‘An initiative by the Schwab Foundation’s Global Alliance for Social Entrepreneurship [is] charting pathways to the responsible adoption of AI for impact (…) The AI for Social Innovation initiative is a collaborative project between social innovators and technology leaders. It encourages dialogue between technology leaders and social innovators to inform the technology roadmap, mobilises resources for the impactful application of AI for impact and builds capacity amongst the ecosystem. It works across three major pillars:
- Informing tech leaders: Insights and case studies from social innovators to influence the tech roadmap and responsible adoption.
- Training and capacity building: Equipping the social innovators with the tools and knowledge to understand and adopt artificial intelligence.
- Resource mobilisation: Facilitating financial and in kind support to promote the increased adoption of AI by social innovators.’ (Source: WEF)
AI for Social Good in Asia and the Pacific
‘UN ESCAP (Economic and Social Commission for Asia and the Pacific) and the Association of Pacific Rim Universities (APRU), with support from Google, developed the ‘AI for Social Good’ multi-stakeholder network. The network is supporting policymakers by developing insights on what capabilities and governance frameworks will be most supportive for leveraging AI effectively for social good (…) The AI for Social Good multi-stakeholder network was initially set up in 2019 as a platform that convenes leading experts from the region to explore opportunities and challenges for maximizing AI benefits for society.’ (source: ESCAP) Outcomes include several publications such as a series of the Artificial Intelligence for Social Good reports.
The Landscape Report on Artificial Intelligence in Social Innovation
‘Artificial Intelligence (AI) is revolutionizing every facet of business and life, thanks to the accelerated development of generative AI, which has made the technology widely accessible. For social innovators, the ethical adoption of AI in their business models and/or to streamline their operations represents a unique opportunity to maximize their impact. The social economy represents 7% of global GDP, and generative AI could add between $182 billion and $308 billion in value annually to the sector. How can social innovators better understand, access and deploy this technology?’ (source: WEF). ‘The Landscape Report on Artificial Intelligence in Social Innovationhighlights the current landscape of AI in social innovation, its prevalence, opportunities, and challenges. The report draws on insights from an extensive dataset of 300 social innovators spanning over 50 countries as well as 90 initiatives forming the ecosystem of AI for social innovation. Its analysis uncovers a nearly equal representation of AI applications across high-income and lower-income regions, underscoring AI’s universal potential to tackle diverse societal issues. The report features 300 social innovators who already apply Artificial Intelligence for impact purposes. 90 ecosystem initiatives, conferences and publications are mapped to highlight their geographic diversity and impact on the UN SDGs.’ (Source: WEF)
AI for Social Good Guide
This data.org’s (Google AI) guide introduces organizations to AI for social impact, sharing examples of work to illustrate the potential. The report, full of concrete examples, states: ‘As AI redefines what’s possible, it also creates new ways to be helpful (…) AI can be applied in ways that benefit humanity. Our mission is to demonstrate AI’s societal benefit by enabling real-world value, with projects spanning work in accessibility, science, education, economic impact, and society. We believe that the best way to drive positive change in underserved communities is by partnering with change-makers and the organizations they serve.’ (source: Google AI). The report covers a range of good practice case studies on using AI for social innovation in access, climate, economic opportunity, government innovation, healthcare, learning and education, science.
IBM Sustainability Accelerator for AI-powered social innovation
‘Technologies like Generative AI and AI Agents are poised to change the way we interact with urban environments and tackle economic and environmental challenges. Today, five new AI projects are ready to take on cities’ biggest challenges. Over the next three decades, our world is projected to continue to urbanize. In fact, the share of people living in urban areas will increase from 56 percent (2021) to 68 percent by 2050, according to UN Habitat. While urbanization poses a range of challenges for city governments, services, and communities to overcome, the growth of urban populations and urban areas also reveals an opportune moment to accelerate social innovation and uplift urban economies. Tailored tech solutions, offering highly curated insights, can be leveraged to help deploy the right resources in the right places. That’s a call to action that the power of AI and data can help us catalyze.
At the beginning of 2024, and in alignment with United Nations Sustainable Development Goal 11, IBM launched a request for proposals (RFP) for projects that aim to make cities safer, more resilient and more sustainable. Today, out of more than 100 applications, five new organizations have been selected to join the IBM Sustainability Accelerator and collaborate with IBM experts on AI solutions to address key challenges for — and with — the communities they support. Participants were selected for their significant level of support to the communities they serve, as well as the innovative ways each organization plans to leverage AI technology to build more resilient cities.’ (source: IBM). Some of these projects are presented in the recent IBM article on AI for social innovation in building resilient cities.
‘The IBM Sustainability Accelerator is a social innovation program that applies IBM technologies, such as hybrid cloud and AI, and an ecosystem of experts to enhance and scale non-profit and government organization initiatives, accelerating economic impact. Projects are executed in two phases, starting with the IBM Garage, IBM’s proven methodology for accelerating digital transformation and delivering meaningful, measurable, outcomes. Next, during the Development and Implementation phase, IBM experts will configure IBM resources and technology to help participants meet their goals. As part of this IBM Sustainability Accelerator cohort, EY teams will provide general capacity building workshops and coaching to the resilient city cohort, supporting these innovative organizations on their mission to make cities more sustainable, equitable, and resilient.’ (source: IBM).
Data: the key element for leveraging AI for social innovation
The recent Stanford Social Innovation Report online article by Nithya Ramanathan & Jim Fruchterman (Feb. 19, 2025) titled “Gather, Share, Build – Why data is one of the biggest challenges to leveraging AI for social good—and how the social sector can address it” tackles the question of why AI is not yet optimally used for social innovation. The article (full text can be found here) reads:
Recent milestones in generative AI have sent nonprofits, social enterprises, and funders alike scrambling to understand how these innovations can be harnessed for global good. Along with this enthusiasm, there is also warranted concern that AI will greatly increase the digital divide and fail to improve the lives of 90 percent of the people on our planet. The current focus on funding AI intelligently and strategically in the social sector is critical, and it will help ensure that money has the largest impact. So how can the social sector meet the current moment? AI is already good at a lot of things. Plenty of social impact organizations are using AI right now, with positive results. Great resources exist for developing a useful understanding of the current landscape and how existing AI tech can serve your mission, including this report from Stanford HAI and Project Evident and this AI Treasure Map for Nonprofits from Tech Matters. While some tech-for-good companies are creating AI and thriving—Digital Green, Khan Academy, and Jacaranda Health, among many—most social sector companies are not ready to build AI solutions. But even organizations that don’t have AI on their radar need to be thinking about how to address one of the biggest challenges to harnessing AI to solve social sector problems: insufficient data.’ (source: Ramanathan & Fruchterman, 2025). We encourage you to read this thought-provoking piece here.
AI-powered non-profits in climate, health and education
Another read from the SSIR, a series worth reading is titled “Introducing AI-powered Non-Profits“. ‘AI-powered nonprofits (APNs) are deploying artificial intelligence in creative, powerful, and rapidly changing ways. Despite operating in disparate issue areas, APNs around the world are following similar patterns of innovation. Most excitingly, all of them are scaling their human impact at an unprecedented pace.“Introducing AI-Powered Nonprofits,” presented in partnership with Fast Forward, is inspired by a quest to understand precisely how nonprofits are leveraging AI today. The series begins with an overview of the current APN landscape, then explores the groundbreaking work of nonprofits in three key sectors: climate, health, and education. By spotlighting these vanguard organizations and providing a landscape to better understand their work, Fast Forward and their partners aim to inspire more innovators toward AI for humanity. While technological advancement often overlooks the needs of the most vulnerable, we see a need to prepare nonprofits and civil society for transformations stemming from AI. The more we provide support for all communities to explore, understand, and build with AI tools, the better equipped we will be to create a human-centered future that meets the needs of everyone.’ (source: SSIR)
A critical look at AI and its challenges and negative impact
Besides multiple opportunities that AI offers for social innovation, it would be naive to not notice the negative sides. From the social issues with Intellectual Property ownership problems to the massive use of energy and water that large data centres and AI operations require, AI-powered technologies have potentially very high negative impacts. An interesting set of articles on AI, not shying away from some of the troublesome aspects of AI, are continuously presented on Impakter. Impakter, initially active as Impakter Magazine, now ‘Impakter informs you through the ESG news site and empowers your business CSRD compliance and ESG compliance with its Klimado SaaS ESG assessment tool marketplace’. You can check out the whole Impakter platform here.
Learn more at Social Innovation Academy
Social Innovation Academy is the first fully online management training programme focusing exclusively on social innovation.
Why Social Innovation Academy? Social innovation has increasingly come to be perceived as the answer to the rising number of European societal challenges. While the European authorities, leading academics, policy experts, business people and activists agree that social innovation is the key to a better future for Europe and the world, it is extremely difficult for professionals to obtain high-quality training on what social innovation actually offers and, more importantly, how it can be done in practice.
The Social Innovation Academy is aiming to change this situation in Europe and beyond. If you are interested in keeping up with this project, you can subscribe to our newsletter, become one of our friends or follow us on social media (LinkedIn, Twitter and Facebook). We welcome all requests for collaboration here.
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