AI use cases in behaviour change & social change projects

Artificial Intelligence (AI) is increasingly being incorporated into the way social change and behaviour change projects are researched, designed and implemented. By integrating AI, organisations are finding more efficient and impactful ways to engage communities, tailor interventions, and drive change. Below are some examples of how AI is being applied to projects.

AI-assisted behavioural research and campaigns

At a recent event organised by London School of Economics, Elisabeth Costa shared how the Behavioural Insights Team (BIT) is integrating AI into its research processes. One of their standout innovations is the use of AI-assisted behavioural personas. Developed through a custom GPT, these personas allow researchers to quickly segment their audience, tailoring interventions to the specific needs of different groups. AI helps intervention designers focus their campaigns on the unique behavioural characteristics of each segment.

Costa also discussed how AI chatbots are being used to conduct qualitative research. By replacing human interviewers with AI in sensitive focus groups, BIT discovered that participants felt more comfortable sharing personal or sensitive information, especially on topics like health. Using AI in this way not only broadens the scope of research but also removes potential biases from human-to-human interactions.

Another interesting example that Costa shared was the Argentina COVID-19 vaccination campaign. BIT deployed an AI-powered chatbot to increase vaccination rates by engaging individuals in personalised conversations about vaccine locations, timings, and addressing concerns. The chatbot proved to be four times more effective at increasing vaccination rates compared to traditional text messages. By providing interactive, real-time responses to specific questions, the chatbot helped reduce barriers that lead to vaccine hesitancy.

AI-driven community engagement in India

In Rajkot, India, the Asia Resilient Cities (ARC) project (funded by USAID and implemented by JSI and several partners) leveraged AI-generated images to address urban climate challenges. By using AI-powered visuals, the ARC project helped community members understand the pressing issues of rising temperatures, water scarcity, and waterlogging. These visuals are tailored for local populations, ensuring inclusivity regardless of literacy levels. The use of AI-generated imagery allowed stakeholders to participate more actively in co-creating solutions. Residents, city government officials, and other stakeholders can visualise climate problems, such as urban heat islands, and explore practical solutions like green spaces.

Chatbots for youth reproductive health in West Africa

YUX is developing a generative AI powered chatbot to improve youth reproductive health in West Africa. Accessible through popular platforms like WhatsApp and Telegram, the chatbot provides young people in Senegal, C?te d'Ivoire, and Burkina Faso with culturally relevant information on reproductive health and connects them with healthcare providers.

A key element of this project is its co-design approach. By involving young people in shaping the chatbot’s tone, language, and content, YUX ensures the tool resonates with its audience. This participatory approach leads to higher engagement, making reproductive health information more accessible and less intimidating. Moreover, the chatbot’s continuous development, driven by iterative user feedback, ensures that it remains relevant and impactful in changing health-seeking behaviours.

Expanding the role of AI in social change and behaviour change projects

AI’s potential to drive projects is becoming increasingly apparent. Here are some broader ways AI is set to transform the future of SBC interventions:

1. Scaling interventions at a lower cost

AI allows organisations to scale interventions more efficiently and at a lower cost. Tools such as chatbots, AI-generated content, and automated data collection enable projects to reach larger audiences without significantly increasing operational expenses. This scalability is especially valuable for NGOs and government bodies operating in resource-constrained environments, where resources need to be maximised for impact.

2. Real-time insights and adaptive interventions

AI facilitates the continuous monitoring of interventions, allowing projects to adapt in real-time. For example, health chatbots can adjust their messaging based on user interactions or emerging trends in misinformation. This adaptive capability ensures that interventions remain effective over time, responding dynamically to the needs and concerns of target populations.

3. Bridging cultural and linguistic gaps

AI-driven natural language processing (NLP) tools can operate in multiple languages, making SBC interventions more accessible in multilingual regions. By using culturally relevant content and local dialects, AI can foster trust and engagement within diverse communities. In projects like YUX’s reproductive health chatbot, this capability ensures that interventions are tailored to the specific cultural and linguistic contexts of each region.

Conclusion

AI’s role in social change and behaviour change projects offers exciting opportunities to enhance the design, implementation, and scalability of interventions. As AI technology evolves, it will allow SBC initiatives to become more personalised, adaptive, and capable of addressing a broader range of issues. However, ethical considerations around privacy, data security, and the use of AI in vulnerable populations must remain a priority. Ensuring that AI is used responsibly will be key to achieving positive, sustainable change worldwide.

If you have any more use cases of AI in SBC to share, please do so in the comments!

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