By Satender Rana, Project Lead – ISDM DataShakti, Indian School of Development Management – ISDM
Artificial Intelligence (AI) is making a significant impact on the social sector worldwide. There is an increasing interest and involvement also seen from major technology companies to support social purpose organisations (SPOs). For instance, Google.org launched a Generative AI Accelerator in 2024, supporting 21 SPOs in creating generative AI-powered solutions that aim to benefit over 30 million people by 2028.
Globally, irrespective of whether SPOs currently use the AI technology or not, believe that AI could be helpful in the future, reports Google.org. India’s social sector is also embracing the AI with remarkable growth in AI-driven social innovations. For instance, a report by the World Economic Forum (WEF), ranked India second globally in AI deployment by social innovators. However, the divide in the usage of technology, scepticism, and challenges looms large.
A study by GivingTuesday reports while 68% of respondents in their study have experimented with AI, there is significant skepticism. The study indicates that 54% of AI users are worried about bias, and 56% are concerned about data breaches. Interestingly, individuals in the tech and MERL sectors exhibit more apprehension about these risks compared to their non-technical counterparts.
Furthermore, smaller SPOs are being left behind. Digitally mature and larger SPOs are actively experimenting with AI while smaller organisations often rely on external tech enablers, and avoid AI due to cost, capacity, or ethical concerns, reports Pacta, a Bengaluru-based law firm. This creates a digital divide within the sector. GivingTuesday report that although comfort with AI is higher in India compared to the global average, the country’s readiness—assessed by policy frameworks, infrastructure, and the range of applications—is lower than the international average.
Only 1 in 3 respondents in Google.org study highlighted strategic use of the technology such as program design. On the other hand, most Indian SPOs are using AI for low-risk, programmatic tasks like content, reports Pacta, suggesting that deeper AI integration is still rare.
For organisations currently utilising generative AI at any level, the primary challenge that hinders SPOs’ ability to leverage generative AI in their operations is inability to select and implement AI resources and tools. Organisations that are not using AI at all often cite a lack of familiarity with the technology as a significant barrier. Moreover, financial constraints are another major obstacle.
However, research points out that AI adoption in the social sector isn’t just about resources—it’s about mindset, staffing, and strategic intent. Therefore, the mindset of SPO leaders—whether optimistic, cautious, or skeptical—plays a critical role in AI adoption.
Access to high-quality and usable data is essential for developing AI tools like AI-based automation. However, lack of well-organised and open datasets, and inconsistent data standards is a challenge in social sector. These issues make it difficult to build reliable AI systems that can effectively process and analyse information, reports Pacta. Investments in AI-enabled open access data platforms can provide long-term sustainable access to high quality datasets.
For SPOs, two key lessons emerge. First, as the Data Maturity Assessment (DMA) study by the Centre for Data Science and Social Impact (CDSSI) at ISDM reports, it’s important to ask critical questions about data maturity, ownership, potential biases, and unintended consequences before committing to any tool. Second, it’s wise to start with small-scale, low-risk applications that address current operational needs, rather than pursuing high-profile, cutting-edge projects.
Moreover, SPOs cannot progress alone. Funders need to provide sustained financial support for long-term investments in data infrastructure, skills development, and ethical frameworks.
India’s social sector stands at a pivotal moment. It’s important for stakeholders to move beyond the hype and focus on responsible innovation. As the DMA study emphasises the importance should be given to building a solid data foundation. If SPOs, funders, and tech enablers collaborate, AI can become more than just a tool for efficiency—it can drive inclusion, empowerment, and sustainable change in India’s social sector.