Why donors keep asking for sustainability

October 26, 2026 Leave a comment

I have often been asked by the funding partners, ‘How will this project be sustained after the funding ends?’ While it is a reasonable question, it is also often the wrong one. The development sector has turned ‘sustainability’ into a synonym for ‘what will happen when the donor stops paying?’ The donors ask NGOs to build lasting solutions while often funding them through short-term, restricted projects that make long-term institutional and financial resilience harder to achieve. The real test of sustainability is the possibility of value created by the funding that can continue beyond the project cycle, and whether the economic, institutional or public systems exist to carry that value forward.

If a donor spends money on training women entrepreneurs, establishing community institutions, improving health services or creating livelihood opportunities, it is entirely reasonable to ask what happens when the grant ends. Nobody wants an intervention to disappear the moment the donor’s logo disappears from the last banner. But before asking how a project will survive without the donor, we should ask what exactly is supposed to continue, who is expected to take responsibility for it, and whether the conditions exist to make that possible.

A three-year project can be financially unsustainable but socially transformative, and it can end because its purpose has been achieved. A community institution can survive without the NGO but require continued public or market support. A livelihood intervention can become sustainable because participants increase their incomes, while the organisation delivering it remains dependent on philanthropy. And sometimes ‘sustainability’ simply means that the NGO promises to find another donor, which often is the least convincing of all. For years, development organisations have been encouraged to think about sustainability as an exit strategy. The donor funds the intervention often for 1-3 years, the NGO builds capacity, creates local ownership, establishes linkages and prepares an exit plan, and then the donor leaves and the model is expected to continue. While the logic is attractive, ending external funding and creating sustainability are not necessarily the same thing.

The OECD’s longstanding definition of sustainability in development evaluation focuses on the benefits of an intervention continuing after donor funding ends. That is a useful starting point, but it immediately raises a more important question of what will allow those benefits to continue? Government may take over, communities may contribute, users may pay, markets may generate revenue, or another institution may assume responsibility. Or the intervention may change behaviour or strengthen systems sufficiently that continued external support is no longer necessary. These are fundamentally different pathways, yet grant proposals often treat sustainability as a generic quality that can be added through a paragraph near the end of a concept note.

Consider a women’s entrepreneurship program that trains 5,000 rural women, organises producer collectives, provides business support and connects them to markets. If a donor asks how the program will be sustained after three years, the answer depends entirely on the model. Perhaps producer collectives will become commercially viable, or an anchor company will continue purchasing from the enterprises, while the financial institutions in the entrepreneurial ecosystem will provide working capital, and women will eventually pay for business services. Each possibility requires a different intervention design. If sustainability depends on markets, the project must build a viable market proposition. If it depends on government, public institutions need to be involved from the beginning. If it depends on producer collectives, those organisations need governance, capital and commercial capability. If another donor will be required, the project should be honest about that rather than presenting donor substitution as financial sustainability.

Donors increasingly expect NGOs to be resilient, adaptive and financially sustainable, while many NGOs are funded through short-term, restricted project grants that make precisely that difficult. Recent evidence from Bridgespan’s 2025 research, based on responses from 460 nonprofits and interviews with 51 nonprofit leaders, funders and intermediaries from India, found growing movement towards multiyear funding and greater recognition of core organisational costs, but continuing gaps in organisational development and financial reserves, particularly among smaller and non-metro organisations. Earlier Bridgespan research found that 83% of Indian NGOs surveyed had difficulty securing funding for indirect costs, while more than half had fewer than three months of reserves. Only 18% said they invested adequately in organisational development. Another analysis of 40 relatively well-funded Indian nonprofits found that actual core costs ranged from 5% to 51% of total costs and averaged 19%, while the average coverage provided by key donors was only 9%.

Funders ask organisations to be resilient while funding them as if their only legitimate expenditure is the activity that can be photographed and counted. Donor grants fund the field worker but not always enough of the management system that supports the field worker, training but not necessarily the organisational learning required to improve it, and program delivery while hesitating to fund reserves. Funders ask NGOs to diversify their funding while providing little unrestricted money with which to build their fundraising capacity. Then, three years later, the funder asks why NGOs are not sustainable.

Instead of asking an NGO, ‘How will you sustain this project when our funding ends?’, donors should instead ask, ‘What needs to be true for the benefits of this intervention to continue, and what role should our funding play in creating those conditions?’ This question recognises that philanthropy is often most useful when it finances a transition between two states. A grant can demonstrate that an idea works, absorb early-stage risk, strengthen institutions, develop markets, improve technology or support innovations that government and commercial finance are not yet prepared to fund. The grant should help create the conditions for the next stage. That may mean public financing, market revenue, community ownership, institutional adoption, commercial investment or another form of philanthropy. The appropriate pathway will vary by intervention, for example, a rural entrepreneurship program and a community health program should not be expected to arrive at sustainability through the same route.

This also means donors should sometimes be prepared to fund the less glamorous parts of sustainability. Financial systems are not exciting, NGO reserves are not photogenic, good middle management rarely features in impact stories, and neither do information systems, HR, audit, leadership development or fundraising capacity. Yet these capabilities determine whether an organisation can survive shocks, retain good people, manage resources and deliver programs consistently. Flexible funding is therefore not necessarily the opposite of accountability. It can be an investment in the organisational capacity required to deliver accountability well. A strong organisation with adequate systems and reserves may actually be better positioned to manage restricted program funding, and respond to changing circumstances and protect donor resources.

Then there’s another very important aspect of development programs, where everything cannot be sustained. Some projects end and achieve the desired results/purpose during their lifecycle. A delivery model may become obsolete, a technology may get replaced, a program may fail to produce meaningful results, or a community may no longer need an external intermediary. Continuing to fund something simply because it has existed for five years is institutional inertia and not sustainability.

The objective should therefore be sustainable value, not sustainable projects. This matters because many development challenges are systemic. Poverty, women’s economic exclusion, malnutrition, tuberculosis, climate vulnerability and the lack of decent employment cannot generally be ‘solved’ by a three-year project. At best, a project can change part of the system like improve a service, strengthen an institution, alter incentives, demonstrate a model, influence policy or help people acquire assets and capabilities.

Sometimes the honest answer will be that an intervention requires long-term funding, and there is nothing inherently unsustainable about that. Governments continuously spend money on education, public health, roads, social protection and environmental management. We do not ask whether a public hospital will become financially self-sustaining after three years, but are more interested in it producing sufficient public value to justify continued investment. Perhaps philanthropy should adopt some of the same logic. A community health program that requires continued financing may still be highly valuable if it prevents disease at a cost society is willing to pay. A program supporting children with special needs may never generate revenue, yet its social value can be substantial. 

So sustainability cannot always mean, ‘Can this generate its own revenue?’ That is a business-model question. For many social interventions, the better question is that, Who has a legitimate reason and capacity to pay for this value over the long term? The answer is an appropriate combination of market, government, communities, and philanthropy as per the need. This also places a responsibility on NGOs to become more honest in how they answer sustainability questions. A reassuring paragraph about capacity building, community ownership and exit strategies is not necessarily a credible plan. It’s better to be honest about it and say that the interventions may require continued public expenditure, or a livelihood project would need several more years beyond the grant cycle before it can cover its operating costs, and show the pathway. If another donor will be required, explain why and what will be different by then.

Sustainability becomes more credible when it is treated as a theory of how an intervention will continue to create value, rather than as a promise that the NGO will somehow find money after the current grant ends. We have turned a ,legitimate development objective into a ritual of grant writing. Every proposal has a sustainability section, a sustainability framework, and an exit strategy. Yet none of these, by themselves, answers the fundamental question of what will make this intervention continue to work when the source of money ends. A serious answer requires thinking about incentives, markets, institutions, behaviour, public finance, community ownership and organisational capability. It may require more than one source of funding and more than one institution. It may take five years rather than three. It may require unrestricted funding rather than another tightly earmarked project grant. And sometimes it may require accepting that the value created by a program is important enough to warrant continued investment. Perhaps, then, donors should stop treating sustainability as the final question in a grant proposal, but should be one of the first. So, instead of ‘How will you survive without us?’, the donor should ask, ‘What will exist, who will own it, who will pay for it, who will maintain it, and what should our role be when the grant ends to make the impact sustainable?’ While these are harder questions, I think, they can also lead to better projects. The most sustainable thing a donor can fund is NGOs capability, institution, market, public system or community ownership that makes the original grant less necessary over time.

(Disclaimer: The opinions expressed are those of the author and do not purport to reflect the views or opinions of any organisation, foundation, CSR, non-profit or others.)

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The price of stability in an unstable world

October 19, 2026 Leave a comment

We have been sold a dangerous idea that stability is normal and disruption is the exception, but is it? Yes, stability is an achievement, though an expensive one! Every morning, when the electricity is on, the internet works, the bank processes a transaction, food reaches you from a quick-commerce platform, a child gets to school, a salary arrives on time, and a hospital has the medicines it needs, it means thousands of invisible systems are doing their job in the background. We notice them only when they fail. For most of modern history, perhaps the greatest privilege was not wealth but predictability, the reasonable expectation that tomorrow would look broadly like today. That expectation is now harder to sustain as wars are disrupting supply chains, climate events are destroying livelihoods, artificial intelligence is unsettling occupations, financial volatility travels across borders in milliseconds, and demographic change is altering the very structure of families and work. We are entering an era in which instability may no longer be a temporary interruption to ordinary life but may become the usual.

So, who pays for stability in an unstable world? The obvious answer is governments, which build roads, maintain electricity grids, regulate financial systems, run hospitals, banks, police, and borders, subsidise food, respond to disasters, and provide social protection. But businesses pay too, as they maintain inventories, assets, diversify suppliers, retain cash and build redundancy into systems that would otherwise be cheaper and more efficient. So do families, as they keep emergency savings, buy insurance, invest in education, maintain social networks and sometimes make profoundly conservative choices because the consequences of failure are too high. Individuals pay in ways that don’t appear anywhere on a balance sheet. They stay in jobs they dislike because they’re secure. They postpone starting a business because they cannot afford six months without an income. They choose a predictable career over an uncertain vocation. They save instead of spending. They remain in cities they don’t particularly love because the city offers better healthcare, schools and employment opportunities. Stability, in other words, is not free, and we purchase it every day, often without realising that we are doing so.

But we don’t all pay the same price for instability. A wealthy household can absorb a medical emergency, while a poor household may have to borrow, sell an asset or withdraw a child from school. Likewise, a large corporation can survive a temporary collapse in demand, whereas a small enterprise may shut down permanently. A professional with savings can spend six months learning a new skill, and at the same time a casual worker may not be able to afford six days without income. The ability to absorb a shock is itself becoming a form of wealth. We have traditionally measured inequality through income, consumption and assets. Perhaps we now need another measure: the unequal distribution of uncertainty. Two families earning the same amount can live completely different lives if one has savings, insurance, secure housing, social capital and access to credit while the other survives from one monthly payment to the next.

Consider the millions of informal workers in India whose economic lives were disrupted during the COVID-19 lockdown. For many, the crisis was not simply about losing a job. It meant losing the entire architecture through which survival happened, like their daily wages, transport, access to urban work and sometimes food itself. The images of migrant workers walking hundreds of kilometres home became one of the defining visual memories of the pandemic. The crisis revealed how much of India’s economic stability was being privately financed by people with almost no financial cushion. When formal systems failed, the burden was transferred to households, communities and individual workers, where families became the insurance company of last resort.

Something similar happens every day, at a smaller scale, when an illness strikes a low-income household. India has made enormous progress in expanding healthcare access, insurance and public health infrastructure, but for millions of families, healthcare expenditure can still become a destabilising financial event. The difference between a middle-class household experiencing a serious illness and a poor household experiencing the same illness is not simply the quality of medical treatment available. One family may recover financially after recovering medically, while the other may spend years repaying debt. The illness turns into a crisis cascade of healthcare expenses, debt, reduced consumption, interrupted education and sometimes the sale of productive assets.

Climate change is producing another version of the same problem. Take a small farmer in Bihar, Assam, Odisha or Rajasthan. Agriculture has always involved uncertainty, but climate volatility is changing the scale and frequency of that uncertainty. An unexpected flood, prolonged heat, irregular rainfall or pest outbreak can wipe out months of effort. We often respond by telling farmers to become ‘climate resilient’, adopt new practices, diversify crops or use technology. All of these can be useful, but we tend to forget that resilience requires resources. A farmer with savings, irrigation, crop insurance, access to credit and market information has options. A farmer who owns little land and depends entirely on one seasonal harvest has very few. We cannot keep asking the poorest citizens to become more resilient without asking whether we have given them the financial and institutional infrastructure with which resilience can actually be built.

The same contradiction is visible in India’s growing, small-enterprise economy. We celebrate entrepreneurship and tell young people to become entrepreneurs, women to start enterprises, rural communities to build businesses and small producers to enter digital markets. Yet entrepreneurship is, by definition, an encounter with uncertainty. A person with substantial capital can afford entrepreneurial failure, but, say, a woman investing her family’s only savings in a small enterprise cannot. When a rural woman starts a tailoring unit, food-processing business, handloom enterprise or digital service centre, she is not merely creating income but is taking a financial risk on behalf of her household. This is why access to credit alone is not enough and entrepreneurs need markets, digital access, business capabilities, working capital, insurance, peer networks and, perhaps most importantly, the ability to fail without falling into destitution.

And then there is the instability coming from new-age technology. AI may create extraordinary new opportunities, but it will also change the value of many existing skills. We tell older workers to remain employable in a labour market changing faster than the institutions designed to train them. But learning itself requires time, money and psychological space. The person working ten hours a day to pay rent cannot effortlessly become an AI-enabled professional at night. The person supporting a family cannot always afford to experiment with a new career. Adaptability is not simply an attitude; it is an economic resource.

This is where our understanding of resilience needs to change. We have increasingly turned resilience into an individual virtue of being adaptable, keep learning, diversify your income, build an emergency fund, exercise, take care of your mental health, prepare for the future, etc., etc. There is nothing wrong with any of this, but we risk creating a society in which structural instability is increasingly privatised. At some point we have to ask whether we are confusing resilience with the ability of individuals to absorb risks that should partly be shared by institutions.

How to prevent uncertainty from becoming catastrophic for ordinary people, perhaps, will be the central economic challenge of the next few decades. We cannot promise a farmer that the monsoon will behave, a worker that her job will exist for thirty years, or that the next pandemic, financial crisis or geopolitical shock will never happen. But we can design systems in which these events do not permanently destroy a person’s future. That would require a different conception of social protection. The welfare state of the industrial era was largely built around protecting people from particular risks of unemployment, old age, illness, disability and poverty. The unstable world ahead may require something more dynamic, like systems that help people move through disruption. 

The cost of living without psychological certainty is another hidden cost of instability that economists struggle to capture, where uncertainty consumes mental bandwidth. When you don’t know whether your job will survive, whether a medical emergency could wipe out your savings or whether your child’s education will remain affordable, some part of your mind is permanently occupied by contingency planning. And that has implications beyond individual wellbeing. A society in which people are perpetually afraid of falling backwards is unlikely to be as entrepreneurial, innovative or creative as a society in which people know that failure will not destroy them.

This produces a fascinating paradox as we want an innovative economy, but innovation requires risk. Perhaps, therefore, the goal should not be stability in the conventional sense. We should stop trying to build a world in which nothing goes wrong, as such a world does not exist. The goal should be recoverability, where the capacity of people, families, businesses and communities to recover when something inevitably goes wrong should be present. This is ultimately a question of what kind of social contract we want. The price of stability will rise as the world becomes more volatile. Governments will spend more on resilience. Companies will pay more for redundancy and security. Families will save more. Individuals will invest more in skills and insurance. But if we allow every emerging risk to be pushed downwards from governments to companies, from companies to workers, from institutions to families and finally from families to individuals, we will create a society that appears economically efficient while becoming increasingly fragile.

We have become obsessed with efficiency precisely when the world is demanding resilience. We have spent decades removing buffers because buffers looked like waste, including excess inventory, spare capacity, multiple suppliers, idle infrastructure, permanent workers, and generous social protection. Everything had to be optimised, become leaner, faster and cheaper. Until the world reminded us that the things we call inefficiencies are sometimes the very things that keep systems alive when they break. So, the question we should be asking is not how much stability we can afford. It is how much instability ordinary people can afford to absorb before a temporary shock becomes a permanent change in their lives. Because the future will not belong to those who successfully predict every disruption. Nobody can. It will belong to societies that make disruption survivable. And if we fail to build those societies, we may discover a deeply uncomfortable truth that the poor will not merely be the people with the least money, but they will be the people who can afford the least uncertainty.

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What if love became infrastructure 

September 28, 2026 Leave a comment

I got the title (more like borrowed) from a WhatsApp group where a member shared the theme of the ‘At One Impact Week 2026’ conference in Singapore. This one powerful phrase, ‘what if love became infrastructure,’ made me think deeply from romantic and philosophical perspectives initially, and finally from an economist’s viewpoint, and I ended up doing a visioning exercise (sort of) for the future. Ideating and eventually writing this essay took me back down memory lane when I was a student of Social Planning.

We think of infrastructure as something tangible, visible and measurable, like roads, bridges, electricity, water systems, digital networks and financial systems. We know how to calculate their construction costs, estimate their economic returns, and argue over who should pay for them. We even understand that infrastructure can determine the destiny of societies and can alter the trajectory of an entire generation. But there is another infrastructure without which none of these systems ultimately works, and yet it rarely appears in our economic imagination. It is invisible, difficult to measure and almost impossible to commodify. It is love, not romantic love, though that matters too, but the broader human capacity to care, to notice, to remain, to take responsibility for another person’s wellbeing. We have traditionally treated love as a private emotion and have failed to recognise it as a public resource.

Every society runs on enormous quantities of unpaid love, like a parent getting up in the middle of the night for a sick child, or a daughter accompanying an ageing parent to hospital. However, none of these acts is generally counted as economic output. They do not appear in national accounts and are not part of productivity statistics. However, if we remove it altogether, hospitals will become more crowded because there will be nobody to care for people after discharge. Children will require more formal intervention because fewer adults will be available to support them. Elder-care systems will become unaffordable. Workplaces will become less resilient because employees have no one to rely upon outside them. We have created elaborate systems to compensate for the absence of care while rarely acknowledging the care that prevents those systems from collapsing in the first place.

The more efficiently we organise modern economic life, the more we seem to separate it from the relationships that make life worth living. We have become remarkably good at producing things and increasingly uncertain about how to sustain one another. We can deliver almost anything to a doorstep within minutes, but we cannot guarantee that someone will sit beside an elderly person who is lonely. We can communicate instantly with someone on the other side of the planet, but millions of people live without a person they can call when they are frightened. We can build increasingly intelligent machines, but many people struggle to find another human being willing to listen without looking at a screen. The technological revolution has reduced distance while, in some unexpected ways, increased emotional distance. Perhaps this is not a contradiction, and perhaps we simply solved the wrong problem. We became extraordinarily good at connecting devices, markets and information, while leaving the architecture of human connection largely to chance.

If love were infrastructure, loneliness would become an infrastructure deficit. That may sound absurd today, as we are used to thinking of loneliness as a psychological condition, a personal problem or sometimes a consequence of individual choices. But imagine applying the logic we already use elsewhere. If a community has no reliable public transport, we do not tell every resident to become better at walking, instead, we investigate the transport system. If people have no access to clean water, we do not blame them for being thirsty. If an entire generation has inadequate access to education, we do not simply advise young people to become more self-motivated. We build schools and institutions. Why, then, when millions of people experience profound social isolation, do we so quickly individualise the problem? Perhaps some loneliness is personal and inevitable. But some of it is produced by the environments we have built, like cities designed around cars rather than encounters, housing designed around privacy rather than community, workplaces designed around productivity rather than belonging, digital platforms designed around engagement rather than connection, and economic systems that leave people with less time for the relationships they depend upon.

The future city may therefore have to answer a question that today’s urban planning rarely asks if the city make it easy or difficult to belong? A well-designed neighbourhood might not simply be one where people can reach work quickly. It might be one where an elderly person can walk to a park, a child can meet other children, a young professional can enter a community without already knowing someone, and a person living alone has places to go where consumption is not the price of admission. Public libraries, community kitchens, parks, sports facilities, cultural centres, pedestrian streets and shared spaces are not mere amenities but relational infrastructure. Their purpose would be partly to create the conditions under which relationships can emerge naturally. Nobody can be ordered to make a friend. Governments cannot manufacture affection, but governments can certainly create environments in which human beings are more likely to meet one another, spend time together and develop trust.

This would require us to rethink the economics of care. Our economic systems are designed to value what enters markets. Care becomes visible when it is professionalised and paid, like a nurse, childcare worker, therapist, home-care worker, etc. But when the same work is performed by a spouse, parent, sibling, friend or neighbour, its economic value often disappears. What we fail to measure, we tend to underinvest in. And what we underinvest in eventually becomes a crisis. The care economy is therefore not an alternative to the productive economy; rather, it is one of its foundations. Every employee who arrives at work has already been sustained by some network of care. Every entrepreneur has had someone who tolerated their uncertainty. Every successful professional has, somewhere along the way, benefited from someone else’s patience, encouragement, childcare, emotional support or practical help. Economic independence is rarely as independent as we like to imagine.

Perhaps the next stage of capitalism will involve recognising this by redesigning institutions around the reality that people have caring responsibilities. Not by putting a price on love itself, because the moment love becomes a transaction, we risk destroying precisely what makes it valuable. Parental leave, elder care, flexible working, community services and mental-health support are not corporate generosity or welfare expenditure but investments in the infrastructure of human capability. The question would no longer be how much care we can extract from individuals before they burn out, but how we can design economies that reproduce care rather than consume it.

The 20th century built welfare states around the assumption that governments could provide a substantial share of social security. And now, the 21st century is discovering that governments cannot provide human presence, which is increasingly scarce. As populations around the world age and families become smaller, geographically dispersed and increasingly mobile, the question of who will provide everyday human care will become one of the defining social questions of the century.

We are approaching a world in which machines can converse, remember, personalise and simulate empathy with extraordinary sophistication. An AI companion may be available 24 hours a day, never become bored, never interrupt and never judge. For millions of lonely people, this may provide genuine comfort. There is nothing inherently tragic about that. However, if machines become exceptionally good at giving us the feeling of being understood, will we become less willing to tolerate the inconvenience of understanding another human being?

Human relationships are inefficient as they demand time, contain misunderstandings, and require compromise. Other people have needs that compete with ours, and they disappoint us, change, and sometimes even leave. But these inconveniences are not defects in the human system but are more part of what relationships teach us. A machine can perhaps simulate unconditional attention; another human being offers the possibility of mutual responsibility. The challenge for technology, therefore, should not be to replace human relationships but to protect the conditions under which they can flourish. The best AI may ultimately be the AI that saves time for us by reducing bureaucracy for doctors, helping families care for distant parents, assisting teachers, making public services easier to navigate and freeing people from repetitive work. Technology should ideally expand the space available for human presence rather than fill that space itself.

If this sounds utopian, consider how many things that once seemed private have already become legitimate subjects of public policy. We once treated literacy as an individual matter, and now we build education systems. We once treated disease as fate, and now we build healthcare systems. We once treated poverty as personal failure, and now we debate social protection. Our definition of what society owes its members has expanded repeatedly. Perhaps relational wellbeing will be the next frontier.

Imagine a future national wellbeing report that contains a metric nobody takes seriously today: the capacity to care. It might measure how much time people have for family, whether older people have regular social contact, whether young people have trusted adults, how many neighbourhoods possess accessible community spaces, whether workers can take time off for caregiving without economic punishment and whether people feel that they belong somewhere. Imagine a company reporting not only employee turnover but whether its organisational culture leaves people with enough time and psychological capacity to maintain lives outside work. Imagine investors recognising that communities with high levels of trust and social connection are more resilient in crises. These ideas may sound soft compared with infrastructure spending today. But history repeatedly demonstrates that societies often collapse because the relationships holding them together become brittle.

Love, in this broader sense, is demanding and requires boundaries, accountability and difficult choices. A society organised around love would not be one in which everyone agrees with everyone else or where harm is excused because the perpetrator is human. It would be one in which disagreement does not automatically turn the other person into an enemy, where vulnerability does not become a source of shame and where the dignity of a person is not entirely dependent on their economic usefulness. It would ask a different and radical political question: What do we owe one another?

Perhaps this is where the idea of love as infrastructure becomes most disruptive. Infrastructure is usually associated with physical capital, but civilisation also accumulates relational capital, like trust, friendship, community, reputation and reciprocity. The ability to call someone in a crisis is a form of wealth. Knowing that someone will notice when you disappear is a form of security. Having people who will help you when your circumstances change is resilience. These things are not equally distributed. Some people inherit enormous reservoirs of relational capital through families, communities and social networks, while others inherit almost none. We talk endlessly about inequality of income and increasingly about inequality of opportunity. Perhaps it’s time we should also talk about inequality of belonging.

The most interesting possibility is that love may eventually become a new way of thinking about development itself. It will be a recognition that human beings are profoundly relational creatures and that any civilisation that ignores this will eventually pay for it through other systems like healthcare, welfare, policing, education, mental-health services and lost productivity. What we fail to provide through relationships, we eventually attempt to provide through institutions, often at vastly greater cost.

And perhaps the deepest irony is that we already know how to build this infrastructure. We do not need a revolutionary technology. We need to rediscover ordinary human practices that modern life has made increasingly difficult, like sitting with someone, listening without checking the phone, knowing the names of neighbours, sharing food, visiting the elderly, creating public spaces where nobody needs to buy anything, giving people time to care, allowing friendships to develop slowly and treating presence as something valuable rather than unproductive. The infrastructure of love is built in minutes, conversations, gestures and acts of attention. 

When we imagine the future, we tend to imagine what technology will allow us to do. Perhaps a more important question is what technology will allow us to stop doing, and what we will choose to do with the time we recover. If AI does our paperwork, who will we visit? If autonomous vehicles drive us, who will we meet on the journey? If machines educate our children, who will teach them how to care? If algorithms know our preferences better than our friends do, will we still make the effort to know one another?

The future will not be short of infrastructure. It may, however, be short of reasons to use it together. Perhaps the civilisation that comes after ours will judge progress differently. It may look back at our obsession with highways, buildings, bandwidth, productivity and growth and wonder why we spent so much effort making things faster while allowing relationships to become harder. It may find it strange that we measured national wealth but not the wealth of human connection, counted houses but not homes, calculated healthcare expenditure but ignored the unpaid care that kept millions alive, and celebrated technological connectivity while tolerating extraordinary levels of loneliness. And perhaps the great infrastructure revolution of the future will begin with a deceptively simple realisation that the purpose of infrastructure is not to connect roads, machines, markets or data, but to enable human beings to live meaningful lives together.

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Humans, AI, and Singularity

September 13, 2026 1 Comment

For decades, artificial intelligence (AI) belonged to the margins of intellectual conversation in India. It appeared occasionally in science fiction paperbacks, in obscure academic journals, and in the late-night philosophical arguments of university students who spent more time debating the future than preparing for exams. Today AI has escaped the lab and entered dining table conversations. Hardly a day passes without newspapers carrying stories about machine learning, humanoid robots, generative AI, autonomous weapons, AI tutors, AI doctors, AI girlfriends, AI layoffs, or the looming question of whether machines may someday surpass human intelligence altogether.

I read these reports with fascination and a peculiar sense of déjà vu. They take me back more than thirty years, to conversations I had as a young student with my peers and professors about singularity, machine consciousness, and the possibility that intelligence itself might eventually become independent of biology. Back then, those conversations were treated as the eccentricities of a teenager. Most people dismissed them as fantasy, a youthful obsession fed by too much science fiction and too little realism. However, today many of the same questions have escaped philosophy departments and entered boardrooms, parliaments, military doctrines, and ordinary households.

Over the years, I discovered that very few people took such conversations seriously. In fact, until now, I have met only two individuals who shared similar views with genuine conviction: a young computer scientist then in his twenties, and a CEO of a major technology company then in his sixties, around 2010. One represented the restless optimism of a generation growing up with intelligent machines, and the other carried the hard-earned realism of someone who had spent decades building technology at scale. Despite the difference in age and experience, both sensed the same thing, that humanity may be approaching a transition far larger than another technological cycle.

The idea of technological singularity was always unsettling because it challenged one of humanity’s oldest assumptions that intelligence is uniquely human and therefore naturally tied to human control. The singularity hypothesis suggested something far more radical that technological systems could eventually improve themselves at a pace beyond human comprehension, producing an intelligence that exceeds human cognitive capability. At the time, in 1993-96, even discussing such ideas in India invited amused smiles. We were a country still grappling with unreliable electricity, landline waiting lists, and typewriters in government offices. To talk about self-improving machines in that era sounded absurdly premature.

But history has a habit of moving slowly for decades and then suddenly all at once. The internet changed how humans accessed information, and smartphones changed how humans interacted with information. AI now threatens to change what information itself means. This is not another technological wave comparable to social media or e-commerce, but it can potentially bring a civilizational shift. The printing press democratised knowledge, electricity mechanised labour, and the internet connected humanity. I think AI may redefine cognition itself. That is why the current AI moment feels fundamentally different. ChatGPT, Gemini, Claude, and other emerging systems are doing something historically unprecedented as they are beginning to perform tasks once considered exclusively intellectual. They write essays, generate code, compose music, summarise legal documents, diagnose diseases, create artwork, conduct research, and converse with startling fluency. 

Many critics comfort themselves by pointing out AI’s current flaws, as it hallucinates, lacks emotional depth, and cannot truly ‘understand.’ But this criticism misses the larger pattern of technological evolution. Early automobiles were unreliable and slower than horses on rough roads. Technologies mature exponentially while human intuition remains linear. We judge the future by the limitations of the present, forgetting how quickly those limitations disappear.

This is why singularity debates no longer feel theoretical. The unsettling part is not that AI can already imitate human capabilities; instead, it is the speed at which it is improving. Systems that seemed miraculous two years ago already appear primitive today. The interval between breakthrough and obsolescence is shrinking dramatically. Humanity is accustomed to gradual adaptation, and it seems that AI may deny us that luxury.

The greatest immediate threat from AI may not be killer robots, instead, it may prove to be social destabilisation. Human societies are built on meaning, and not only economics. Work is not only about income; it is also about identity, dignity, and social relevance. What happens when millions discover that cognitive labour, which was once considered secure from automation, is no longer uniquely valuable? For decades, developing countries like India viewed knowledge work as the path to upward mobility. Entire generations were told to study harder because intellectual labour was future-proof. But AI is beginning to challenge precisely that very foundational assumption.

Industrial automation disrupted blue-collar work first, and AI may disrupt white-collar work next. Lawyers, designers, coders, writers, analysts, accountants, customer support executives, and even educators are already witnessing AI-assisted transformation. Some roles will evolve, others may disappear entirely, and new professions will emerge. But transitions of this magnitude are never painless. History celebrates innovation retrospectively while ignoring the generations displaced during the process.

India possesses one of the world’s youngest populations and also has one of the largest digital workforces. AI could dramatically increase productivity and democratize access to education, healthcare, governance, and entrepreneurship. Rural women entrepreneurs, local language interfaces, AI-powered agricultural advisory systems, and intelligent public services could transform development outcomes. Yet AI could simultaneously intensify inequality if access, ownership, and benefits remain concentrated among a small technological elite.

Technology itself is never neutral, and it reflects the priorities of those who build and deploy it. This is where India’s conversation on AI remains surprisingly shallow. Much of our discussion still focuses on whether AI will make us globally competitive. The urgent questions are political: who controls AI infrastructure? Whose languages does AI understand? Whose biases does it inherit? Which jobs become expendable? Who captures the economic gains? What happens to human agency in societies increasingly mediated by algorithms?

The deeper issue is that AI is forcing humanity to confront uncomfortable truths about itself. For centuries, intelligence has formed the basis of human exceptionalism. We accepted that machines could outperform us physically because intellect remained our final frontier. But if machines begin outperforming humans cognitively in many domains, our understanding of value may fundamentally change. Perhaps that is why AI discussions evoke such emotional intensity. 

Every technological revolution reshapes not only economies but human psychology. Industrialisation changed family structures, television changed attention spans, and social media altered social validation itself. AI may reshape cognition, creativity, and even interpersonal relationships in ways we barely understand. Already, many people interact more comfortably with algorithms than with neighbours. And yet, despite these anxieties, I remain cautiously optimistic. Not because AI will automatically produce a better world, but because humanity has repeatedly demonstrated an extraordinary capacity for adaptation. The printing press triggered religious wars and political upheaval before enabling mass literacy. Electricity displaced industries before creating entirely new economies. The internet generated misinformation and addiction but also democratized knowledge and communication on an unprecedented scale.

AI, too, will produce both liberation and disruption. We are entering an era where ethical frameworks, governance systems, educational models,  and labour structures designed for the industrial age may no longer suffice. Yet our political systems remain trapped in short electoral cycles while technological acceleration operates exponentially. This mismatch worries me more than the machines.

Thirty years ago, singularity debates felt abstract because technological reality lagged far behind imagination. Today, imagination struggles to keep pace with reality, and that shift alone should humble us. Human civilisation may be approaching one of its most consequential transitions since the Industrial Revolution, yet our collective response often oscillates between hype and distraction.

Perhaps the most important question is not whether AI will surpass human intelligence, but the more important question is whether humanity can develop the wisdom necessary to coexist with technologies more powerful than any we have previously created. Intelligence without wisdom is dangerous, whether biological or artificial. And maybe that is the defining feature of our age. For the first time in history, humanity is no longer merely imagining intelligent machines; we are living alongside their early forms. The distance between science fiction and social reality has collapsed dramatically within a single generation. The singularity may still be decades away, or perhaps it may never arrive in the dramatic form as futurists have predicted. But one thing is certain that AI is no longer a peripheral technological development. It is becoming the central force shaping economics, politics, labour, warfare, creativity, and perhaps eventually even human identity itself. The question is no longer whether AI will change civilisation, but whether civilisation is prepared for what AI may become.

(The cover image is generated using AI)

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Invisible Entrepreneurs

September 7, 2026 Leave a comment

Across rural India and much of the developing world, millions of women wake up before dawn, manage households, tend to livestock, cultivate small plots of land, process food, stitch garments, rear poultry, trade locally, and keep families economically afloat through a variety of income generating activities. Despite their relentless productivity, most of this work does not count as ‘business’ in policy frameworks, financial systems, or even social imagination. These women are workers, contributors, and risk takers, but are rarely recognised as entrepreneurs. Their labour remains invisible, undervalued, and structurally excluded from the very systems meant to promote enterprise and growth.

The invisibility of rural women entrepreneurs is not accidental. It is the outcome of deeply entrenched economic definitions, gender norms, institutional biases, and measurement failures that collectively erase women’s work from formal recognition. To understand why rural women’s enterprises remain unseen, one must look beyond individual capability or ambition and examine how ‘business’ itself is defined, counted, and legitimised.

Entrepreneurship has a narrow and exclusionary definition. In mainstream economics, a business is typically imagined as a registered entity, operating from a distinct workspace, producing for markets beyond the household, employing labour, and generating measurable profits. This definition immediately excludes most rural women, whose enterprises are often home-based, seasonal, informal, and interwoven with domestic responsibilities. When a woman processes grains, sells homemade snacks, stitches clothes for neighbours, weaves handloom products, or rears goats for periodic sale, her work is seen as an extension of household duty rather than economic activity. The fact that it generates income is treated as incidental, not central.

This conceptual blindness is further reinforced by national accounting systems. Gross Domestic Product calculations and labour force surveys systematically undervalue or exclude unpaid and semi-paid work. Women’s labour in family farms, household enterprises, and informal trade is often categorised as ‘assisting’rather than ‘ownership’ work. Even when women contribute substantial labour and decision-making, land titles, business ownership, and enterprise registration are typically in men’s names. As a result, women disappear statistically, even when they are economically indispensable.

Social norms further deepen this invisibility, as in many rural societies, men are perceived as breadwinners and women as caregivers, regardless of actual income contribution in the households. When a man sells produce in the market, he is seen as doing business. When a woman does the same, it is often framed as ‘helping’ the family. Earnings generated by women are frequently pooled into household income, while men’s earnings are recognised as individual contribution. This asymmetry strips women of entrepreneurial identity and reinforces the idea that their work lacks independent economic value.

The location of women’s work also plays a critical role in its invisibility. Because women’s enterprises are commonly home-based, they blur the line between productive and reproductive labour. The home, traditionally associated with unpaid care work, becomes a site where economic activity is rendered invisible simply because it does not conform to spatial norms of business. While a shop has legitimacy, a kitchen does not; a workshop is considered productive, but a courtyard is not. This spatial bias penalises women whose mobility is restricted by safety concerns, social norms, accessibility, or caregiving responsibilities.

Most rural women operate outside formal regulatory frameworks, not as their choice but by necessity. Registration processes are complex, documentation-heavy, and poorly aligned with women’s realities. Limited literacy, lack of identity documents, absence of land titles, and dependence on male family members make formalisation difficult. Formal financial institutions, in turn, rely on formal registration to extend business credit, insurance, and market linkages. This creates a vicious cycle, where women remain informal because systems exclude them, and systems exclude them because they remain informal.

Despite extensive evidence that women are reliable borrowers and effective managers of small enterprises, rural women face disproportionate barriers to credit and access to formal business financing. Collateral requirements favour land and property ownership, which women rarely possess. Credit histories are tied to formal transactions that women are excluded from. Even microfinance, often celebrated as a solution, has limits. Loans are frequently used for household consumption rather than enterprise expansion, and women bear repayment responsibility without gaining corresponding control over assets or profits. Financial inclusion without entrepreneurial recognition risks turning women into financial intermediaries rather than empowered business owners.

Rural women tend to operate at the lowest end of value chains, engaged in production rather than aggregation, branding, or marketing. They sell in local haats (markets), through informal networks, or to middlemen who capture most of the value. Because their scale is small and operations fragmented, their economic contribution is dismissed as marginal. Yet, collectively, these micro-enterprises form the backbone of rural economies, sustaining food systems, crafts, services, and local trade.

The development sector itself has played an ambivalent role in reinforcing invisibility. Programs targeting rural women often frame entrepreneurship as a social development or empowerment intervention rather than a serious economic strategy. Women are encouraged to ‘supplement’ household income, and not to build scalable enterprises. Training focuses on skills rather than markets, confidence rather than capital, participation rather than profit. While these interventions have value, they inadvertently reinforce the idea that women’s enterprises are secondary and subsistence-oriented and not engines of growth.

Most measurement surveys and impact assessments rely on indicators that fail to capture women’s economic realities. Metrics such as revenue, employment generation, or formal registration overlook non-monetary contributions, seasonal income, risk mitigation, and household-level decision making. Women’s enterprises are often judged against male norms of entrepreneurship, setting them up to appear less productive or ambitious, when in fact they operate under entirely different constraints. When women’s work is not recognised as business, they are excluded from policy support, denied access to finance, overlooked in market development initiatives, and marginalised in economic planning. This exclusion perpetuates gender gaps in income, assets, and agency. It also represents a massive loss to economies that fail to harness the full potential of half their population.

There is growing evidence that recognising and supporting rural women entrepreneurs yields significant economic and social returns. Studies show that women are more likely to reinvest earnings in nutrition, education, and health, creating intergenerational benefits. Women-led enterprises contribute to local resilience, especially in contexts of climate stress, migration, and economic shocks. Yet, without recognition, these benefits remain undervalued and underleveraged. Changing this reality requires a fundamental shift in how entrepreneurship is conceptualised and operationalised. Definitions of business must expand to include informal, home-based, and collective enterprises. Economic contribution should be measured not only by scale and formality, but by sustainability, resilience, and impact. Data systems must be redesigned to capture women’s work accurately, including unpaid and semi-paid labour, joint ownership, and household enterprises.

Institutional reforms are needed to lower barriers to formalisation without penalising informality. Simplified registration, group-based enterprises, and recognition of alternative forms of collateral can help bring women into formal systems on their own terms. Financial products must be tailored to women’s enterprise cycles, risk profiles, and asset constraints. Credit should be linked to capacity building, market access, and asset ownership, not just repayment discipline. Market interventions must move beyond production to address value chains holistically. Supporting aggregation, branding, digital access, and collective bargaining can help women capture greater value. Technology, if designed with women’s realities in mind, can play a transformative role by reducing mobility constraints and expanding market reach. However, as experience shows, access alone is insufficient without confidence, trust, and institutional support.

Finally, social norms must be confronted directly, as recognition is not only a technical issue but a cultural one. When communities, families, and institutions begin to see women as entrepreneurs rather than helpers, power dynamics shift. Legal recognition, public visibility, and role models matter, and so does language. Calling women ‘business owners’ instead of beneficiaries is a political act, and not just semantics. Invisibility is not a natural state, and is produced through choices about what counts, who counts, and whose work is valued. Rural women have always been entrepreneurs in practice, even if not in name. Making their work visible is not about charity or inclusion alone, but it is about economic realism. Until rural women’s enterprises are recognised, measured, and supported as legitimate businesses, development efforts will continue to underestimate both the problem and the potential.

If this essay made you reflect on rural development, women’s entrepreneurship and human potential, subscribe to my blog for one new article in your inbox every week. It’s free!

(Disclaimer: The opinions expressed are those of the author and do not purport to reflect the views or opinions of any organisation, foundation, CSR, non-profit or others.)

The cover image is generated using AI

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