.