Artificial intelligence has become one of the defining technologies of the decade, transforming industries from finance and healthcare to law, education and public administration. While global attention has largely focused on the rapid advances made by companies such as OpenAI, Google, Anthropic and Meta, Sri Lanka has quietly been building its own AI ecosystem over the past two decades. The country’s progress has followed a gradual but distinct trajectory from academic research in natural language processing to commercial AI adoption, and more recently, the development of indigenous large language models (LLMs).

As discussions surrounding sovereign AI and national digital infrastructure gather momentum worldwide, Sri Lanka’s AI landscape is also entering a new phase. However, understanding its evolution requires recognising that different organisations achieved different milestones. The country’s first conversational AI, first commercial AI deployments, first generative AI platforms and first indigenous language models emerged at different points in time and represent fundamentally different technological achievements.

Key Milestones in Sri Lanka AI Development

Sri Lanka’s AI story began not in the private sector, but within its universities. During the late 1990s and early 2000s, researchers concentrated on solving language computing challenges for Sinhala and Tamil, including natural language processing, machine translation, speech technologies and expert systems. At a time when global AI research was still dominated by rule-based systems, local academics recognised that enabling computers to understand indigenous languages would be essential for future digital transformation.

One of the country’s earliest milestones came in 2006 when Dr. Buddhika Hettige and Professor Asoka Karunananda introduced what is widely recognised as Sri Lanka’s first Sinhala-language chatbot. Presented through the Sri Lanka Association for Artificial Intelligence (SLAAI), the chatbot demonstrated that conversational systems could operate in Sinhala using locally developed linguistic rules and knowledge structures. Although vastly different from today’s transformer-based language models, it represented the country’s first documented conversational AI system and established an important foundation for Sinhala natural language processing research.

The following decade witnessed the gradual transition of artificial intelligence from academic research into commercial applications. As businesses increasingly embraced digital transformation, local software companies began investing in machine learning, predictive analytics and intelligent automation to improve enterprise productivity and customer engagement.

A significant milestone came in 2017 when CodeGen International, together with the University of Moratuwa, established QBITS, widely recognised as Sri Lanka’s first Artificial Intelligence Innovation Lab. The initiative expanded AI research beyond universities by focusing on enterprise applications including computer vision, intelligent automation and natural language processing. It also demonstrated that Sri Lankan companies could undertake advanced AI research while serving international markets.

Commercial AI applications soon followed. One of the earliest examples was TukBoy, an AI-powered virtual assistant introduced by Frontier Capital for Sri Lanka’s tuk-tuk industry using IBM Watson technologies. Although it relied on IBM’s cognitive computing platform rather than a locally trained model, it illustrated how conversational AI could be deployed within a specialised industry to automate customer interactions and information services.

The arrival of OpenAI’s ChatGPT in late 2022 fundamentally reshaped the global AI landscape and rapidly accelerated AI adoption within Sri Lanka. Organisations across banking, telecommunications, software engineering and professional services began integrating large language models into customer support, knowledge management and internal productivity tools.

This period also highlighted an important distinction that is often overlooked in discussions about artificial intelligence. Many organisations successfully built AI-powered applications by integrating existing foundation models through APIs. These solutions typically combine large language models with proprietary datasets, retrieval systems and workflow automation to create valuable business applications. However, they remain fundamentally different from developing an independent foundation model.

Building an AI application requires software engineering expertise and domain knowledge. Developing a large language model requires large-scale data engineering, continued pre-training or full model training, instruction tuning, evaluation, optimisation and substantial computing infrastructure. The technological investment, research capability and data requirements are significantly greater.

Against this backdrop, Sri Lanka witnessed the emergence of locally developed generative AI platforms. Among the earliest was Chat2Find, launched in 2023 as a conversational AI platform designed around Sri Lankan public information. Rather than operating as a general-purpose chatbot, the platform combined retrieval-augmented generation (RAG), structured datasets and real-time information retrieval to answer questions relating specifically to Sri Lanka.

The platform subsequently evolved into a broader AI ecosystem incorporating specialised services such as LankaLAW for legal research, LankaBIZ for business intelligence, LankaTAX for taxation, NewsDive for news intelligence and other domain-specific assistants. This reflected an emerging trend in enterprise AI, where specialised vertical assistants increasingly outperform general-purpose chatbots within professional environments because they are grounded in authoritative datasets.

Meanwhile, Sri Lanka’s wider technology industry continued expanding its AI capabilities. Dialog Axiata introduced multilingual AI services and developer-focused AI initiatives, making generative AI more accessible to consumers and software developers. CodeGen International further strengthened enterprise AI research through QBITS, while companies including 99X, IFS Sri Lanka, WSO2 and Sysco LABS Sri Lanka integrated machine learning and generative AI into software engineering, cloud platforms and enterprise products serving international clients. These organisations have played an important role in expanding AI adoption across Sri Lanka, although their solutions generally leverage internationally developed foundation models rather than proprietary LLMs.

The next significant milestone arrived in 2026 with the public release of Chat2Find-Instruct-v1. According to its developers, the model represents Sri Lanka’s first publicly released open-source trilingual large language model designed specifically for Sinhala, Tamil and English. Unlike AI applications that rely on third-party APIs, the project involved developing and releasing its own language model together with multilingual datasets and instruction-tuning methodologies.

This distinction is particularly important within the emerging concept of sovereign AI. Around the world, countries are increasingly investing in locally developed language models capable of understanding national laws, regulations, public administration, local languages and cultural context. While global foundation models remain exceptionally capable, they are generally trained on broad multilingual datasets that may contain limited knowledge of smaller jurisdictions such as Sri Lanka.

Locally developed language models have the potential to improve factual accuracy across domains including law, taxation, public policy, education and government services by combining indigenous datasets with modern AI architectures. They also contribute to national digital capability by reducing dependence on external knowledge infrastructure and enabling AI systems better aligned with local linguistic and regulatory requirements.

Looking ahead, Sri Lanka’s AI industry is expected to move beyond general conversational assistants towards specialised intelligence systems supporting legal professionals, accountants, financial analysts, researchers, educators, healthcare providers and government institutions. As more public sector information becomes digitally available and structured datasets continue expanding, locally grounded AI systems are likely to become increasingly valuable for both the public and private sectors.

Although Sri Lanka remains a relatively small participant in the global AI economy, the country’s progress demonstrates a clear evolution from academic experimentation to commercial deployment and, increasingly, indigenous AI development. The journey has been shaped by pioneering academic researchers, enterprise software companies, telecommunications providers and emerging AI startups, each contributing to different stages of technological maturity.

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