India's next AI revolution may not begin in Bengaluru's tech parks, but in neighbourhood shops, small factories and kitchens.
Why the real test of artificial intelligence in India is not how many jobs it replaces, but how many new entrepreneurs it helps create.
India's debate on artificial intelligence (AI) often begins with two concerns: how many jobs will disappear and how much productivity will improve. But there is another question worth asking. Who will get the opportunity to use AI to build something new?
In a recent column published in a national daily, Ravi Venkatesan makes the case that India's next generation of AI-driven entrepreneurs may not emerge from Silicon Valley or Bengaluru. They could come from neighbourhood shops, small factories, food-processing units and local businesses across the country.
His argument shifts the focus from technology companies and highly qualified professionals to people who understand everyday business problems but have never had access to the expertise needed to solve them.
The Two Questions Everyone Asks
Most public discussion about AI revolves around two concerns. The first is employment: how many jobs will machines take over? The second is productivity: how much will AI increase economic output?
Both questions matter. But Venkatesan raises a third question that receives far less attention. How can AI help solve India's persistent problems in healthcare, credit, agriculture, education and small-scale commerce? More importantly, who will get direct access to this technology?
These are not abstract concerns. Many of India's everyday economic and social problems have remained unresolved for years. One reason is that the people who understand these problems most closely have rarely possessed the technical, financial or professional resources to develop solutions.
AI could change that equation.
Who Decides What Gets Built?
Venkatesan's argument draws on a column by Wall Street Journal writer Kimberley Strassel, who examined Silicon Valley's enthusiasm for what is often described as "AI abundance".
Strassel raised a question that goes beyond how the gains from AI should be distributed. She asked who decides which problems deserve attention in the first place.
Her argument was that entrepreneurs tend to build products for people whose lives and experiences resemble their own. Research cited in this debate suggests that female entrepreneurs create products with an 18 per cent higher share of female customers than their male counterparts. Similarly, founders from wealthier backgrounds are more likely to understand and address the needs of high-income consumers.
The venture capital industry calls this founder-market fit. The idea is straightforward: entrepreneurs are often better at identifying problems in markets they know personally.
Strassel illustrated the point through her experience teaching a course on building businesses around social problems. In nearly a decade, she had not seen a student propose a solution for Medicaid or the reintegration of former prison inmates. Yet students regularly came up with ideas such as apps for delivering cookies at three in the morning.
The contrast highlights a basic problem. When entrepreneurs have limited exposure to the everyday challenges faced by certain communities, those challenges are less likely to become business opportunities.
India's Missing Entrepreneurs Are Already Here
Venkatesan argues that India faces the same problem on a much larger scale.
A significant part of India's start-up ecosystem is concentrated among people with access to elite educational institutions, professional networks and investment capital. Graduates of the IITs and IIMs have contributed substantially to the country's technology and business sectors. However, their experiences do not necessarily reflect the realities of India's smaller towns, informal markets and neighbourhood enterprises.
Consider a woman running a small food-processing business. She understands her customers, knows when demand rises and falls, and has a practical sense of what her competitors are selling. But she may not have access to a business analyst who can study her sales records or help her identify opportunities for expansion.
A graduate in Nagpur or Visakhapatnam may understand the local economy better than a consultant brought in from Bengaluru. A small manufacturer may know exactly why customers prefer one product over another but lack the expertise to convert that knowledge into a growth strategy.
These people are not short of ideas or market understanding. What they lack is access to professional and technical capabilities.
That is where AI could make a difference.
How AI Can Bridge the Expertise Gap
Venkatesan's central argument is that AI does more than make existing experts productive. It can also help people work around the absence of experts.
A small business owner can use AI tools to examine sales records, understand customer preferences, study competitors and identify products with growth potential. The same technology can help create a website, prepare marketing material, draft a business proposal or organise information for a loan application.
Similarly, an unemployed graduate in a smaller town with a business idea can use AI to research the local market, understand potential customers and develop an initial business model without hiring a team of specialists.
These tools do not guarantee business success. Entrepreneurs still need market knowledge, financial discipline, customer trust and the ability to make sound decisions. AI-generated information also needs verification.
But the cost of getting started could fall considerably.
For an economy where local knowledge is widely available but professional expertise remains difficult to access, this is an important change. AI can make capabilities that were once expensive or difficult to obtain more accessible to ordinary entrepreneurs.
India Does Not Need to Search for Its Next Founders
Strassel suggests that American venture capital firms should look beyond their familiar networks and identify entrepreneurs whose ideas have been overlooked.
Venkatesan makes a different observation about India. The country does not necessarily need to search for these founders. Many are already running shops, managing small manufacturing units, driving auto-rickshaws, operating food businesses and maintaining accounts for family enterprises.
They understand the problems around them because they deal with them every day.
What they need is the ability to turn that understanding into practical solutions.
This also changes how India should measure the success of its AI ambitions. Counting the number of people trained to use AI applications may offer some indication of adoption, but it does not tell us whether the technology is creating economic opportunities.
A more meaningful assessment would examine how many new businesses are being established, how many existing enterprises are expanding, whether small businesses are becoming more efficient and how quickly entrepreneurs can test and develop new ideas.
Venkatesan describes this as entrepreneurial velocity.
It is a useful way of looking at AI because it connects technological adoption with measurable economic activity rather than simply counting users or applications.
The Real Test of India's AI Ambition
The central question is not simply how India will distribute the economic gains generated by artificial intelligence. It is also about who will have the power and capability to decide what gets built with it.
If AI remains largely in the hands of big corporations, technology professionals and well-funded start-ups, its benefits may follow existing patterns of economic concentration.
But if small entrepreneurs, underemployed graduates, local manufacturers and frontline workers can use these tools effectively, the impact could reach much further.
There is a difference between giving people access to an AI application and enabling them to use it to solve a problem that affects their livelihood. The latter requires affordable technology, reliable digital infrastructure, access to finance, practical training and an environment where small businesses can experiment without facing unnecessary barriers.
India's AI story should therefore not be measured only by the size of its technology companies, the number of engineers it produces or the investments flowing into its start-up ecosystem.
It should also be measured by what happens in its smaller towns, local markets, workshops and kitchens.
The next successful AI entrepreneur may not have an IIT degree or a venture capital connection. She may already be running a small business and looking for a better way to manage it.
India does not lack people who understand its problems. It needs to make the tools of innovation accessible to them. That could be one of the most meaningful contributions artificial intelligence makes to the country's economic future.
Why the real test of artificial intelligence in India is not how many jobs it replaces, but how many new entrepreneurs it helps create.
India's debate on artificial intelligence (AI) often begins with two concerns: how many jobs will disappear and how much productivity will improve. But there is another question worth asking. Who will get the opportunity to use AI to build something new?
In a recent column published in a national daily, Ravi Venkatesan makes the case that India's next generation of AI-driven entrepreneurs may not emerge from Silicon Valley or Bengaluru. They could come from neighbourhood shops, small factories, food-processing units and local businesses across the country.
His argument shifts the focus from technology companies and highly qualified professionals to people who understand everyday business problems but have never had access to the expertise needed to solve them.
The Two Questions Everyone Asks
Most public discussion about AI revolves around two concerns. The first is employment: how many jobs will machines take over? The second is productivity: how much will AI increase economic output?
Both questions matter. But Venkatesan raises a third question that receives far less attention. How can AI help solve India's persistent problems in healthcare, credit, agriculture, education and small-scale commerce? More importantly, who will get direct access to this technology?
These are not abstract concerns. Many of India's everyday economic and social problems have remained unresolved for years. One reason is that the people who understand these problems most closely have rarely possessed the technical, financial or professional resources to develop solutions.
AI could change that equation.
Who Decides What Gets Built?
Venkatesan's argument draws on a column by Wall Street Journal writer Kimberley Strassel, who examined Silicon Valley's enthusiasm for what is often described as "AI abundance".
Strassel raised a question that goes beyond how the gains from AI should be distributed. She asked who decides which problems deserve attention in the first place.
Her argument was that entrepreneurs tend to build products for people whose lives and experiences resemble their own. Research cited in this debate suggests that female entrepreneurs create products with an 18 per cent higher share of female customers than their male counterparts. Similarly, founders from wealthier backgrounds are more likely to understand and address the needs of high-income consumers.
The venture capital industry calls this founder-market fit. The idea is straightforward: entrepreneurs are often better at identifying problems in markets they know personally.
Strassel illustrated the point through her experience teaching a course on building businesses around social problems. In nearly a decade, she had not seen a student propose a solution for Medicaid or the reintegration of former prison inmates. Yet students regularly came up with ideas such as apps for delivering cookies at three in the morning.
The contrast highlights a basic problem. When entrepreneurs have limited exposure to the everyday challenges faced by certain communities, those challenges are less likely to become business opportunities.
India's Missing Entrepreneurs Are Already Here
Venkatesan argues that India faces the same problem on a much larger scale.
A significant part of India's start-up ecosystem is concentrated among people with access to elite educational institutions, professional networks and investment capital. Graduates of the IITs and IIMs have contributed substantially to the country's technology and business sectors. However, their experiences do not necessarily reflect the realities of India's smaller towns, informal markets and neighbourhood enterprises.
Consider a woman running a small food-processing business. She understands her customers, knows when demand rises and falls, and has a practical sense of what her competitors are selling. But she may not have access to a business analyst who can study her sales records or help her identify opportunities for expansion.
A graduate in Nagpur or Visakhapatnam may understand the local economy better than a consultant brought in from Bengaluru. A small manufacturer may know exactly why customers prefer one product over another but lack the expertise to convert that knowledge into a growth strategy.
These people are not short of ideas or market understanding. What they lack is access to professional and technical capabilities.
That is where AI could make a difference.
How AI Can Bridge the Expertise Gap
Venkatesan's central argument is that AI does more than make existing experts productive. It can also help people work around the absence of experts.
A small business owner can use AI tools to examine sales records, understand customer preferences, study competitors and identify products with growth potential. The same technology can help create a website, prepare marketing material, draft a business proposal or organise information for a loan application.
Similarly, an unemployed graduate in a smaller town with a business idea can use AI to research the local market, understand potential customers and develop an initial business model without hiring a team of specialists.
These tools do not guarantee business success. Entrepreneurs still need market knowledge, financial discipline, customer trust and the ability to make sound decisions. AI-generated information also needs verification.
But the cost of getting started could fall considerably.
For an economy where local knowledge is widely available but professional expertise remains difficult to access, this is an important change. AI can make capabilities that were once expensive or difficult to obtain more accessible to ordinary entrepreneurs.
India Does Not Need to Search for Its Next Founders
Strassel suggests that American venture capital firms should look beyond their familiar networks and identify entrepreneurs whose ideas have been overlooked.
Venkatesan makes a different observation about India. The country does not necessarily need to search for these founders. Many are already running shops, managing small manufacturing units, driving auto-rickshaws, operating food businesses and maintaining accounts for family enterprises.
They understand the problems around them because they deal with them every day.
What they need is the ability to turn that understanding into practical solutions.
This also changes how India should measure the success of its AI ambitions. Counting the number of people trained to use AI applications may offer some indication of adoption, but it does not tell us whether the technology is creating economic opportunities.
A more meaningful assessment would examine how many new businesses are being established, how many existing enterprises are expanding, whether small businesses are becoming more efficient and how quickly entrepreneurs can test and develop new ideas.
Venkatesan describes this as entrepreneurial velocity.
It is a useful way of looking at AI because it connects technological adoption with measurable economic activity rather than simply counting users or applications.
The Real Test of India's AI Ambition
The central question is not simply how India will distribute the economic gains generated by artificial intelligence. It is also about who will have the power and capability to decide what gets built with it.
If AI remains largely in the hands of big corporations, technology professionals and well-funded start-ups, its benefits may follow existing patterns of economic concentration.
But if small entrepreneurs, underemployed graduates, local manufacturers and frontline workers can use these tools effectively, the impact could reach much further.
There is a difference between giving people access to an AI application and enabling them to use it to solve a problem that affects their livelihood. The latter requires affordable technology, reliable digital infrastructure, access to finance, practical training and an environment where small businesses can experiment without facing unnecessary barriers.
India's AI story should therefore not be measured only by the size of its technology companies, the number of engineers it produces or the investments flowing into its start-up ecosystem.
It should also be measured by what happens in its smaller towns, local markets, workshops and kitchens.
The next successful AI entrepreneur may not have an IIT degree or a venture capital connection. She may already be running a small business and looking for a better way to manage it.
India does not lack people who understand its problems. It needs to make the tools of innovation accessible to them. That could be one of the most meaningful contributions artificial intelligence makes to the country's economic future.
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