diniscruz.ai / writing

Portuguese as a Programming Language in the AI Era

By Dinis Cruz and ChatGPT Deep Research · · 18 min read

PDF

Contents · 6 sections
  1. Context and Importance
  2. Language as the New Programming Paradigm
  3. The Case for Portuguese: Data and Impact
  4. Strategic Actions to Prioritize Portuguese in AI
  5. Policy and Industry Recommendations
  6. Conclusion and Call to Action

Context and Importance

A Global Language at a Crossroads: Portuguese is one of the world’s most widely spoken languages, with roughly 260–270 million speakers spanning Europe, South America, Africa, and Asia. It consistently ranks among the top six languages globally by number of speakers (10 Fascinating Facts About the Portuguese Language), and is the third most spoken European-origin language (after English and Spanish).

As the official language of nine countries and a working language in multiple international organizations, Portuguese wields significant cultural and geopolitical influence. In economic terms, the Lusophone (Portuguese-speaking) world collectively accounts for about $2.5 trillion in GDP (Community of Portuguese-Speaking Countries(Source：MOEA)) – roughly on par with the world’s largest economies – underscoring its market potential and strategic importance.

Language in the Age of AI: Advances in Large Language Models (LLMs) and Generative AI (GenAI) have transformed human language itself into a powerful computing interface. Today, writing a prompt in natural language can execute complex tasks, blurring the line between coding and everyday speech. In effect, language has become a new form of programming. As NVIDIA CEO Jensen Huang recently observed, with modern AI “the programming language is human”, enabling anyone to instruct computers in plain English (Nvidia CEO predicts the death of coding — Jensen Huang says AI ...). This paradigm shift – sometimes summed up as “English is the new programming language” (Thanks to AI, the Hottest New Programming Language is... English) – carries profound implications: those languages best represented in AI will shape the future of technology and information flow.

Yet, who benefits from this revolution? So far, the lion’s share of AI development has centered on English, creating an emergent asymmetry. Portuguese (along with many other languages) risks being left behind if AI systems are not taught to understand and “code” in it. The ability for Portuguese speakers to interact with AI in their native language is not just a matter of convenience – it is about inclusive access to technology, preservation of cultural-linguistic heritage, and equity in the digital economy. In this context, investing in Portuguese within AI is both a strategic opportunity and a necessity to ensure that the LLM era does not become a one-way street favoring English alone.

(Note: While this paper focuses on Portuguese as a case study, the insights and arguments apply to all European languages. Ensuring linguistic diversity in AI is a pan-European imperative.)

Language as the New Programming Paradigm

From Code to Conversation: Traditional software programming required learning specialized syntax and languages (Python, Java, C++, etc.). Today, with GPT-style LLMs, any well-structured prompt in natural language can function as a program, executing queries, generating content, or controlling devices. AI systems now interpret instructions, answer questions, and solve problems given in plain speech. This represents a seismic shift: interaction in natural language is becoming the default user interface for computing tasks. In practical terms, one can “write” an application by simply telling an AI what to do – a concept often described as prompt engineering or zero-shot programming. The rapid improvement of models (e.g. GPT-4, PaLM, Llama) has shown that carefully crafted English prompts can yield sophisticated outcomes that once required coding.

The English-First Bias: Current LLMs have largely been trained on massive English datasets, meaning English enjoys a first-mover advantage as the de facto programming language of AI. Complex prompt techniques, knowledge repositories, and even documentation for AI models are predominantly in English. As a result, an English-speaking user can leverage AI with greater precision and reliability today than a user issuing instructions in Portuguese (or Polish, or French). Research indicates that AI tools trained on internet data risk widening the gap between speakers of “data-rich” languages and others (How language gaps constrain generative AI development). In other words, if AI understands English best, English speakers reap disproportionate benefits, and global linguistic diversity may be subtly eroded (How AI threatens linguistic diversity - Opinion - Chinadaily.com.cn). This is not a mere academic concern: language bias in AI could translate into fewer services, less information, and diminished economic opportunities for those operating in languages outside the AI mainstream.

Portuguese as Code: The solution is clear – equip Portuguese to stand alongside English as a programming medium for AI. We must develop AI models that think and operate in Portuguese with the same fluency and capability that today’s top models demonstrate in English. This goes beyond basic translation. It means training AI to accurately grasp Portuguese idioms, context, and nuance; to access and output knowledge stored in Portuguese; and to allow Portuguese instructions to accomplish anything an English instruction could. In essence, LLMs should treat Portuguese as an equal “first-class” language for interfacing with technology. When a Portuguese policymaker can query a national AI system in Portuguese and get a detailed policy brief, or a Brazilian entrepreneur can prototype an app through Portuguese prompts, we will have achieved parity. The tools are within reach – the latest generation of LLMs are inherently multilingual – but concerted effort is needed to optimize and localize them. Just as English became the initial programming language of AI by virtue of data dominance, Portuguese (and other European languages) can become languages of AI by deliberate investment and strategic focus.

The Case for Portuguese: Data and Impact

To understand why prioritizing Portuguese in AI makes sense, consider the following key facts and figures about Portuguese in the world today:

Impact of Investment: Investing in AI for Portuguese means unlocking this potential. It means an Angolan student can use a tutoring chatbot that understands her language and context; a Brazilian doctor can consult a medical AI trained on Portuguese case studies; a Portuguese journalist can quickly search vast Portuguese archives via an AI assistant. The social impact (greater inclusion, literacy, services access) and economic upside (new markets, improved efficiency, local AI industry growth) are substantial. In short, the data paints a clear picture: Portuguese is too globally important to ignore in the AI era. Any nation or business strategy that values scale, inclusivity, and long-term relevance should treat Portuguese-language AI competence as a strategic priority.

Strategic Actions to Prioritize Portuguese in AI

Ensuring that Portuguese thrives as a “programming language” of AI will require coordinated effort across government, industry, and academia. Below are key strategic actions and initiatives that stakeholders should undertake:

1. Invest in Native AI Models and NLP Tools for Portuguese

Build AI by and for Portuguese speakers. The foundation of language-enabled AI is data and models. Governments and enterprises should invest in creating large-scale Portuguese language models – from foundational LLMs to specialized tools – rather than relying solely on translations of English-centric systems. Notably, multilingual models exist, but dedicated Portuguese models can achieve higher fidelity. For example, the BERTimbau project produced a state-of-the-art Portuguese NLP model that outperformed multilingual BERT on Portuguese tasks ((PDF) BERTimbau: Pretrained BERT Models for Brazilian Portuguese), underscoring the value of native-language AI research. More recently, a consortium of Portuguese researchers announced AMÁLIA, the first large-scale Portuguese-only LLM, with a planned release by 2026 (Final version of Portuguese large language model launched in 2026). Such efforts should be accelerated and expanded. Key investments include:

Investing in homegrown models not only improves performance for Portuguese users, but also secures technological sovereignty – reducing dependence on foreign AI providers and ensuring local control over data and ethics. It sets the stage for Portugal (and Lusophone partners) to export AI solutions to other language markets, turning a linguistic asset into a competitive advantage.

2. Foster Open-Source Collaboration and Government AI Initiatives

Leverage the power of community and public support. Open collaboration has proven immensely successful in AI – the best example being BLOOM, a 176-billion-parameter open model that can generate text in 46 languages (including Portuguese) and was produced by a global volunteer effort (BLOOM - BigScience). Portugal and other Portuguese-speaking countries should actively participate in and initiate open-source AI projects centered on language. This includes contributing to international projects and launching dedicated programs for Portuguese.

Governments play a catalytic role here. Policy makers should back open research and infrastructure for AI in Portuguese. This could mean funding a “Portuguese AI Commons” – open datasets (e.g. the BrWaC web corpus with billions of words), open models, and APIs that startups and researchers can use. It also means adopting favorable policies: for example, requiring that publicly funded AI research be open-source, and encouraging data sharing agreements (while respecting privacy) so that Portuguese language data from libraries, media, and academia can fuel AI development.

There are positive precedents to build on. The European Union’s Digital Europe Programme emphasizes multilingual AI technologies and could support Portuguese projects (eLangTech: The EU's Multilingual toolset - Nimdzi). The European Language Equality roadmap aims for full digital language equality by 2030 (European Language Equality) – a vision that aligns perfectly with boosting Portuguese in AI. Portugal’s national AI strategy (“AI Portugal 2030”) can integrate language objectives, ensuring that resources are allocated to NLP and that Portuguese is well-represented in European AI initiatives. Collaboration should also extend to the Community of Portuguese Language Countries (CPLP) – a united effort among Lusophone nations to share data, talent, and applications (for example, building a common Portuguese AI translation system or a joint research center). By pooling efforts in an open, transparent manner, the Portuguese-speaking world can punch above its weight in the AI arena, producing tools that benefit all and are freely available. Open-source also invites global talent: researchers from anywhere can contribute to Portuguese AI, and Portuguese contributions to multilingual projects will raise the language’s profile in the AI community.

3. Build AI-Driven Knowledge Graphs and Semantic Systems

Connect the Portuguese knowledge universe. A language is not just grammar and vocabulary – it’s a repository of knowledge. One strategic move is to construct comprehensive knowledge graphs and semantic databases for Portuguese information. These are structured networks of facts and concepts (people, places, events, terms) and their relationships, which AI can query to retrieve reliable answers. Imagine an AI that can answer a question like “What were the economic effects of the 1755 Lisbon earthquake?” by consulting a Portuguese knowledge graph that links historical records, economic data, and scholarly research – all in Portuguese. This is possible if we invest in the creation of such semantic infrastructure.

Projects could include:

By building these semantic assets, we augment the “brain” of AI with Portuguese context. It ensures that AI systems not only speak Portuguese, but truly understand the world through Portuguese. This is key for governmental use (e.g. policy intelligence systems that parse Portuguese policy documents) and for businesses (e.g. semantic search in Portuguese for enterprise data). Such knowledge graphs can be built through partnerships between universities, libraries, and tech companies, supported by government grants. Over time, this creates a virtuous cycle: as AI uses the knowledge graph, it can also help expand and refine it, leading to continuously improving Portuguese knowledge accessibility.

4. Support Portuguese-Based AI Startups and Innovation Hubs

Cultivate an ecosystem of innovation. The entrepreneurial community will be instrumental in turning language AI capabilities into real-world applications. We need to empower startups and tech companies focusing on AI solutions for the Portuguese-speaking market. This can be achieved through a mix of incentives, funding, and incubator programs:

By supporting startups, we also create local expertise and high-value jobs. Rather than a brain drain where top AI talent leaves for Silicon Valley, a vibrant local market will keep Portuguese AI engineers and researchers engaged at home, or even attract foreign talent interested in multilingual AI. Over time, a successful cohort of AI companies focusing on Portuguese can expand globally – exporting their tech to other language markets – thus turning an initial focus on linguistic inclusion into a competitive export advantage.

In summary, these strategic actions – investment in models, open collaboration, semantic systems, and startup support – form a comprehensive approach. They attack the challenge from all sides: technology, data, knowledge, and market deployment. The coordinated execution of these steps by government agencies (through funding and policy), by academic institutions (through research and training of talent), and by the private sector (through innovation and scaling) will establish Portuguese as a first-class citizen in the AI universe.

Policy and Industry Recommendations

To operationalize the above strategy, we present targeted recommendations for different stakeholder groups. These concrete proposals aim to integrate Portuguese deeply into AI frameworks and ensure sustained support:

By following these recommendations, each stakeholder contributes to a holistic ecosystem where Portuguese is thoroughly integrated into AI development cycles. The government ensures resources and a favorable environment; industry drives application and scale; and the tech community pushes the boundaries of what’s possible. This multi-pronged collaboration is crucial – no single actor can achieve language parity in AI alone, but together it’s attainable.


Conclusion and Call to Action

A Future Worth Building: Portuguese is at a pivotal moment in the AI and LLM era. The choices made now will determine whether it flourishes as a digitally empowered language or gets sidelined in favor of more dominant tongues. The evidence and arguments presented here make a compelling case that investing in Portuguese for AI is both strategically wise and morally sound. It is an investment in people – the hundreds of millions who speak Portuguese and deserve technology that understands them. It is an investment in innovation – unlocking new solutions and markets by leveraging a great world language. And it is an investment in diversity – reinforcing a future where AI reflects the rich tapestry of human language and culture, rather than homogenizing it.

The call to action is clear: policy makers, entrepreneurs, researchers, and media influencers must recognize language as the backbone of AI innovation. We urge governments in Portuguese-speaking nations and the EU to treat language equality as a tech priority, committing to the necessary funding and frameworks. We urge companies and startups to seize the Portuguese opportunity – those who do so will not only access a large market but also set themselves apart as leaders in a less crowded space. We urge the AI community to champion multilingual and open approaches, so that breakthroughs in AI benefit all languages, not just a few.

The era of “English-only” AI is already evolving. In the coming years, as projects like Europe’s language equality roadmap drive progress (European Language Equality), we can expect a landscape where interacting with AI in Portuguese (or Spanish, French, German, etc.) is just as seamless as in English. Achieving this will require dedication and collaboration, but the reward is enduring: a world in which technology empowers individuals in their own language, and where Portuguese, with its history, vitality, and global reach, stands as a fully enabled programming language of intelligent machines.

Now is the time to act and shape that future. Portuguese has given poetry, knowledge, and connection to the world for centuries; let us now give it a prominent place in the AI revolution. By doing so, we not only honor the linguistic heritage of millions but also unleash the full potential of AI to serve humanity in all its diversity. This is a call to invest, innovate, and include – so that the next chapter of the digital age is written em português.

Released under CC BY 4.0. First published on docs.diniscruz.ai; this page as markdown.

← O2 Platform's MethodStreams (2010 Open Source SAST engine)Generative AI and the Future of Learning →