Influence of Scalable AI: Foundations, Business Models, and Impact Pathways

GSMA EmergingTech Programme The GSMA is a global organisation unifying the mobileecosystem to discover, develop and deliver innovationfoundational to positive business environments and societalchange. Our vision is to unlock the full power of connectivityso that people, industry and society thrive. Representingmobile operators and organisations across the mobile The GSMAEmergingTech programmeaccelerates impactand climate action by fostering the adoption of AI andemerging technologies in low- and middle-income countries (LMICs) by working with public, private and third sectorinnovators to develop scalable and sustainable solutions To get in touch with the Emerging Tech team, please email:emergingtech@gsma.com We invite you to find out more atgsma.com ||y This material has been funded by UK InternationalDevelopment from the UK government and is supported by Author:Ibrahim Sajid (GSMA Mobile for Development) Acknowledgements: We would like to thank the many individuals andorganisations that contributed to this research. This includesEY,World Food Programme,World Bank,UNDP,GlobalPartnership for Sustainable Development Data (GPSDD),Tony Blair Institute,GenAI Fund,Rwanda Ministry of ICT andInnovation,Mozilla,Earth VC,KenCorpus,Gooey.ai,&frnds,InvestEd,Wysa,Niramai,Gringgo,LifeBank,SmartTerra,Kissan AI,Varaha,Khushi Baby,Trestle Labs,Cropin,Lengo,Jacaranda Health,Orca,Digital Green,Simprints,Kitovu,Husk Power Systems,Amini,Omdena,Ignitia,Glific, This document has been financed by the Swedish InternationalDevelopment Cooperation Agency (Sida). Sida does not Published April 2026 The report has been produced in partnership with DalbergAdvisors, a strategic advisory firm that works collaborativelyacross the public, private and philanthropic sectors to drive Contents Acronyms and abbreviations  Definitions Introduction Data: the foundation of impactful AI The spectrum of impactful dataNavigating the data acquisition labyrinthData scarcity and fragmentation The technological building blocks for scalable impactCommon technical architectural patternsThe role of open source and foundation models Spotlight 1:GOOEY.AI Sustainable business models for impactful AIDominant themes in go-to-market strategies The role of mobile in the AI revolutionMobile technology: the indispensable delivery channel Spotlight 2: Knowledge Platform (Eneza Education)The value add: the transformative capabilities of AIPoints of intervention: where AI creates valueHow AI adds valueTiers of impact Definitions Introduction Across low- and middle-income countries(LMICs) in Africa, South Asia and SoutheastAsia, AI has the potential to address systemicchallenges in health, agriculture, climate, energyand economic development. This report isthe second of a two-part series that presentscross-cutting lessons from innovators andexperts working at the intersection of technologyand development(see Annex 1 and 2). Building emerging technologies (e.g. mobile big data, IoT,remote sensing, computer vision, blockchain anddrones) alongside mobile technologies to solve The report also presents considerations forinnovators and ecosystem enablers, primarilygovernments, global tech companies, mobilenetwork operators (MNOs), donors and The analysis reveals a maturing ecosystem inwhich deep localisation, hybrid AI approaches andhuman-AI symbiosis are enabling AI to augment,rather than replace, the capabilities of frontlineworkers and institutions. Within this ecosystem,innovators in LMICs are overcoming the challengeof data scarcity in creative ways, embeddingdata collection in user-centric design and This report is aimed at solution providers,including startups, social enterprises andnonprofit organisations, that are developing Data: thefoundation ofimpactful AI Impactful AI begins with data that reflects the local context. In LMICs, however, the datasets that mattermost are often incomplete, fragmented or locked in analogue systems, constraining the development ofreliable and equitable digital solutions. For innovators, the priority is not just the volume of data but thestrategic acquisition, management and use of diverse, high-quality, context-rich data sources. To closethis gap, they are assembling practical data pipelines – using mobile channels to reach last-mile users;Internet of Things (IoT) and edge devices to sense and structure real-world signals; and remote sensing The spectrum of impactful data Innovators are leveraging an array of data types to buildcontext-specific solutions. This diversity reflects a creative Agricultural and environmental data AI for impact FarmerChat by Digital GreenPage 27 To learn more aboutthe work of theseinnovators, read the case FarmerChat by Digital Green draws insights from curated datasources, including advisory videos, call centre logs, digitalisedtraining manuals and farming guides, weather data from VarahaPage 35 Varaha continuously collects region- and crop-specific data tore