Reported by Simon Daniel Yusuph l Journalist at Weng Global
African nonprofit organisations can use artificial intelligence (AI) to expand access to essential services, strengthen programme delivery and address challenges in healthcare, education, agriculture and livelihoods, according to a new report by The Bridgespan Group.
The report, titled Pursuing the Promise of AI: A Guide for African Nonprofits to Advance Their Missions, examines how nonprofit organisations and social enterprises across Africa can adopt AI responsibly to improve their work and reach more people.
Released in October 2026, the research draws on interviews and discussions with more than 40 nonprofit organisations, social enterprises, funders, experts and intermediaries working across different sectors on the continent. It explores how organisations can identify suitable AI applications, test their effectiveness, integrate successful initiatives into their programmes and determine whether expanding their use would deliver sustainable benefits.
The report comes as AI tools become increasingly accessible to organisations seeking new ways to improve efficiency and service delivery. However, it highlights a gap between the widespread interest in the technology and its direct use to strengthen programmes serving communities.
According to The Bridgespan Group, many organisations have started using AI for routine administrative and productivity tasks, but relatively few have incorporated it directly into the delivery of their core services.
The research therefore encourages nonprofit leaders to focus on the problems they need to solve rather than adopting AI simply because the technology is attracting attention.
Report Urges Nonprofits to Prioritise Their Missions
The Bridgespan Group’s findings emphasise that successful AI adoption should begin with an organisation’s mission, operational needs and the communities it serves.
Rather than treating AI as an objective in itself, nonprofit leaders are encouraged to establish whether the technology can produce measurable improvements in their work.
Madhuri Mukherjee, a Bridgespan partner and co-author of the research, said organisations should look beyond technology and consider their data, workforce, governance arrangements and the needs of the communities at the centre of their programmes.
Her position reflects the report’s central argument that AI adoption requires more than purchasing software or introducing new digital tools.
Organisations must first understand the challenges they face, assess whether AI is an appropriate solution and determine whether they have the resources and expertise needed to implement it responsibly.
For an organisation working in education, for example, the priority might be improving access to learning resources or helping teachers manage administrative responsibilities. A health-focused nonprofit might investigate whether AI could support the analysis of programme information or improve the coordination of services.
An agricultural organisation could examine whether suitable AI applications might help it process information used in farmer-support programmes.
These are potential applications rather than evidence that every organisation can achieve such outcomes immediately. Their usefulness would depend on the quality of available data, the suitability of the technology, local conditions and the ability of organisations to evaluate the results.
The report’s approach places the intended social benefit ahead of the technology itself.
It also recognises that AI may not be the most appropriate solution for every challenge. In some circumstances, strengthening existing systems, improving staff training or investing in conventional digital infrastructure may be more effective.
Four Stages for Responsible AI Adoption
The report identifies four stages through which nonprofit organisations can assess, test and potentially expand the use of AI in their programmes.
The framework is intended to help leaders make informed decisions about implementation rather than rushing into projects without sufficient preparation.
1. Explore and Prepare
The first stage involves identifying a problem and determining whether AI could help address it.
Organisations are encouraged to examine their objectives, existing technology, available information, staff capabilities and readiness for implementation.
They must also consider whether the information needed for an AI application exists and whether it is sufficiently reliable and relevant to the communities being served.
Language is another important consideration, particularly for organisations working across communities with different linguistic needs.
An AI system that performs adequately in one language or setting may not produce equally useful results in another. Organisations therefore need to establish whether the tools available are appropriate for their intended users.
The preparation stage also requires leaders to consider potential risks, including privacy concerns, inaccurate outputs and the possibility that automated systems could produce unfair results.
By addressing these questions early, organisations can avoid investing resources in projects that lack a clear purpose or cannot be sustained.
2. Prove and Learn
The second stage involves testing a specific AI application to determine whether it works under real-world conditions.
Rather than introducing a technology across an entire organisation immediately, leaders can begin with a limited pilot designed to answer clearly defined questions.
A pilot might examine whether an AI-supported process saves staff time, improves the handling of information or helps a programme reach its intended beneficiaries more effectively.
Organisations should establish measurable indicators of success before beginning the test.
They also need to determine whether the benefits justify the financial and operational costs associated with the technology.
The report highlights decisions about whether to develop a solution internally, purchase an existing product, adapt an available tool or collaborate with an external partner.
Each option carries different implications for cost, expertise, maintenance and organisational control.
A successful pilot should provide evidence that informs the next decision. If the results are poor or the risks outweigh the benefits, an organisation may need to modify the application, conduct further testing or abandon the project.
This approach can help nonprofits avoid committing scarce resources to solutions that have not demonstrated their value.
3. Embed and Operate
The third stage focuses on integrating an AI application into an organisation’s regular programme delivery after a pilot demonstrates sufficient promise.
At this point, technology becomes part of the organisation’s operating model rather than an isolated experiment.
The transition may require changes to staff responsibilities, management processes, technical systems and internal oversight.
Employees also need appropriate training to understand how the technology works, where its limitations lie and when human review is necessary.
For instance, an organisation using AI to support the preparation of programme reports would still need staff to verify important figures and ensure that the final document accurately reflects the underlying evidence.
Similarly, an organisation applying AI to decisions that affect access to essential services would need safeguards against errors and unfair outcomes.
The report emphasises the importance of governance, talent, operating structures and long-term costs at this stage.
These considerations are particularly important for nonprofits because a promising demonstration does not automatically establish that a technology can operate reliably across a full programme.
Organisations must ensure that the systems they introduce can be maintained and supervised without undermining their primary responsibilities to beneficiaries.
4. Sustain or Scale
The fourth stage examines whether an AI application should continue, expand or be reassessed.
Organisations that demonstrate positive results may consider extending a solution to additional users, geographical areas or programmes.
They may also explore partnerships with public institutions or other organisations that can help extend its reach.
However, expansion requires evidence that the benefits can be maintained under different conditions.
A system that works well in a small pilot may face new challenges when introduced across several communities or regions.
Differences in connectivity, language, staff capacity and available information can affect performance.
Organisations must also consider recurring expenses, technical support and the resources required to maintain appropriate safeguards.
Importantly, the report recognises that continuing with an existing approach or deciding against expansion can be legitimate outcomes.
The objective is not to maximise AI adoption but to determine whether a particular application contributes meaningfully to an organisation’s mission.
Healthcare, Education and Agriculture Among Potential Beneficiaries
The report identifies healthcare, education, livelihoods and other areas of social development as sectors in which African nonprofits are exploring ways to use AI.
These sectors involve complex service-delivery challenges, making it important for organisations to assess potential benefits carefully and avoid assuming that one technological approach will work everywhere.
In healthcare, nonprofit organisations often support public awareness campaigns, community outreach and access to essential services.
AI could potentially help some organisations analyse programme information, organise administrative work or identify patterns that warrant further investigation.
However, any application involving sensitive health information would require appropriate privacy protections, reliable data and human oversight.
In education, organisations may explore AI tools to support teachers, develop learning materials or reduce administrative workloads.
The potential value of such tools would depend on the needs of learners, the quality of the materials produced and whether the technology is accessible to the communities concerned.
Agriculture presents another area for investigation, particularly for organisations supporting farmers and rural livelihoods.
Depending on the available information and infrastructure, AI applications could help process agricultural data or support the delivery of relevant information to farming communities.
Yet these possibilities should not be confused with guaranteed improvements in productivity or income. Any intervention would need to be assessed against the realities faced by its intended users.
The report’s broader contribution is to encourage organisations to evaluate such opportunities systematically instead of assuming that the availability of AI automatically translates into better outcomes.
For African nonprofits, this distinction matters because resources committed to technology must compete with other pressing operational and programme needs.
Infrastructure and Funding Remain Major Considerations
The report also highlights the conditions that influence whether mission-driven AI can succeed.
These include access to digital infrastructure, locally relevant information, appropriate policies and regulations, and established channels through which organisations reach the communities they serve.
Such factors can determine whether a solution is practical, affordable and sustainable.
An organisation may identify a useful application but struggle to implement it if its staff lack reliable internet access, the necessary equipment or the technical knowledge required to manage the system.
The quality of available information is equally important. AI applications depend on the information and processes supporting them, meaning that incomplete, inaccurate or unsuitable data can undermine their usefulness.
Local context also matters.
African countries and communities differ in their infrastructure, languages, institutional arrangements and development priorities. A solution designed for one setting may require substantial adaptation before it can be used effectively elsewhere.
The Bridgespan Group’s research therefore calls attention to the role of funders and other organisations in helping nonprofits address these barriers.
Potential forms of support include flexible funding suited to different stages of implementation, shared infrastructure, technical assistance and broader capacity-building initiatives.
Such assistance could help organisations assess opportunities, conduct pilots and develop the internal capabilities needed to manage technology responsibly.
The report does not suggest that technology alone can resolve structural development challenges. Instead, it places AI within the wider organisational and institutional conditions necessary for effective social programmes.
Why AI Governance Matters for African Nonprofits
As nonprofits consider incorporating AI into their work, questions about accountability and responsible use become increasingly important.
AI systems can produce inaccurate information, reflect biases in their underlying data or create risks when sensitive information is handled improperly.
For organisations serving vulnerable communities, such problems could undermine trust and weaken the effectiveness of otherwise valuable programmes.
Nonprofit leaders therefore need clear procedures for deciding how AI can be used, who is responsible for supervising it and how errors or harmful outcomes should be addressed.
Human oversight is especially important where automated outputs could influence decisions affecting people’s access to services, support or opportunities.
Organisations should also be transparent with relevant stakeholders about the role of AI in their activities when disclosure is appropriate and necessary.
These responsibilities extend beyond technical teams. Senior leaders and governing boards need to understand the strategic implications of AI and ensure that its use remains consistent with organisational values and obligations.
Staff members must also know which tools they are permitted to use and what information should not be entered into external systems.
The report’s emphasis on governance reflects the view that responsible implementation must develop alongside technological experimentation.
Without clear accountability, an organisation may struggle to identify who is responsible when a system produces an incorrect result or causes unintended harm.
The Role of Funders and Development Partners
The report identifies funders and other ecosystem actors as important participants in efforts to strengthen responsible AI adoption across the nonprofit sector.
Financial support can help organisations obtain technology, but successful implementation may require more than a grant for software or equipment.
Nonprofits may also need assistance with staff development, data management, strategic planning, cybersecurity and the evaluation of new applications.
Funding arrangements that recognise these needs could allow organisations to develop their capabilities over time rather than relying on short-term technology projects.
Shared infrastructure and technical partnerships may also help organisations that cannot independently afford specialised systems or expertise.
Such cooperation could be particularly useful for smaller nonprofits operating with limited budgets and personnel.
However, support should remain responsive to each organisation’s circumstances. A solution suitable for a large institution may be too expensive or complicated for a smaller community-based organisation.
The report’s staged framework provides a way for funders and nonprofit leaders to discuss what kind of assistance is appropriate at different points in an AI project.
An organisation exploring an initial idea may need technical advice and support with problem identification. Another that has completed a successful pilot may require funding for integration, training and long-term maintenance.
Matching support to these different needs could help reduce the risk of projects being abandoned after initial experimentation.
What the Findings Mean for Africa’s Development Sector
The report adds to a wider discussion about how African organisations can use emerging technologies without losing sight of the social problems they are established to address.
Nonprofits frequently operate in environments where the need for services exceeds the resources available to provide them.
AI may offer opportunities to improve certain processes, analyse information more efficiently and develop new approaches to service delivery. Whether these benefits materialise, however, depends on how organisations choose and implement the technology.
For African development organisations, the central challenge is not simply gaining access to AI tools. It is determining which applications are appropriate, ensuring that the necessary safeguards are in place and establishing whether the results justify continued investment.
The report also highlights the importance of local knowledge in shaping technology decisions.
Organisations working directly with communities can help identify practical problems that technology developers or external funders might overlook.
Engaging staff and beneficiaries in the process can also help ensure that proposed solutions reflect actual needs rather than assumptions about what communities require.
This is relevant to efforts to improve healthcare access, educational opportunities, agricultural support and other essential services across the continent.
At the same time, the report’s recommendations should not be interpreted as evidence that AI will automatically close development gaps. Infrastructure limitations, financial constraints and the need for reliable public services remain important considerations.
The value of AI must ultimately be judged by its contribution to measurable social outcomes.
Bridgespan Calls for Decisions Based on Evidence
Aditi Sharma, a Bridgespan principal and co-author of the research, said the purpose of the report was not to promote mission-driven AI adoption as an end in itself.
Instead, she said the research was intended to help organisations make informed decisions about where AI could genuinely advance their missions.
Her position reinforces the report’s central message: nonprofits should evaluate technology according to the problems they need to solve and the results they can demonstrate.
The four-stage framework offers a structured approach, from initial assessment and testing to integration and decisions about long-term sustainability.
For organisations considering AI, the next steps include identifying a clearly defined challenge, assessing their readiness, selecting an appropriate application and establishing how its performance will be measured.
They must also consider whether they have the funding, staff capacity and governance arrangements required to manage the technology responsibly.
Where the evidence supports further investment, organisations can consider integrating successful applications into their programmes. Where it does not, they may need to revise their approach or pursue an alternative solution.
The report ultimately places accountability and measurable impact at the centre of decisions about AI in Africa’s nonprofit sector.
For development organisations, the challenge is to ensure that technological innovation strengthens their ability to serve communities rather than becoming an additional burden on already limited resources.
What Happens Next?
The Bridgespan Group’s report provides a framework that nonprofit leaders, funders and development partners can use when evaluating potential AI initiatives.
The immediate task for individual organisations is to determine whether AI addresses a genuine operational or programme challenge and whether the necessary conditions exist for responsible implementation.
Organisations can begin by reviewing their priorities, examining their available data, consulting staff and relevant communities, and identifying applications that can be tested on a manageable scale.
They should then establish clear measures of success, assess risks and determine whether the results justify further investment.
Funders and technical partners can support this process by providing resources appropriate to each stage, including expertise, training and infrastructure.
The report does not establish a universal timetable for adoption or suggest that every nonprofit should deploy AI. Instead, it encourages organisations to make deliberate choices based on their circumstances and objectives.
For Africa’s nonprofit sector, the broader question is how emerging technology can contribute to stronger, more accessible and more sustainable services.
The answer will depend not on how quickly organisations adopt AI, but on whether they use it responsibly to deliver meaningful benefits to the people and communities they serve.
Weng Global – stories beyond borders
Sources
- The Bridgespan Group — New Research Shows How African Nonprofits Can Use AI to Advance Their Missions, October 2026.
- The Bridgespan Group — Pursuing the Promise of AI: A Guide for African Nonprofits to Advance Their Missions.
- Africa Business Insight — A Guide to Help African Nonprofits Advance Their Missions with AI, October 2026.
