What are the risks?
It all sounds very exciting, and AI is definitely throwing up interesting new prospects for NGOs and other social-impact organizations, but we need to consider the downsides too. Although AI can enable groups to reduce administrative burden, analyze data quickly, optimize delivery of services, and extend reach, when systems are deployed at scale, even relatively minor errors can impact a large number of beneficiaries. Those dealing with vulnerable communities might, on top of these risks, be concerned that a faulty AI system with inaccurate data, discriminatory algorithms, and poor data security could cause significant, if not irreversible, damage.
Data Privacy Could Become a Major Concern
NGOs can work with a lot of very sensitive information, which the public entrusts to their care. This data can cover health records, financial data, contact details of people, childhood records, beneficiary data, refugee data, and file history files, to name only a few. When this type of information is input into an AI system, an NGO should know where it is going, who holds it, and which members of staff have access to the data within an AI system. Failure to do this may expose its beneficiaries to unnecessary risks when they have invested trust in the organization using the AI. For NGOs, a data breach is not just a technical concern but poses a security risk for their beneficiaries, along with irreparable damage to the relationship between the organization and the public in whose care it acts.
AI Can Make Mistakes While Sounding Completely Confident
One of the biggest challenges with generative AI is that it can provide incorrect information while presenting it in a very convincing way.
This can become particularly risky when AI is used for health information, legal support, beneficiary assessments, grant compliance, or other important activities. A staff member may assume an answer is correct simply because it is clearly written and sounds professional.
For this reason, AI-generated information should be reviewed before it is used, especially when the decision could directly affect a person’s life or access to services.
AI can be a useful assistant, but it should not automatically become the final decision-maker.
Bias Could Affect Vulnerable Communities
AI systems depend heavily on the information and data used to develop them. If that data contains existing biases or does not properly represent certain communities, the AI system may produce unfair or less accurate results.
This is particularly important for NGOs because many of them work with people who are already underserved or vulnerable.
For example, imagine an AI system being used to identify families eligible for assistance. If the system is based on incomplete or unbalanced data, certain communities could be overlooked even when they genuinely need support.
That is why NGOs need to regularly question whether an AI system is treating different groups fairly rather than assuming that technology is automatically neutral.
The Human Connection Could Be Lost
NGO work is ultimately about people. Technology can make communication faster, but it cannot completely replace empathy, cultural understanding, and personal relationships.
A chatbot may answer a beneficiary’s question within seconds, but it may not understand the emotional or social situation behind that question. Someone asking for help may need more than an automated response. They may need a person who can listen, understand their circumstances, and guide them appropriately.
If organizations rely too heavily on automation, beneficiaries could begin to feel that they are interacting with a system rather than an organization that genuinely understands them.
This matters especially in areas such as humanitarian assistance, refugee support, mental-health services, and community development, where trust and human connection are essential.
Smaller NGOs Could Face a Technology Gap
Not every NGO has the same access to technology.
Large international organizations may have developers, cybersecurity experts, data specialists, and enough funding to experiment with advanced AI tools. A small grassroots organization, however, may have only a handful of employees and limited technical infrastructure.
This difference could create a new technology gap within the nonprofit sector.
Organizations with greater technical resources may be able to adopt AI quickly, while smaller community-based NGOs could struggle to access the same tools or afford the necessary training and infrastructure.
This becomes an even bigger concern if technology starts becoming necessary for accessing funding, managing programs, or delivering services. NGOs should therefore consider whether AI adoption is actually helping smaller organizations or unintentionally making the gap between large and small organizations wider.
Cybersecurity Risks Could Increase
AI can improve an organization’s digital capabilities, but it can also introduce new cybersecurity challenges.
As NGOs connect AI tools with websites, databases, internal documents, and other systems, there may be more digital access points that need to be protected. Organizations also need to consider who has access to AI tools and what information employees are allowed to share with them.
For NGOs that already operate with limited cybersecurity resources, introducing AI without strengthening security practices could increase their exposure to cyber threats.
This means AI adoption should go hand in hand with stronger passwords, access controls, staff training, data protection policies, and regular security checks.
AI Could Become Expensive to Maintain
AI is sometimes presented as an inexpensive way to improve efficiency, but large-scale implementation can involve significant costs.
Organizations may need to spend money on technical staff, data systems, cloud infrastructure, cybersecurity, staff training, AI subscriptions, and regular maintenance. These costs can become difficult for smaller NGOs with limited budgets.
There is also an important question of opportunity cost.
If an NGO spends a large amount of money developing an AI system that produces very little practical value, those resources could have been used for direct community programs instead.
The goal should not be to adopt the most advanced technology available. The goal should be to find technology that solves a real problem and provides meaningful value to the people the organization serves.
Staff May Become Too Dependent on AI
Another risk is overreliance on AI.
If employees begin using AI for almost every task without checking the results, they may gradually stop questioning the information they receive. Over time, this could affect important skills such as writing, research, analysis, and decision-making.
The problem becomes more serious when AI recommendations are used for decisions involving beneficiaries or organizational strategy.
The better approach is not AI instead of people, but AI with people.
AI can handle repetitive tasks and help staff process information faster, while humans continue to provide judgment, context, and accountability.
Accessibility Could Become a Problem
An AI-powered service is only useful if the people who need it can actually access it.
Many communities may still face limited internet access, poor connectivity, older mobile devices, low digital literacy, language barriers, or accessibility challenges.
An organization could unintentionally create a service that works extremely well for digitally connected users while leaving the people most in need behind.
NGOs should therefore think about alternative ways for people to access services. Human support, offline options, phone-based assistance, and accessible formats may still be necessary even when AI is introduced.
Technology should make services more inclusive, not create another barrier between people and the support they need.
The Biggest Risk: Using AI Without a Clear Purpose
Perhaps the biggest mistake an NGO can make is adopting AI simply because it is becoming popular.
AI should not be introduced just to make an organization appear innovative. There should be a clear reason behind its use.
Before investing in an AI system, NGOs should ask:
What problem are we trying to solve?
Who will actually benefit from this technology?
Could a simpler and less expensive tool solve the same problem?
What could go wrong if the system makes a mistake?
What information will the AI system need?
Who will be responsible if something goes wrong?
Will people still be able to speak to a human when they need one?
These questions are just as important as asking what AI can do.
How NGOs Can Reduce These Risks
The answer is not to avoid AI completely. Instead, NGOs can introduce it carefully and gradually.
Organizations can begin with lower-risk activities such as administrative support, document organization, translation drafts, internal research, and repetitive tasks. These uses allow staff to understand the technology before introducing it into more sensitive areas.
NGOs should also establish clear rules about what employees can and cannot enter into AI tools, particularly when personal or confidential information is involved.
Most importantly, humans should remain responsible for important decisions.
AI can process information. It can identify patterns. It can save time and help staff work more efficiently.
But when people’s safety, rights, health, or access to essential services are involved, the final responsibility should remain with qualified people.
The Opportunity and the Risk Must Be Considered Together
The 12-month AI partnership provided to 15 organizations by the Tech To The Rescue and Google.org project demonstrates the power and scope of AI within the social impact realm, yet along with this benefit also comes a key takeaway when applying scaled technology: scaled responsibility. From privacy and accuracy to bias and cybersecurity and human involvement, there exists an increased diligence required when your product extends beyond initial users. So how we use AI and NGOs’ success stories should be a measured factor less about people and hours saved by your AI platform and more about how you reach the most safe, justifiably relevant individuals. AI can enhance your ability to do more while wearing different hats on a tighter budget; technology itself will not deliver on its own; only the application, monitoring, and implementation will, for you can choose wisely or wisely choose the risks of disaster.
