Smartphone vs Computer Gap: India may have solved for digital access, but not for digital capability and that gap could decide who builds the next decade of wealth in the AI era. That was the core warning in a recent post by Sandeep Jethwani, Co-Founder at wealth-tech firm Dezerv, who argued that India’s explosive smartphone adoption has come with an overlooked cost: millions are online, but far fewer have the tools and skills needed to create on the internet rather than merely consume.

In his post, Jethwani cited a stark contrast: 85% of Indian households own at least one smartphone, while only 9% own a computer. He framed it as a “PC-skipped” trajectory one where mobile devices became the primary gateway to the digital world, but foundational computer ownership did not scale alongside it.

Computer Gap: A regional comparison that raises uncomfortable questions

What makes the disparity harder to ignore, Jethwani wrote, is how India compares with countries he described as having similar socio-economic profiles. He cited Vietnam at 27% computer ownership, Indonesia at 18%, and Pakistan at 12% all higher than India’s 9%.

The point of the comparison wasn’t to create a league table, but to underline what he called an emerging fault line: the ability to participate in higher-value digital work is not evenly distributed, and device access plays an outsized role.

“Access is not capability”: DPI’s limits in the compute era

Until recently, digital public infrastructure in India-exemplified by system platforms like UPI and Aadhaar-has been largely characterized by scale and access. Jethwani, however, said these systems are incomplete and not what is needed beyond this point.

“UPI, Aadhar, and other DPIs only solve for access not capability or compute,” he wrote, adding that the world will be increasingly shaped by those who control “energy and compute.”

In this framing, internet penetration is no longer the finish line. It’s the entry ticket. The bigger contest is now about whether people have the devices and environments that enable them to learn and perform higher-order digital work: creating documents, running software, coding, manipulating data, and building products, especially as AI becomes embedded across industries.

Skills data shows the gap widening from basic to advanced tasks

Jethwani’s post connects device ownership with a measurable skills divide. He cited ICT (information and communication technology) skills data to argue that while basic phone-native tasks have spread, computer-centric skills remain limited.

According to the figures he cited:

• About half of Indian adults can send messages
• Only about a fourth can send emails or install software
• Just one in ten can work with spreadsheets

In other words, the steep drop-off begins right where the modern workplace begins. Messaging is ubiquitous; email and software installation, often the minimum bar for many office roles are far less common. Spreadsheet competence, a foundational skill for business, finance, operations, and analysis, is rarer still.

The youth picture is “equally concerning”

The most unsettling part of the post, Jethwani suggested, is that the gap isn’t confined to older cohorts. He pointed to generational data as evidence that even young Indians may be entering adulthood without the hands-on computing exposure that earlier generations in computer-rich environments take for granted.

He cited that only one in ten Indians aged 15-24 can create electronic presentations, compared with more than half in Mexico.

This is not just about slideshow software, he implied. It is a proxy for comfort with desktop interfaces, file systems, productivity suites, and workflows that are still central to formal education and professional work across the world.

Why low PC ownership shapes what people can become

Jethwani’s argument is built on a simple chain: low computer ownership reduces everyday practice, and without daily practice, skills that require a computer remain out of reach for a large share of the population.

He listed examples of “foundational skills” that are harder to develop without regular access to a computer:

• configuring hardware
• working deeply with spreadsheets
• writing computer programs

These activities cannot be characterized as niche pursuits. They open doors to professional opportunities within technology, analytics, digital operations, finance, design, as well as a range of entrepreneurial activities. Without access to a machine on which these activities can be undertaken, exposure becomes an intermittent process, limited to educational or cyber cafes, for instance.

A blunt AI-age warning: phones can’t do everything

The post lands most forcefully when it ties device constraints to AI capability. As AI tools proliferate, Jethwani argues, the difference between using AI and building with AI will increasingly come down to compute access and the ability to work in environments designed for creation.

“You cannot train models on a phone. You cannot run local LLMs. You cannot code or build agents,” he wrote, adding that “the tools that will define the next decade of wealth creation require real compute.”

This is the crux of the “compute divide” he is describing: smartphones can dramatically expand participation in digital payments, messaging, entertainment, and services. But many of the activities that generate outsized economic leverage, building software, training and deploying models, running development environments, working with large datasets, are far more difficult without a computer.

“India risks becoming an AI user base, not an AI builder base”

Jethwani’s conclusion is less about doom and more about trajectory. The risk, as he frames it, is structural: if computer ownership and computer skills remain low, India could end up as a massive market for AI-powered products built elsewhere, rather than a country producing a proportional share of AI builders and companies.

“Compute will determine how quickly we move from labour to leverage,” he wrote, positioning compute access as the next stage after connectivity. Internet access, in this view, has become “table stakes.” The differentiator is who has the tools and skills to produce.

Why this debate is resurfacing now?

The post reflects a broader anxiety that tends to surface during platform shifts: when the world changes its tools, societies that lack those tools risk being permanently placed on the consumption side of the equation.

Jethwani’s framing suggests India is at such a moment. The smartphone boom delivered scale and convenience and arguably accelerated everyday digitisation. But his warning is that scale without capability can produce a different kind of inequality: not between connected and unconnected, but between those who can build with technology and those who can only access it.

Jethwani also cited a capability estimate: as of 2025, a little over one in five adults around 200 million people, were able to operate a computer. Placed alongside the household ownership figures he shared, the implication is that computer familiarity exists, but may not be backed by widespread personal access.

This combination, some capability, some ownership, often denotes friction: learning can occur, but is more difficult to maintain; capabilities can be developed, but are harder to implement; contact can be made, but is harder to capitalize.

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