A New Digital Model for Global South

 

The world is being quietly rewired. Not debated. Not theorized. Rewired. Most nations are drifting into this transformation without agency, adopting systems designed elsewhere, shaped by interests that are not their own.

This is not a technical issue. It is a sovereignty issue. A development issue. A dignity issue.

To understand why this matters, consider a simple story. Two boys from Mumbai meet at an international math Olympiad in the United States. One is from an affluent neighbourhood, the other from a nearby slum. When the first expresses surprise at seeing him there, the second replies: “I too use the Internet. I too have access to Google… I too can afford it.”

This story (I am not sure if is really a true story) captures a profound truth: when information became democratized, and bandwidth was made affordable opportunity followed.

But the same did not happen with the digital economy. Commerce splintered into walled gardens. Power concentrated. Access narrowed. And now, as artificial intelligence becomes the next foundational layer of society, the risk is even greater: a world where intelligence itself is monopolized.

Two futures are emerging. One imagines abundance, where AI collapses the cost of essential services and expands human capability. Everybody enjoys the fruits. The other imagines a digital ghetto, where a handful of corporations and countries control the tools that determine economic and social mobility.

Let us go a little deeper.

The Three Models That Have Defined the Digital World

For the last decade, the world has been shaped by three dominant digital models:

1. The US Model: Innovation With Limited Guardrails

It produces extraordinary breakthroughs, and extraordinary concentration. Platforms own identity, data, and digital rails. Regulation arrives late, often after the damage is done.

2. The European Model: Rights Without Scale

It protects citizens but struggles to build globally competitive digital markets. Compliance becomes the moat; innovation becomes the casualty.

3. The Chinese Model: Scale Without Contestability

It delivers population-scale systems but centralizes power to an unprecedented degree. Predictive governance and surveillance becomes the default; pluralism the exception.

Each model solves one problem and creates another. Each is incomplete. Each is unsustainable for most nations; especially the global south.

A Fourth Model Is Emerging—And It Comes From the Global South

Across Africa, Southeast Asia, and Latin America, governments are searching for a digital architecture that is open, sovereign, affordable, and inclusive. One that does not require choosing between innovation and rights, or between scale and contestability.

A new model, pioneered in India but not limited to India, is offering that path.

Its core principles are simple:

1. Digital Infrastructure as a Public Good

Identity, payments, data exchange, and document systems are built as open protocols, not private platforms. This ensures interoperability, competition, and low entry barriers.

2. Competition Through Design, Not Litigation

When switching costs are low and systems are interoperable, small firms can compete with global giants. Markets remain contestable by architecture, not by antitrust lawsuits.

3. AI as Shared Infrastructure

Public compute grids, open foundational models, and federated data governance prevent AI from becoming a private monopoly. Intelligence becomes a public good.

4. Inclusion as a First-Order Principle

Digital systems must work for the poorest, the least literate, the least connected. If they don’t, they are not public goods—they are private luxuries.

5. Pluralism as a Structural Safeguard

Diverse societies require systems that prevent any single institution, narrative, or actor from dominating. Pluralism becomes a guardrail against digital authoritarianism.

This model is not ideological. It is practical. It is exportable. And it is already being adopted, from digital ID systems in Africa to payment networks in Southeast Asia to data exchange frameworks in Latin America.

The Real Contest of the Next Decade

The next decade will not be defined by who builds the most powerful AI.
It will be defined by who builds the most governable AI.
The most contestable AI.
The most inclusive AI.

The real contest is not between nations.
It is between models of governance.

One model concentrates power.
One fragments society.
One slows itself into irrelevance.
And one, if we choose to build it, distributes power, accelerates innovation, and protects dignity.

Digital Systems Are the New Constitutions

“Digital systems are the new constitutions. And constitutions must be written by the people they govern, not by corporations, not by foreign powers, and not by accident.”

The world is being rewired. The only question is whether nations will shape that rewiring or be shaped by it.

History does not reward hesitation.
It rewards those who build the foundations on which others must stand.

And today, those foundations are digital.

The world is being rewired. The only question is whether we will shape that rewiring—or be shaped by it.

Governing the Age of Prediction: Why Digital Public Infrastructure May Define the Future of Freedom

 

 

We are not merely regulating data anymore.

We are deciding who governs prediction.

For fifty years, data protection laws evolved to defend privacy in an increasingly digital world. They were designed to answer a simple but profound fear: What happens when institutions know too much about individuals?

But that question now feels incomplete.

The deeper transformation of our time is not about data collection. It is about inference. Artificial intelligence has converted data into predictive power,  and predictive power into economic, political, and social influence.

The age of information has quietly become the age of prediction.

And this shift demands a new paradigm.

From Privacy to Power

The early era of data protection emerged in response to centralized databases. The concern was surveillance. Governments digitized welfare systems, tax records, and population registries. Corporations built credit databases and marketing profiles. The solution was rights-based regulation: consent, purpose limitation, minimization.

Privacy became a shield.

Then came the internet economy.

Data was no longer administrative,  it became extractive. Behavioral tracking, location monitoring, cross-device identity graphs, and advertising ecosystems transformed personal data into a new form of capital. Platforms scaled globally. Users became legible at unprecedented depth.

The scandals of the 2010s, mass surveillance disclosures and political microtargeting triggered regulatory escalation. But even the most sophisticated privacy laws were built for a world where harm came from misuse of stored information.

AI has altered the equation.

Today, systems do not simply record what we do. They infer traits we never disclosed. They shape the choices presented to us. They optimize our attention and influence our behavior. They anticipate what we will do.

Data protection regulates inputs.

AI governance must regulate outputs.

And this is where the paradigm shifts.

The Transformation of Autonomy

Classical freedom meant freedom from coercion.

But algorithmic societies do not rely on visible force. They rely on modulation.

What you see is ranked.
What you buy is suggested.
What you believe is nudged.
What you fear is amplified.

The modern citizen is not under surveillance  only to be watched, but to be predicted.

Prediction reduces uncertainty.
Reduced uncertainty increases control.

And control, even when invisible, pressures autonomy.

The essential tension of the AI age is now clear:

• Economic systems reward maximum prediction.
• Democratic systems require independent judgment.
• Human dignity requires space for unpredictability.

If optimization becomes the highest social value, freedom quietly transforms into managed choice.

The Concentration of Intelligence

AI introduces network effects more powerful than any previous industrial logic.

More users → more data → better models → better services → more users.

This dynamic concentrates intelligence infrastructure into a handful of global entities. The asymmetry grows:

• A small number of actors can model billions.
• Billions cannot meaningfully model the systems modeling them.

This is not merely market concentration. It is cognitive concentration.

Whoever controls large-scale inference controls the architecture of influence.

That reality forces a civilizational question:

Will intelligence infrastructure remain privately centralized, nationally siloed, or publicly democratized?

Enter Digital Public Infrastructure (DPI)

Digital Public Infrastructure is often discussed in technical terms, digital identity systems, payment rails, data exchanges. But its true significance is philosophical.

DPI represents a structural alternative to data extraction models.

At its core, DPI builds shared digital rails upon which markets, services, and innovation can operate, without requiring private monopolization of identity and transaction layers. Diffusing AI to edges instead of concentrating with the intermediaries

It separates foundational infrastructure from competitive services.

That separation is transformative.

1. Identity as a Public Good

In many platform ecosystems, identity is proprietary. Your login credentials are tethered to corporate environments. Identity becomes a gateway controlled by private actors.

DPI reimagines identity as a public utility, interoperable, portable, user-consented, and governed by public-interest principles.

When digital identity is public infrastructure:

• Market access barriers decrease.
• Data portability improves.
• Individuals gain structural leverage.
• Governments reduce dependence on foreign platforms.

Identity ceases to be a corporate moat.

It becomes a civic layer.

2. Payments and Transactions as Open Rails

Closed payment ecosystems concentrate economic data. DPI-based payment interoperable markets create open transaction layers that allow multiple providers to innovate atop standardized infrastructure.

This democratizes participation in digital markets.

Small businesses compete without surrendering all behavioral intelligence to dominant intermediaries.

Economic value distribution becomes less asymmetrical.

3. Consent Architecture Reimagined

Traditional privacy law depends on notice-and-consent mechanisms that individuals rarely understand.

DPI enables programmable consent frameworks:

• Granular permissions.
• Revocable access.
• Transparent audit trails.
• Interoperable data-sharing protocols.

Instead of endless consent pop-ups, DPI can embed structural governance into architecture.

The goal shifts from individual vigilance to systemic design.

4. Enabling Public-Interest AI

Perhaps most importantly, DPI creates the conditions for pluralistic AI development.

When foundational data and identity rails are interoperable and regulated:

• Startups can train models without vertically integrating entire ecosystems.
• Public institutions can build AI systems for health, climate, education.
• Data monopolies weaken.
• Intelligence becomes layered rather than captured.

DPI does not eliminate markets. It prevents markets from owning the rails of cognition.

DPI and the Global South: Preventing Data Colonialism

The predictive economy risks replicating colonial extraction patterns.

Behavioral data from developing populations flows outward. Models are trained elsewhere. Economic value accrues in distant jurisdictions. Local ecosystems remain dependent.

DPI offers strategic sovereignty.

By retaining control over:

• Identity systems,
• Payments infrastructure,
• Data exchange layers,

Nations can capture domestic value from digital participation.

DPI allows emerging economies to leapfrog directly into interoperable, open ecosystems without surrendering long-term predictive power to external platforms.

In this sense, DPI is not merely technical architecture.

It is geopolitical infrastructure.

Beyond Ownership: Toward Governance of Intelligence

The debate about “who owns data” is increasingly misplaced.

Data is relational. Its value emerges through aggregation and inference. Ownership frameworks alone cannot address asymmetrical predictive power.

What must be governed is not raw data, but intelligence infrastructure.

Three structural paths lie ahead:

1. Corporate Predictive Order
   Global platforms dominate AI and behavioral modeling.
2. State-Centric Sovereignty
   Governments centralize AI power within national borders.
3. Distributed Civic Intelligence
   DPI, public AI frameworks and competitive innovation layers.

The third path is the most complex. It requires coordination, constitutional foresight, and political will.

But it is also the only path that structurally balances:

• Innovation
• Autonomy
• Democracy
• Economic dynamism

Designing an AI-Compatible Democracy

If AI becomes embedded in governance, new principles are required:

• Cognitive Liberty: Protection against involuntary behavioral manipulation.
• Algorithmic Accountability: Regulation of system impacts, not just data inputs.
• Separation of Predictive Power: No single actor should control data aggregation, model training, and deployment simultaneously.
• Public Digital Commons: Shared informational spaces insulated from commercial manipulation.

DPI operationalizes many of these principles. It distributes leverage. It lowers structural asymmetry. It embeds public-interest values at the infrastructure layer.

The Civilizational Fork

By 2040, societies will not debate whether AI exists.

They will debate what kind of predictive civilization they inhabit.

If optimization dominates:
Society becomes frictionless, efficient, and permanently legible.

If autonomy dominates:
Society becomes plural, slower, less predictable, but genuinely free.

The real battle is not over privacy pop-ups.

It is over the architecture of intelligence.

Digital Public Infrastructure offers a path where intelligence is democratized rather than monopolized, where AI augments society without enclosing it.

The future of data governance is no longer about protecting information.

It is about governing prediction.

And in the age of prediction, the deepest question is not technological.

It is political:

Who should control the systems that model humanity?

The answer will define the meaning of freedom in the twenty-first century.

 

“The deepest form of privacy is not secrecy — it is cognitive sovereignty.”

How Open Networks Are Re Architecting the Digital Future of the Global South

 

The world stands at an inflection point. Open networks are democratising commerce, and AI is poised to democratise intelligence. If these two forces learn to move in harmony, humanity has a genuine chance at a more equitable future. That was the spirit with which I opened the panel at the AI Summit, because the question before us is no longer whether technology will transform society, but who it will transform it for.

The Historical Warning We Cannot Ignore

Every major technological revolution has reshaped the world. The Industrial Revolution unlocked unprecedented productivity, new infrastructure, and innovations across defence, travel, textiles, and more. But it also carried a darker truth: the very technologies that enabled progress were weaponised by a few to conquer, colonise, and control many. The benefits were not shared; they were extracted.

Today’s digital revolution risks repeating that pattern. What began as a promise of openness, participation, and inclusion is drifting toward concentration, gatekeeping, and digital colonisation. The “digital continent” we are building could easily become another empire, unless we choose a different path.

India’s Answer: Digital Public Infrastructure

India chose that different path. We built Digital Public Infrastructure (DPI) to reverse the trend and make the digital world genuinely democratic. Two principles define DPI:

• Unbundling -separating layers so innovation can flourish independently
• Interoperability - ensuring systems talk to each other, not lock users in

These principles have already reshaped payments through UPI and are now re‑architecting commerce through ONDC. Open networks do not replace markets; they redesign markets. They create common rails that:

• Lower entry barriers for small businesses
• Enable competition without fragmentation
• Allow innovation to happen at the edges, not only at the centre

In ONDC’s case, the goal was never to build another platform. It was to make commerce itself a shared public capability accessible to kirana stores, micro‑entrepreneurs, logistics providers, startups, and consumers alike.

The Internet of Transactions

We are entering a new phase of the internet—one that is not just a network of information but a network of transactions. This new architecture will be:

• Interoperable - connecting diverse actors across sectors and borders
• Inclusive - enabling participation without gatekeepers
• Iterative - evolving through feedback and experimentation
• Infrastructure‑led — built on public digital rails, not private silos

This is how we build choice without coercion, scale without centralisation, and innovation without inhibition.

Why This Matters for the Global South

For the Global South, the stakes are even higher. These nations face a dual challenge: massive scale and deep diversity on one side, and resource constraints on the other. The real questions are:

• Who benefits from scale?
• Who controls the ecosystem?
• Who gets left out?

Open networks emerged precisely to address this tension. They are not a technical alternative; they are a governance choice, a choice to separate infrastructure from innovation, protocols from platforms, and power from participation.

As ASEAN, Africa, and other regions explore open digital infrastructures, India’s experience offers a blueprint: open networks can shift the centre of gravity from a few dominant players to millions of participants.

When AI Meets Open Networks

AI can turbocharge open networks. It can:

• Expand market access for small merchants
• Improve discovery for consumers
• Enable smarter matching between buyers and sellers
• Strengthen trust through fraud detection and verification

But AI also introduces a new risk: concentration of power. If intelligence becomes centralised, we risk replacing platform monopolies with algorithmic monopolies.

The question is not whether AI should be used, it must be. The question is how.

In open systems, AI must be:

• Augmentative, not extractive
• Contestable, not monopolised
• Diversity‑enhancing, not concentration‑driven
• Accountable, not opaque

This requires careful choices about where intelligence resides, at the edge or only at the core, with users or only intermediaries, governed by rules or by defaults.

Open networks give us a chance to build AI‑enabled markets without creating AI‑driven monopolies. But this is only possible if governance evolves as fast as technology.

Governance: The Quiet Hero of Digital Transformation

Governance is the least glamorous part of digital transformation, but it is the most decisive. Open networks must answer foundational questions:

• Who sets and evolves the protocols?
• How are disputes resolved?
• How is compliance enforced without stifling innovation?
• How do we maintain neutrality as ecosystems scale?

As AI becomes embedded, governance must also address:

• Algorithmic accountability
• Data rights and consent
• Cross‑border interoperability
• Long‑term stewardship

These are not technical questions, they are institutional ones.

The Real Impact: Participation, Not Just Transactions

Open networks fundamentally change who gets to participate in the digital economy.

• Small merchants reduce dependence on a single platform
• Startups lower customer acquisition costs
• Consumers especially the marginalised, gain choice and transparency
• Economies become more competitive and resilient

In the Global South, where informality is high and trust is fragile, this is transformative. When layered responsibly, AI can amplify this impact, making services more accessible, markets more efficient, and systems more responsive to local needs.

But inclusion is never automatic. It must be designed, governed, and defended.

What Will Define Success

The success of open networks in the Global South will not be measured by transaction volumes or the sophistication of AI models. It will be defined by:

• Diversity of participants
• Resilience of governance
• Fair distribution of value
• Ability to innovate without concentration of power

This is difficult work, but it is essential work.

As we move into the panel discussion, we bring together perspectives from global finance, digital infrastructure, market ecosystems, and public policy. The goal is not just to share insights but to shape the collective learning that will guide the next decade of digital transformation.

“AI will amplify whatever architecture we build. If we build open networks, it will amplify inclusion. If we build silos, it will amplify concentration. The choice is ours—and it is urgent.”

Artificial Super Intelligence and the Humble Human Part 1

 

“Science fiction warned us about machines that think; it never warned us how ordinary that moment would feel.”

For centuries, intelligence was the one domain humans assumed would remain uniquely ours. Strength could be mechanized, memory could be stored, speed could be amplified, but thinking felt different. Today, that assumption is quietly dissolving. Artificial Intelligence is advancing not in steady steps, but in accelerating leaps, challenging our definitions of reasoning, creativity, and even understanding itself. And yet, when we look closely, the distance between computation and humanity remains both profound and revealing.

Artificial Intelligence is progressing in leaps and bounds, practically on a day-to-day basis. In many areas, it already outperforms humans by a wide margin. To evaluate how close AI comes to genuine human reasoning, we rely on benchmarks such as ARC, which attempts to measure AI performance in comparison to humans.

ARC (Abstraction and Reasoning Corpus) is a benchmark created by François Chollet to measure general fluid intelligence in AI—the ability to learn new skills and reason abstractly without prior domain-specific training. It has evolved into multiple levels: ARC-AGI-1, ARC-AGI-2, and ARC-AGI-3 (preview). Current leading AI models perform far below human level on the hardest levels: humans solve nearly 100% of tasks, while even the best AI models struggle to reach 50% on ARC-AGI-2 and under 20% on ARC-AGI v2.

The current performance landscape looks like this:

• Humans vs AI: Humans consistently solve 100% of ARC tasks, highlighting the massive gap in reasoning ability.
• AI Progress: While ARC-AGI-1 was nearly “solved” by large models, ARC-AGI-2 exposed their limitations—brute force and scale are insufficient.
• Breakthroughs: GPT-5.2’s ~53% on ARC-AGI-2 is a major leap, but still far from human-level reasoning.
• Future: ARC-AGI-3 will test interactive reasoning, pushing AI beyond static puzzles into dynamic environments.

In summary, ARC is the North Star benchmark for AGI, measuring whether AI can truly think, generalize, and adapt like humans. Despite significant progress, leading models remain far from human-level performance, especially on ARC-AGI-2 and beyond.

While researching this topic, I was reminded of Data, the humanoid android from Star Trek: The Next Generation. Curious, I asked Microsoft Copilot how Data might score by comparison. This was its response:

ARC-AGI-1 (basic abstract reasoning puzzles)
Humans: ~100% | AI: ~75–87% | Data: Effortless.
Data routinely demonstrates the ability to infer rules, patterns, and transformations far beyond simple grid puzzles. He would solve these instantly, likely faster than humans.

ARC-AGI-2 (harder, resistant to brute force, requiring deep abstraction)
Humans: ~100% | AI: ~53% (best models) | Data: Near-perfect.
Data shows fluid intelligence: he learns new games (like poker or strategy simulations) without prior training, adapts to alien logic systems, and reasons abstractly across domains. He would likely match or exceed human-level performance here.

ARC-AGI v2 (leaderboard variant, where top AI scores are <20%)
Humans: ~100% | AI: ~15% (best) | Data: Essentially flawless.
Data’s ability to generalize across unfamiliar contexts—whether deciphering alien languages, solving engineering crises, or improvising in diplomacy—suggests he would achieve near-100% here, like humans.

ARC-AGI-3 (interactive reasoning, dynamic environments)
Humans: ~100% | AI: Not yet tested | Data: Beyond benchmark.
Data thrives in interactive, real-world reasoning: commanding starships, negotiating with adversaries, and adapting in real time. He embodies the kind of general, embodied intelligence ARC-AGI-3 aims to test.

At this point, I listened again to a discussion between Data, Geordi (Chief Engineer), and Dr. Pulaski (Chief Medical Officer), which reminds us how far away even the fictional android is from being human.

The context is that Data and Geordi enter the Holodeck to play Sherlock Holmes adventures. Since Data knows all the stories, he keeps jumping the gun and spoiling the fun. Geordie got frustrated and abandoned the game. They both came to the café and discussing the frustration about playing with Data and Dr Polaski was listening to this conversation.

“What we were doing You are wasting your breath ,lieutenant. saying that to data is asking a computer not to compute” Said Dr Polaski.

“Am I so different from your doctor.” Asked Data

“Are you able to cease speaking on command. In medicine I am often faced with puzzles that I do not know the answer.” Said Doc

“She's right there. you always know the answer. to feel the thrill of victory there has to be the possibility of failure and where's the Victory in winning a battle you can't possibly lose.” Georgie observed

“Are you suggesting there is some value in losing” Data asked

“ Yes yes that's the great teacher . we humans learn more often from a failure or a mistakes than we do from an easy success . not you. you learn by rote. to you all is memorization recitation .” Said Doc

‘I don't know about all that. Deductive reasoning is one of data strengths” Georgie commented

“Yes and Holmes is too. But Holmes understood the human soul; the dark flecks that drive and turn the innocent into the evil, that understanding is beyond data.” Said Pulaski

“Now you're just being unfair doctor” Quipped Georgie

“I don’t think so lieutenant. Your artificial friend doesn't have a prayer of solving a Holmes mystery that he hasn't read’

Being a Star Trek aficionado, I then asked Copilot to compare Data with another Next Generation–era AI: the Emergency Medical Hologram from Star Trek: Voyager.

Data would consistently outperform the Doctor in abstract, cross-domain reasoning.
The Doctor would rival or surpass Data in medical problem-solving and human interaction. His emotional growth gives him an edge in empathy-driven reasoning, which ARC-AGI-3 (interactive tasks) is designed to capture.

In short, Data is the embodiment of general intelligence; the Doctor is the embodiment of specialized intelligence evolving toward generality. Together, they illustrate two pathways AI could take. one built for universality, the other for depth and human connection.

AI may bring super intelligence soon, not a normal human being. And will this super intelligence empower the human or annihilate the human is the question.

The idea behind this post is not to be judgmental, but to invite you to join me on a quest on what more is to being human- better human. Atma with a link to Paramatma ?

“Intelligence may be measured in problems solved, but humanity is revealed in the problems we struggle with.”

“The Matrix Isn’t Coming - We’re Building It.”

 

In 2011, my blog post titled “Looking for ‘the One’? A Cynic’s Fantasy” invoked The Matrix as a metaphor for our world ; where most people are treated as mere resources, while a powerful few extract wealth and power, often using distraction and control to keep the masses docile.

Today, as we stand amid the rapid rise of generative AI, autonomous systems, and mass-data platforms, I find that old metaphor eerily prescient , but the villain need not be the technology itself. The real danger lies in how it is exploited, and in our collective failure as society to resist that exploitation.

Consider these parallels:

• AI-driven recommendation engines can personalize content to the point of manipulation , redirecting our attention, shaping our world-views, and nudging behavior, much like the virtual reality in The Matrix.
• Advanced automation could optimize efficiency .  but if left unchecked, it risks reducing people to cogs in a system focused solely on profit and power.
• Powerful actors (big tech, corporations, political players) may lean on technology to amplify influence, extract value, and suppress dissent  not unlike the ruling class in the original metaphor.

But here’s the thing: technology is not the enemy. The problem is how we allow it to be used , or abused,  and the choices we make (or don’t) when we see injustice.

🔹 What if, instead of waiting for a “saviour” (a Neo or “the One”), each of us made small, conscious choices  championing transparency, demanding accountability, and supporting those who use technology for public good rather than private gain?
🔹 What if we recognized that real change comes from collective resolve, not isolated heroics? That means encouraging ethical AI, pushing for fair policies, holding companies accountable, and refusing to be pacified by convenience or fear.

In short: let’s not demonize AI,  let’s stay vigilant about how we use it, and who holds the levers of control. Because if we remain passive, we risk ending up in a very real-world version of The Matrix.

#AI #Ethics #TechForGood #Society #Responsibility #MatrixMetaphor #Leadership

 

Related Article  Looking for “the One”? A Cynic’s Fantasyl

AI, Culture & Trust: Why Relationships Still Matter in a Digital World

 

Economic activities all over the world are heavily influenced by profit motive except in case of affirmative actions by government or philanthropy. However, these transactions are stitched together by relationship among the participants. The extent of this  varies across the cultures

• High-context cultures (e.g. China, India, Brazil) rely heavily on personal relationships, where trust and loyalty are built over time and often precede formal agreements.
• Low-context cultures (e.g. U.S., Germany) prioritize efficiency and clarity, where relationships may be helpful but are not prerequisites for business.
• Hybrid cultures (e.g. Japan, UAE, South Africa) blend formal structures with relational depth, often requiring cultural sensitivity and patience.

As the world is moving towards proliferation of AI in more and more domains especially where human interfaces are heavy, the adoption is significantly going to be influenced by the cultural context.  In this context, the leadership driving this need to keep in mind that

• Relational trust can unlock innovation and speed.
• Cultural fluency helps navigate power dynamics without compromising integrity.
• Ethical clarity ensures that influence remains constructive, not corrosive. 

In cultures where personal relationships are central to business, like India, China, Brazil, and much of Africa, the adoption of AI faces unique friction and adaptation curves:

Trust Is Earned, Not Assumed

• AI systems, especially those that automate decisions (e.g. hiring, lending, procurement), may be met with skepticism unless they reflect human-like empathy, transparency, and cultural nuance.
• In high-context cultures, relational trust often trumps algorithmic efficiency. Leaders may hesitate to delegate sensitive decisions to AI unless the system is explainable and aligned with local values.

Adoption Hinges on Relational Gatekeepers

• Influential individuals—mentors, senior executives, family business heads—play a key role in shaping attitudes toward AI. Their endorsement can accelerate trust and uptake.
• In public-private partnerships, relational capital often determines access and influence. AI must be positioned as a complement to human judgment, not a replacement.

AI Must Learn the Language of Relationships

• AI tools that support personalized recommendations, emotionally intelligent communication, and context-aware negotiation are more likely to succeed in relationship-driven environments.
• For example, AI-mediated communication has shown to improve cross-cultural understanding by 31% and negotiation satisfaction by 24% when transparency is built in.

As AI becomes embedded in business workflows, it will inevitably reshape how trust is built and maintained:

From Intuition to Insight

• AI can surface patterns in behavior, preferences, and risk that were previously inferred through intuition. This can enhance trust by making decisions more consistent and data-backed.
• However, it may also erode the informal, emotional cues that underpin trust in many cultures; especially if AI is perceived as cold or opaque.

Hybrid Trust Models Will Emerge

• The future lies in hybrid trust: where AI handles routine tasks and pattern recognition, while humans manage nuance, empathy, and ethical judgment.
• Businesses that blend AI’s precision with human warmth will build deeper loyalty and satisfaction, especially in customer-facing roles.

Transparency Will Be the New Relationship Currency

• AI systems must be designed with explainability, consent, and cultural sensitivity. In relationship-driven contexts, people want to know not just what the AI decided, but why.
• This is especially true in sectors like digital finance, where personalization must be balanced with ethical clarity and data integrity.

In this context we  could:

• Frame AI as a trust amplifier, not a trust substitute.
• Design DPI systems that embed relational logic—e.g. community-driven feedback loops, culturally adaptive interfaces.
• Mentor young leaders to navigate the dual fluency of algorithmic and interpersonal trust. 

 As we move forward, let’s deepen our understanding of how relationships shape power, influence, and trust. I explored this in an earlier reflection on “Market Power & Relationships”—still relevant today:

📖 Read the blog post

“The measure of intelligence is the ability to change.”Albert Einstein

(I had posted a summariesed version of this as a lined in post. https://www.linkedin.com/posts/koshy89_market-power-relationships-activity-7374399657952628736-_-2t?utm_source=share&utm_medium=member_desktop&rcm=ACoAAAHWSYQBQXp5IHBAbmYtmy0QTDr2QMLjsi8)

ONDC – Big Bang moment for eCommerce

 

The universe after the Big Bang evolved and is still evolving continuously. Not as a centrally controlled and managed process. But, as an ecosystem with each component in its trajectory, impacted by, and impacting, the other ecosystem building blocks. Zooming in further, the lifeforms also evolved from the single-cell wonders in the primordial soup to the atomic-age man through continuous innovation by nature what we know as mutation across the ecosystem. Every new innovation adds or subtracts functionalities and capabilities, with some succeeding to sustain and some failing and perishing. The technological progress we made as a human race from wheel to spacecraft also followed this incremental innovation across the ecosystem. That is the “Order of Nature”.

 Very often, success in the natural order arises in a simple yet fundamental paradigm shift, and successful players are those who quickly adapt to the evolving paradigms, cooperating and collaborating with the ecosystem. Thought leaders from Darwin to Schumpeter to Niall Fergusson in the modern era, have argued that, “This is the age of digital Darwinism, in which it is not the strongest or most intelligent that survives, but the one that most successfully uses technology to adapt to change.”

When it comes to eCommerce w can see that it has evolved out of line with this natural order of the nature. Two or three giants with deep pockets building up stranglehold in each domain tuned to maximise their shareholders’ interest.

There is extensive innovation in this model. But limited to innovation to maximise their self-interest through a centrally managed process, to meet the requirements of their typical user group and/ or enhancing their user group through a cookie-cutter approach.  Any outside innovation has no chance to survive unless it is subservient to or sold out to the biggies. [1] It is an uncontrolled that is engulfing commerce, eventually taking control of it all and leading to stifling diversity. Much like the magma chamber of a dormant volcano, this keeps the lid on growth and evolution. This has already set alarm bells ringing across the world, with many developed countries trying to mitigate through regulation, be it the America Innovation and Choice Online Act in the US, the Digital Markets Act in the EU or UK’s Digital Markets, Competition and Consumers Bill,

It is here that the idea of ONDC has come in with a big bang. Encouraging innovation and specialisation across the ecosystem with all of these building blocks communicating among them and interoperable through an open-source protocol. This allows and encourages lots of people to work on different building blocks and come out with a plethora of solutions for diverse user groups and not to straight jacket users or shape the users into a straight-jacket. As Howard Moskowitz observed in his research paper; there is no single optimum, but there are multiple optima for every use case. Some will fail and some will succeed and the winner is society, as a whole and not shareholders of a few enterprises.

This will address the challenge of market concentration and associated practices that are a challenge in the platform-centric world today.  This will encourage a natural order of continuous innovation with some succeeding and some failing with the overall ecosystem marching forward.

The Build for Bharat Hackathon organised by ONDC recently in collaboration with Industry demonstrates this. 100,000+ participants in 2,100+ teams from across the country coming together with outstanding solutions with most of them having a working model and monetization plan shows. This shows how Open Model will unleash creativity across a wider cross-section of big and small enterprises and individuals. This is what excited representatives from 20 VCs who attended the hackathon final.

Now it is clear why I have the audacity to term ONDC as the Big Bang Moment of eCommerce that can totally transform the world of commerce in the near future.

 

“When money, rather than innovation or value, is your competitive advantage, that’s when things get boring and stagnant, and monopolies take root.” —Hank Green

Implementing ONDC – A Journey

 

Standing on the shoulders of giants…

I read somewhere that in the early nineties when India attempted computerisation of the banking sector which was one of the major early attempts at computerisation across a domain, there was very high resistance from the bank unions who were worried about job loss. The idea was then sold as a provision of the Advanced Ledger Posting Machine (ALPM) to reduce the drudgery of the staff. India has come a long way since then.

The launch of the National Stock Exchange (NSE) as one of the earliest fully computerised stock exchanges, as against the “ring-based trading” that was prevalent in India and across the world, was a bold attempt in computerisation of the capital market. Establishing of National Securities Depository Ltd (NSDL) for dematerialised holding and trading of shares helped India leapfrog from being the most backward, to one of the most modern settlement systems in less than five years.

UIDAI was India’s attempt to build a population-scale digital ID solution first time in the world using open-source technology.  This project aimed to provide each individual with a unique ID.  The factors that contributed to its runaway success were very clear and simple problem definition (one unique ID for every person) which limited the extent of data collection required to issue the ID and functionalities offered which were only ID issuance and authentication), ensuring that there is no vendor or technology lock-in for any component, with the help of opensource technology (even when the use of proprietary solutions was absolutely essential, as in the case of biometric deduplication and authentication, a plug and play architecture ensured this vendor neutrality), the solution that was linearly scalable by design based on open source technology stack helped in making Aadhaar highly cost competitive. UIDAI brought in private sector participation to establish national-level enrolment capacity, and crucially there was no cost to the citizen as the cost of enrolment was borne by the government. The payment to the enrolment agency by the government against successful enrolment helped in the enrolment agencies being outcome-focused and result-oriented. Government’s thrust to UID-based benefit distribution created a demand-pull leading to UID penetration of more than 95% of the population in a short time.

The UID project proved that a Digital Public Infrastructure can drive dramatic transformation in benefit distribution as well as in service delivery. The next big initiative in this direction was UPI for broadening the adoption of digital financial transactions.  The unbundling and interoperability of the building blocks of customer interface for payments and receipts using QR code while the funds being held and transacted by the banks helped to create a very cost-effective fintech ecosystem that could spread across the country, and helped adoption of this method by merchants and consumers across all segments of society. The Demonetization provided a significant demand surge, positioning India to account for over 40% of the global volume of financial transactions.

New Kid on the block

Building on the foundation of these successes, we have ventured onto a new initiative to solve a problem that is challenging both developed and developing countries equally. The problems of a few large tech platforms using proprietary technology hijacking the market in many domains like consumer goods, food distribution, ride-hailing, travel and tourism etc., which in turn leading to business practices that are not in the best interest of the business enterprises (especially small enterprises) and consumers.

The initiative was triggered by the COVID pandemic. DPIIT Ministry of Commerce and Industry) wanted to find a solution to the supply disruption of everyday needs impacting the consumers and small merchants. A Steering committee, established with participation from both the government and the private sector deliberated and decided that the solution should not be a stop-gap arrangement in times of pandemic; but a solution that will transform commerce to address the challenge of exclusion of small businesses and the limitation of choices to the common consumers. This forum was expanded to have eminent members like Nandan Nilekani,  R S Sharma, Adil Zainulbhai, Anjali Bansal, Dilip Asbe, Suresh Sethi, Kumar Rajagopalan, Pradeep Khandelwal and Arvind Gupta with Anil Agarwal, the then JS in DPIIT as the coordinator and now continue as the advisory council. Later, Anurag Jain joined this council with Sanjiv JS DPIIT coming in as the coordinator. ONDC being the latest initiative in the DPI world in India let us delve deeper into how the solution was shaped and how it is proceeding.

In every business transaction, there are two sides. One is the payment for goods or services by the buyer(s), and the other is for making the inventory visible in the digital market by the seller(s) and searching for, choosing of, and contacting for products/ services by the buyers.

UPI took care of the payment side. ONDC is now attempting to do the same magic in the products/ services side by democratising commerce through the un-bundling of building blocks of commerce and making them interoperable to create an Open Network instead of walled gardens of platforms

Challenges Galore

In the case of UIDAI, while the biometric deduplication and authentication for the population of India, was a technological challenge that had no existing solution, which was solved by the brilliant team of UIDAI,  the process requirement for onboarding is relatively straightforward and funded by the government with no cost to the person being enrolled.  In the case of UPI, we have only one SKU (i.e. the money) to be exchanged, and that too digitally. The user interface can be really simple to handle and harmonised for this single SKU. The entities providing end-user interfaces are only a handful and the money is handled by a well digitised and highly regulated banking sector.

When it comes to commerce involving products and services, the challenges are multi-fold. SKUs are in millions, belong to diverse categories of goods and services, ranging from street food to laptops, and from auto-hailing to credit and insurance.

These require different user interfaces for different products/services for different kinds of buyers, and complex business processes for order processing, inventory management, packaging, warehousing, logistics and grievance handling for sellers, which necessitates their own nuances of rendering of information and handling information flow. The sellers come from different domains some well-regulated, some partly regulated and some entirely non-regulated. No regulatory mandate to participate or no “demonetisation” to create business compulsion or no linked benefit delivery to encourage adoption,

One Step at a Time

So ONDC is taking a step-by-step approach. With the help of endorsement from the Government, particularly by the Commerce Minister and DPIIT, leading banks and financial institutions chipped in the necessary capital to establish a not-for-profit company with the necessary flexibility and agility to respond to the fast-changing  requirements of digital commerce; that with a global-first solution architecture. FIDE Foundation with Nandan Nilekani, Pramod Varma and Sujith Nair as founders gave the foundational protocols and continued guidance. A powerful Advisory Council and a Board with appropriate participation of government, investors and independent members provide strategic direction and ensured unblemished governance.

Being a network, there is no central platform to be established by ONDC. The network would succeed only if we can create a vibrant ecosystem. It is a classical chicken-and-egg dilemma. Unless there is wide participation of merchants and service providers, it is not exciting for the customers; and unless there is a wide customer base on the network, there is no incentive for the sellers to come aboard 

More importantly, this is an idea that has never been attempted anywhere in the world. To encourage adoption, we needed to demonstrate that such cascaded flows, stitching services provided by multiple entities, will in reality  work seamlessly with end-to-end security of data.

ONDC being a network there was no central system to be built and tested by ONDC for the potential users to check out. We had to have some entities coming forward to develop seller apps and onboard merchants, buyer apps and consumers to try out orders, and Gateway and Registry to link these.

With a few entities like Protean, PayTM, Loadshare, Gofrugal, DIGIIT, Growthfalcon and Sellerapp, who were willing to bet on this idea and develop a minimum viable product and convince a few sellers to onboard, ONDC team went about demonstrating that this is a Network that can deliver its promise. This was our alpha testing phase that was kicked off in five cities across the county within five months of the company's incorporation. While the ultimate goal of the network is to cover the entire gamut of catalogable products and services, ONDC commenced alpha testing with the challenging domains of Food and Grocery. 

Six months later, ONDC launched beta testing in Bangalore with Grocery, Food and Mobility and after streamlining the processes among the participants and merchants in the first couple of months, we started reaching out to the consumers in Bangalore to try out the network. lowly and steadily, we managed to have more merchants and service providers, and a few customers testing out the network with around 40 to 50 transactions a day.

While this proved that we can have transactions in an unbundled network, we have a long journey ahead to have a critical mass of merchants and consumers in the network to make it sustain, and grow and to achieve the original objective of democratisation of digital commerce.

Unite and Conquer

One of the key elements of our early strategy was to have a few anchor partners in the domains we launched, then gradually scale transactions and publicize on a regular basis our principles, our aspiration, our roadmap and our progress. We had support from the Minister, the ministry, government, industry, startup ecosystem, philanthropic agencies and developmental institutions endorsing us, and the press giving us visibility and encouragement for the baby steps forward. This challenged us and is helping to convert fence-sitters one by one.

15 months on, we have grown from 800 merchants and 1200 orders in a month to 400,000 merchants, 8 million orders in a month across 800 cities, with  month on months steady improvement in penetration, usage and all key performance parameters with respect to order fulfilment and delivery. Though we had started with grocery, food and mobility, we have gradually added many more domains such as electronics, fashion and apparel, health and wellness, beauty and personal care, home and kitchen, credit, insurance, agriculture input and output etc and many more like B2B procurement, home and urban services, entertainment ticketing, multi-modal transportation and the list goes on.

ONDC’s ultimate vision is that every catalogable product/ service will be on the network, with innovative buyer interfaces helping diverse user segments access and choose what is relevant for them.

The industry in general, except for a handful, understands and welcomes this idea of open network. But we need to crack the cold start problem. Therefore, we are approaching this with a dual strategy. We are working with the digitally mature entities familiar with e-commerce to get them onboard and reach across ecommerce-friendly consumers to get the pumps primed. But it is a long journey.

The well-established businesses that are currently operating in a platform-centric world are yet to fully appreciate the dramatic change possible in the distribution channels and supply chains with the freedom an open network offers to the brands and merchants. The corporate bureaucracy, busy with business as usual are slowly realizing the opportunities, and many are seriously evaluating the possibilities, including this in the top management agenda and making it a priority and not just a nice-to-have tick-in-a-box. It is heartening to see established players from the public sector and private sector like SIDBI, NABARD, SFAC, HUL, ITC, Google, Meta, Dominos, Tata, OLA, PayTM, MagicPin, Juspay,Reliance etc. taking definite steps by launching their presence, albeit in pilot scale in comparison with their potential.

In the meantime, we have multiple initiatives to support the mini & small enterprises and to help the unserved and underserved sections of enterprises, entrepreneurs, artisans, weavers etc, who are normally ignored or provided lip-service for PR purposes to become truly ready to embrace, adopt and benefit from the world of digital commerce.

This involves innovation, capacity-building and handholding in areas ranging from selecting and signing-up with a service provider of their choice, developing attractive catalogues, uploading these catalogues with inventories to the network, responding in time to orders, order fulfilment, packaging for delivery, obtaining logistics, responding to queries and so on, so that they are accepted by the extended consumer base the network can offer. 

Many government agencies are excited about the possibilities with the ONDC Network. Ministries like MSME, Agriculture, Textiles, Fisheries and Animal Husbandry from Central  and State Government are doing/developing/ considering projects that can scale nationally. They are also in the process of developing/ launching schemes for their ecosystem, to leverage the network through digitalisation.

Philanthropic agencies like BMGF, TERI. etc have also jumped into the fray to extend processes, technology, and toolsets, and more importantly help them to promote their products/services.

The addition of financial products and services like credit, insurance and investments can be a real gamechanger when it comes to the small business as it can be an avenue for accessing flow-based working capital credits, sachetized insurance and investment driving digital inclusion across the length and breadth of the country.

We are expecting to have participation of of BFSI sector starting with Financial  Products and then expanding their scope to help small and medium scale industry to leverage open network with a robust foundation enhancing digital financial inclusion.

Now that we are getting a decent pipeline of suppliers of diverse products and services, we need a big push to bring the consumer base. Not just existing users; but we need to expand the participation of both merchants and consumers in this world of opportunities digital India offers

Road Less Travelled

While we go through these steps for network and enabling ecosystem development, there are quite a lot of activities that the ONDC team with the active collaboration from the network participants are engaged in, to strengthen the network and to build trust on the network.

These include, but are not limited to:

(i)           continuous evolution of network polices to cover ever-expanding functionalities and domains;

(ii)          continuous evolution of protocol capturing the evolving network policies to help enforcement of processes;

(iii)       network-wide services such as scoring of merchants/service providers, which then becomes a digital asset they can benefit from, as well as acting as a deterrent to unscrupulous merchants, and a protection to the consumers;

(iv)     data lake of non-competitive,    non-business sensitive non-PII data, anonymised   and  aggregated as open data for all participants, to benefit without being an exploitative tool

(v)             SDKs, training and capacity-building material as common assets;

(vi)            developing an ecosystem of enablers and service providers to support small enterprises;

(vii)       enabling big-tech engineering skills on AI and language models to be available as standard offers that can be leveraged by small enterprises to complement their strengths in operation and customer care.

(viii)      enhancing systems and processes for smoother and faster grievance and dispute resolution

Tailpiece

Such roles help ONDC to help the network to continuously evolve as a truly democratic digital marketplace. This is a journey no person has ever made before; where India is playing a leadership role. Come and join hands in this global first quest

 " IF you want to be a pioneer you have to blaze your own trail"