Elisabeth Kurniawan: AI Is About More Than Technology

Jakartaweekly.com – Artificial intelligence is often framed as a race for technological superiority: who can build the most powerful models, access the most computing capacity, or move innovation forward the fastest.

But as AI becomes increasingly embedded in economies, public services, businesses and everyday life, the conversation is becoming much bigger than technology itself.

AI is also about access, capital, governance, sovereignty and, ultimately, power.

That was one of the strongest reflections from the AIFOD Geneva Summit, which brought together leaders, policymakers, investors, academics, technology professionals and other stakeholders to discuss the future of AI, particularly in relation to developing countries and the Global South.

The most important question may no longer simply be, What can AI do?

Instead, it may be: Who gets to benefit from it?

Access Is More Than Using an AI Tool

AI is often described as a democratizing technology. Today, millions of people can access generative AI tools that were unimaginable only a few years ago.

But access to an interface does not necessarily mean equal participation in the AI economy.

There are multiple layers of access: access to computing infrastructure, data, capital, talent, education, connectivity and markets. There is also access to policymakers and institutions that are shaping the rules governing AI.

Someone may be able to use an AI tool while remaining structurally excluded from the economic opportunities created around it.

This is particularly relevant for developing economies.

If AI becomes a major driver of productivity and economic growth, unequal access to the capabilities needed to develop, deploy and govern AI could also create deeper inequalities in economic opportunity.

That is why conversations around capacity building, AI literacy and participation in global AI governance are becoming increasingly important.

The future of AI should not be shaped only by those with the largest data centres, the deepest capital pools or the most advanced technology.

Capital Helps Decide What Gets Built

AI is also a capital story.

Capital does more than finance innovation. It helps determine which technologies are developed, which companies scale, which problems receive attention and which markets become priorities.

As AI creates new economic opportunities, the distribution of those opportunities will not happen automatically.

Investors, governments, companies and founders will all make decisions that shape where resources go.

This raises important questions for investors and business leaders.

What infrastructure does an AI business depend on? Who owns the critical technology layers? Where does the data come from? What happens if access to a platform changes?

And perhaps more importantly: who becomes increasingly dependent as AI becomes more powerful?

These questions may not always appear on a traditional investment pitch deck, but they are becoming increasingly important.

Rethinking AI Sovereignty

Another major issue emerging from the global AI conversation is sovereignty.

AI sovereignty does not necessarily mean that every country must build its own foundation model or own every part of the technology stack.

For many countries, that would be unrealistic.

A more practical question may be: Which capabilities must a country control, and which capabilities can it responsibly share?

Meaningful sovereignty may involve the ability to govern data, protect critical infrastructure, develop local talent, negotiate with technology providers and maintain alternatives.

It is about having the capability to make informed choices rather than becoming permanently dependent on external technology.

The same principle applies to businesses and startups.

Every company depends on something it does not control, whether that is a technology platform, a major customer, a supplier, a distribution channel or a regulatory environment.

Early-stage companies often accept dependency in exchange for speed and efficiency. But as they grow, understanding and managing those dependencies becomes a strategic necessity.

Capability Will Matter More Than Access

Technology can be purchased.

Capability takes much longer to build.

An organisation can subscribe to an AI platform overnight, but it cannot instantly create a workforce capable of building, evaluating, governing and effectively deploying AI.

That requires education, experience, institutions and time.

This is why AI literacy should be viewed as more than a technical skill. It is increasingly becoming part of the infrastructure needed for individuals, businesses and countries to participate in the AI economy.

Technology can amplify capability.

But it can also amplify the absence of it.

AI does not eliminate the need for human judgment. If anything, it makes good judgment even more valuable.

The Questions Are Bigger Than Technology

Perhaps the most significant lesson from the evolving AI conversation is that the questions facing governments are not entirely different from those facing founders and businesses.

Who controls the infrastructure?

Where are we dependent?

What capabilities should we build ourselves?

Where should we partner?

How do we maintain flexibility when the environment changes?

These are strategy questions.

The companies that succeed in the AI era may not necessarily be those with the most impressive AI demonstrations. They may be the ones that understand how AI fits within a larger system of capital, talent, data, regulation, trust and human behaviour.

AI innovation requires technologists. But it also requires policymakers who understand markets, investors who understand infrastructure, founders who understand regulation and institutions willing to consider the broader consequences of technological change.

The challenge is not simply to build more powerful AI.

It is to build the conditions around it: the infrastructure, governance, talent, institutions and access that allow more people to participate.

Ultimately, the most important question may not be who builds the most powerful AI system.

It may be whether the systems being built create broader opportunity—or simply concentrate advantage among those who already hold the greatest resources.

That is where AI stops being just a technology story.

It becomes a question about the future we choose to build.

Opinion by : By Elisabeth Kurniawan