In the global race to build the next generation of artificial intelligence, the most valuable commodity is no longer oil or even computing power. It is data.
Across Sri Lanka, a quiet contest is unfolding among telecommunications companies, emerging AI platforms and government institutions over who will control the country’s most valuable digital information. The outcome could determine how the island nation participates in what economists increasingly describe as the next great technological economy.
Artificial intelligence systems depend heavily on large, structured datasets to function effectively. As governments and businesses around the world invest billions into AI development, Sri Lanka is beginning to recognize that its own digital information—from court rulings to land registries—may hold untapped economic value.
At the center of the emerging private sector push is Dialog Axiata PLC, the country’s largest telecommunications provider. With more than a decade of digital expansion behind it, the company sits on one of the largest collections of consumer data in Sri Lanka.
Telecommunications networks generate a continuous stream of information: how people move across cities, how they communicate, what digital services they use and how they spend money through mobile platforms. Analysts say this type of behavioral data is increasingly valuable for training artificial intelligence systems that can predict trends, automate services and improve decision-making.
“Telecom operators naturally hold some of the richest digital datasets in any country,” said a Colombo-based technology analyst who follows the AI sector. “When that information is combined with artificial intelligence, it can power everything from digital banking services to smart agriculture.”
Dialog has already begun deploying AI-driven services, including automated customer support tools, enterprise analytics and advisory platforms designed to assist farmers. With its nationwide digital infrastructure, the company has the capacity to scale such technologies rapidly.
But the contest over Sri Lanka’s data is not limited to telecommunications giants.
A different approach is emerging from new technology platforms attempting to organize fragmented national information into structured digital knowledge systems. One of the more prominent initiatives is Chat2Find, which is building a network of AI-powered databases across several sectors including law, taxation, education and business intelligence.
Rather than focusing on consumer behavior data, the platform is assembling specialized knowledge datasets—the type that often powers professional research tools used by lawyers, accountants and financial analysts.
Among the projects linked to the ecosystem are platforms that digitize legal judgments, regulatory rulings and taxation frameworks. Such datasets, when combined with artificial intelligence, can transform large volumes of legal or regulatory text into searchable advisory systems capable of answering complex professional questions.
The approach mirrors strategies used by some of the world’s most successful information companies. Bloomberg built a financial empire by aggregating market data, while LexisNexis became indispensable to legal professionals by digitizing court decisions and legislation.
“Data monopolies have historically created some of the most powerful technology businesses,” said the analyst. “The companies that control the information often control the market.”
Sri Lanka, analysts say, possesses several datasets that could prove especially valuable in the AI era.
Legal information is among the most significant. The country’s courts produce thousands of judicial decisions each year, while government institutions publish legislation, regulatory rulings and gazette notifications. Together they form a complex legal record that businesses and professionals must constantly interpret.
Taxation and financial regulations represent another enormous dataset. Sri Lanka’s tax codes, customs regulations and financial reporting standards create layers of compliance requirements that businesses navigate daily. AI systems trained on such information could potentially automate large portions of regulatory analysis.
Corporate registry records also hold substantial value. Information about company ownership, directors and financial filings forms the backbone of corporate intelligence used by investors and banks around the world.
Other datasets extend beyond business and law. Sri Lanka’s education system has produced decades of examination papers, curriculum frameworks and student performance data—information that could be used to develop personalized AI learning systems. Land ownership records and property transactions could power digital real estate markets and urban planning analytics.
And then there is the government.
Public institutions collectively hold some of the largest and most powerful datasets in the country: land registries, health records, census information, agricultural statistics and transportation data. Much of this information remains scattered across agencies and, in some cases, still stored in paper archives.
If modernized and securely digitized, economists say, these datasets could unlock a new generation of AI-powered services.
“The government is actually sitting on the most valuable data in the country,” said another technology researcher in Colombo. “If those datasets become digitally accessible, they could fuel an entire AI startup ecosystem.”
For Sri Lanka, the stakes are high. Artificial intelligence is expected to reshape industries from finance and healthcare to agriculture and education. Countries that successfully organize and deploy their data resources may gain a powerful competitive advantage.
For now, the race remains in its early stages. Telecommunications companies are leveraging infrastructure and consumer data, emerging AI platforms are assembling knowledge databases, and policymakers are beginning to explore digital governance frameworks.
But as artificial intelligence becomes central to the global economy, Sri Lanka’s most important technological battle may not be fought over software or hardware.
It may be fought over who controls the data
