GSMA Innovation Fund for Impactful AI

Artificial intelligence (AI) and other emerging technologies have the potential to contribute to the United Nations Sustainable Development Goals (SDGs) and climate action by bringing innovative approaches to inclusive and sustainable development where it is most needed.

While these technologies are already being deployed across many low- and middle-income countries (LMICs), there is not enough evidence of solutions that address the unique and pressing socio-economic and climate challenges of these contexts.  

The GSMA Innovation Fund for Impactful AI will provide grants and venture building support to small and growing enterprises that leverage AI and other emerging technologies, in conjunction with mobile technology, to have a positive impact on the lives of people in LMICs. The fund is interested in solutions that demonstrate the transformative impact of innovative AI and supporting emerging technologies to tackle socio-economic and climate-related challenges. 

What types of projects are we looking for?  

Please note that the examples and sectors mentioned below are for illustrative purposes only. 

Projects with a focus on predictive and/or generative AI innovations that show promise to scale and generate positive socio-economic and/or climate-related impacts.  

Examples include: (1) early warning systems that predict extreme weather events using historical weather data to guide resilience strategies and resource allocation; or (2) a conversational chatbot that understands farmers’ questions in their local language and offers real-time personalised advice by accessing datasets on agricultural knowledge and best practices.  

Projects that clearly outline how emerging technologies (machine learning, computer vision, Internet of Things (IoT), remote sensing, drones, blockchain, etc.) are contributing to the deployment of AI-driven products and services. 

Examples include:  

Machine learning: an AI model that can be used to train drones to navigate forest areas autonomously, detect and report illegal activities and environmental anomalies and make real-time decisions, such as prioritising areas based on risk assessment. 

Computer vision: an AI model that can analyse X-rays, CT scans or MRIs to diagnose diseases like tuberculosis, pneumonia and even breast cancer in underserved communities.  

IoT: an AI model that can be trained to monitor battery health, solar panel output and track household energy consumption patterns for off-grid rural households to manage renewable energy flow, ensuring efficient energy storage and steady power supply. 

Remote sensing: remote sensing via satellite imagery and/or drones that can be used to collect data on water temperature, turbidity and algal blooms in aquaculture ponds. The data can be fed into an AI model to analyse and predict water quality issues.  

Blockchain: credit scoring for the unbanked. Blockchain can securely store alternative credit data (e.g. mobile payment history, utility bills, crop yields). This data can then be analysed by AI models to generate credit scores for individuals without traditional financial histories.  

Projects across the AI ecosystem 

Business-to-consumer (B2C) examples include: (1) AI-driven personalised learning platforms providing accessible education to children and supporting educators in remote or underserved areas; (2) AI-based remote disease diagnosis of vulnerable communities with lack of access to proper healthcare facilities.  

Business-to-business (B2B) examples include: (1) development of large language models (LLMs) to train local language chatbots to provide information on various topics like healthcare, farm management and education; (2) development of multimodal LLMs, integrating satellite imagery, weather data and local indigenous knowledge for precision farming; (3) edge-enabled soil sensors to monitor soil health and moisture to optimise irrigation, ensuring efficient water usage in regions facing scarcity; and (4) using big data speech patterns to train models that enable voice-based interaction for illiterate users or users speaking low-resource languages, providing access to digital services. 

For more information about the eligibility criteria and the program please check the terms and conditions of the program.