Language Infrastructure in the AI Era
Artificial intelligence systems increasingly shape how knowledge is produced, accessed, and distributed across societies. At the center of these systems lies language. AI models learn, reason, and communicate through linguistic data, making language infrastructure a critical determinant of who can participate meaningfully in emerging knowledge economies and digital public goods.
Yet the global AI ecosystem remains deeply uneven. A small number of dominant languages benefit from decades of investment in data, institutions, and governance, while many widely spoken languages remain structurally underrepresented. Somali — spoken by more than 25 million people across the Horn of Africa and the global diaspora — is one such language.
What Is the SMRI?
The Somali Model Readiness Index (SMRI) is a structured, evidence-based framework designed to assess how prepared the Somali language ecosystem is to participate in AI systems — not in terms of ambition or aspiration, but in terms of infrastructure readiness.
Rather than asking whether Somali should have a large language model, SMRI asks a more foundational question:
What level of investment, coordination, and governance is required for Somali to participate sustainably and ethically in AI-mediated knowledge systems?
SMRI reframes the future of Somali in AI from one of passive inclusion to intentional participation — grounded in infrastructure, governed by public interest, and aligned with global efforts to build more inclusive knowledge systems.
The Five Pillars of Model Readiness
SMRI evaluates readiness across five interconnected dimensions
Data Availability & Quality
Volume, diversity, and quality of linguistic data available for model training and evaluation
Linguistic Structure & Standardization
Orthographic consistency, grammatical documentation, and terminological standardization
Human Capital & Institutional Capacity
Availability of linguists, translators, researchers, and institutional support systems
Governance, Stewardship & Ethics
Frameworks for data rights, community consent, and long-term resource stewardship
Technical Integration & AI Engagement
Current presence in AI systems, technical tooling, and engagement with research communities
Holistic Assessment
All pillars interconnected
Somali Baseline Assessment (2025)
Current state of readiness across all pillars
Strengths
- Linguistic Structure: Well-documented grammar and post-1970s standardization success
- Human Capital: Active translator, educator, and researcher networks
- Language Vitality: 25M+ speakers across Horn of Africa and diaspora
Gaps & Constraints
- Data Infrastructure: Limited structured, machine-ready datasets
- Governance: Absence of coordinated stewardship mechanisms
- Technical Integration: Early-stage engagement with AI systems
Key Finding: Somali demonstrates emerging readiness in linguistic structure and human capital, but remains early-stage in governance, stewardship, and technical integration — areas that determine whether language data can be responsibly reused, scaled, and sustained.
Implications for Action
For Policymakers
Treat language infrastructure as a strategic public good in the digital era, requiring long-term institutional investment
For Development Partners
Invest in foundational capacity building rather than premature model deployment for sustainable impact
For AI Labs & Universities
Engage ethically with underrepresented languages based on readiness assessment rather than data extraction
SMRI as a Living Index
This first edition establishes a baseline, not a verdict. It provides a shared vocabulary, a transparent framework, and a starting point for collective action.
Transparent Framework
Track Progress Over Time
Refine Indicators
Future editions will refine indicators, incorporate new data, and track measurable progress as Somali's language infrastructure develops.
Explore the Full SMRI Report
The Somali Model Readiness Index provides a roadmap for intentional, infrastructure-driven participation in the AI era.