How NGOs Can Use Artificial Intelligence Without Putting Vulnerable Communities at Risk
Artificial Intelligence (AI) is opening up new possibilities for humanitarian NGOs to operate in more efficient ways. Whether helping out after natural disasters, assisting refugees, providing healthcare, or delivering emergency supplies, the potential of AI is vast.
Humanitarian agencies handle vast quantities of data on a daily basis. They gather beneficiary information, deepen their understanding of community needs, organize project data, produce reports, track the flow of funds, and engage with their partners on the ground. Processing all this data manually can be very time-consuming, particularly for smaller agencies with limited capacity.
AI software can automate some of these processes. They can be used to analyze large amounts of data, derive insights from trends, create executive summaries, assist with decisions, and enable companies to adapt to emergency situations.
But there’s a flip side to this technological evolution that must not be overlooked: the safeguarding of humanitarian data.
Below every record entered by an NGO there is a real person. The record might be of a girl or boy who needs educational help, or of a family fleeing conflict, or of a patient who needs medical help, or of a woman who needs help to protect her from violence. The persons share personal data because they trust humanitarian organizations to handle it ethically.
This information, if compromised or provided to people who should not have access to it, could have significant effects. It could threaten individuals’ safety, lead to discrimination, or undermine confidence in the services they rely upon.
As the role of AI in humanitarian work grows, it’s important that NGOs begin to realize that technology can be a tool for good as long as it’s used ethically. Data protection shouldn’t be an afterthought. It should be a consideration for every NGO’s AI approach.
Why Humanitarian Organizations Collect So Much Data
In order to explain why data protection is so critical, I am going to have a look at the importance of information in the context of humanitarian work.
NGOs work with diverse groups of people; they also provide services in accordance with the needs of these communities. For this to happen, organizations require an understanding of people’s context and the ability to quickly identify immediate issues and track the delivery of aid.
For instance, an NGO with families in the refugee camp may gather data on their names, their ages, their family members, where they are, their economic status, and any immediate requirements. A health-based organization may keep records of illness, immunizations, and people in need of urgent care.
In the same way, in an education organization, data collection might include names, attendance records, qualifications, and family details of students to find out if the children are receiving what they need.
This information helps NGOs:
- Identify individuals and families who require immediate assistance.
- Understand the needs of different communities.
- Distribute food, medicines, shelter, and other essential supplies.
- Monitor projects and evaluate their effectiveness.
- Prepare accurate reports for donors and funding organizations.
- Avoid duplication in beneficiary records.
- Understand whether humanitarian programs are reaching the intended people.
Collecting information is an important part of humanitarian work. However, organizations must understand that not every piece of information needs to be collected or stored.
The more personal information an organization holds, the greater its responsibility to protect it. Even information that appears ordinary, such as a person’s location or contact details, can become sensitive when connected with their circumstances.
For vulnerable communities, the exposure of even a small amount of personal information can create serious risks.
How AI Is Changing the Way NGOs Handle Humanitarian Data
AI is making it possible for humanitarian organizations to process information faster and understand complex situations more effectively. Instead of manually reviewing thousands of records, organizations can use AI-powered systems to identify patterns, summarize information, and support planning.
Here are some important ways AI is changing humanitarian operations.
1. Identifying Communities That Need Immediate Help
In times of emergency floods, earthquakes, conflicts, or outbreaks of disease, humanitarian groups need to know where support is most needed.
AI can also analyze data from satellite imagery, weather forecasts, census data, and emergency reports to help pinpoint regions that are impacted.
As an example, after intense flooding, the system could be used by an NGO to assist them to discover communities that might be accessible due to road and bridges damages. It could assist them to estimate the location of emergency shelters, food providers, and medical aid.
This information can guide organizations to understand what is coming and identify what will need to be done first.
Nonetheless, location data can be highly sensitive. If displacement or refugee locations, or even those fleeing violence, become known, they could be at risk.
Thus, NGOs need to carefully determine who should access location-based data and the ways in which this information will be used.
2. Improving Healthcare and Medical Support
Medical NGOs and institutions within the care economy collect medical data of patients to enable proper and relevant health care.
Artificial intelligence can facilitate the processing of medical data, the detection of patterns of health-related issues, the assistance in tracking diseases, and the enhancement of the planning of healthcare.
For instance, in the course of an infection or a virus outbreak, AI can assist public health organizations to track reports of patients and seek out neighborhoods in need of further healthcare supplies.
AI can further assist by keeping lab and medical records organized, as well as aiding health workers in spotting patterns to study more closely.
But medical information needs strong privacy controls. If someone’s health status, history, or treatment information is not authorized to be shared, it must always remain private.
Healthcare NGOs should ensure that the platform services are in line with correct privacy and security practices
3. Making Aid Distribution More Efficient
Distribution of aid is one of the key roles of NGOs. In times of crisis, an organization may require the distribution of food, purified drinking water, medicines, cash, and contingency housing to thousands of impacted individuals.
AI could be used to better structure the database of beneficiaries, who are missing, and support the process of knowing which household is in need of support.
For example, an NGO involved in an area with water shortages could use AI to examine data on a household level to find communities that were struggling to access the water and food the most.
It can assist humanitarian teams in optimizing their distribution of supplies.
But AI should always be a mere assistant, never an automated decider of who deserves help. When data is wrong or missing, the right families are left out.
Humanitarian workers have to go over the information, validate the outcome, and take into account local context.
4. Understanding Community Needs Through Data Analysis
NGOs regularly conduct surveys, collect feedback, and organize community meetings to understand the problems people are experiencing.
AI can help analyze large numbers of survey responses, feedback forms, and project reports to identify common concerns.
For example, an NGO working in rural communities may collect feedback about drinking water, healthcare, education, and employment. AI can help organize these responses and identify which issues are being reported most frequently.
This can help organizations understand community priorities and improve their programs.
However, personal responses should not be shared carelessly with external AI platforms. Organizations must protect the identity of people providing feedback, particularly when the information involves sensitive personal experiences.
The purpose of collecting community information should always be to improve services, not expose the people who provide it.
The Growing Risk of Data Breaches in Humanitarian Work
Increased reliance on digital systems creates risks for NGOs.
A data breach is when sensitive information is obtained, stolen, transmitted, or disclosed without authorization. Hacks, easy-to-guess passwords, unsecured databases, human error, and third-party software that hasn’t been well managed are common causes.
These kinds of outcomes can be even more critical for aid organizations.
A refugee you once knew has come to you with a request, and so you think about putting together some refresher lessons. Down the road is a club for kids in the area; it runs a program to help alienate children of street girls, and this is your desire.
If hackers were to break into this database, the details that are revealed could be dangerous for the people and their families.
In the same vein, if the medical records of people who have experienced violence or who have complex health needs are released, they could be targeted with discrimination, harassment, or worse.
A data breach can also harm the reputation of your NGO and tarnish the trust that donors, beneficiaries, and partner agencies have in you.
This is why protecting data should not be considered an issue for the IT department alone. Cybersecurity and data protection are inherently linked to human rights, dignity, and the security of the communities that NGOs work in.
Real-World Example: The ICRC Cyberattack and Its Lessons for NGOs
One important example of the risks associated with humanitarian data is the cyberattack against the International Committee of the Red Cross (ICRC) in January 2022.
The attack compromised servers containing personal information about more than 515,000 people receiving services through the ICRC’s Restoring Family Links program.
This programme helps people separated from their relatives because of conflict, migration, disasters, and other humanitarian emergencies reconnect with their families.
The compromised information included personal details belonging to people who were already in vulnerable circumstances.
The incident raised serious concerns about the protection of humanitarian databases and demonstrated how cyberattacks can affect people far beyond the organization itself.
For someone searching for a missing family member, the exposure of personal information can create additional uncertainty and safety concerns.
The incident also demonstrated that even well-established humanitarian organizations are not completely protected from cyber threats.
For smaller NGOs, the lesson is equally important. Organizations should not wait until they become large or internationally recognized before investing attention in data protection.
As more NGOs adopt AI tools, cloud storage, and digital databases, protecting sensitive information must become a basic part of their daily operations.
How AI Can Create New Data Protection Challenges
Although AI offers many opportunities for humanitarian organizations, using it without proper safeguards can introduce additional risks.
1. Sharing Sensitive Information With Public AI Tools
Many AI platforms allow users to upload documents, spreadsheets, reports, and other files to receive summaries, generate content, or analyze information.
An NGO employee might upload a beneficiary database to an AI tool to organize information or prepare a project report.
However, that file could contain names, phone numbers, addresses, medical details, and other sensitive information.
If the organization has not reviewed the platform’s privacy policies, data retention practices, and security arrangements, sharing this information could create unnecessary risks.
For example, an employee preparing a donor report may upload an entire beneficiary list when the AI tool only needs general project statistics.
A safer approach would be to remove identifying information and share only the necessary, anonymized data.
NGOs should establish clear rules about which information can be shared with AI platforms and avoid uploading identifiable beneficiary information into public AI tools unless the platform has been properly assessed and appropriate safeguards are in place.
2. AI Systems Can Produce Incorrect or Biased Decisions
AI systems depend on the information they receive. If the data is incomplete, outdated, or biased, their results may also be inaccurate.
For example, an NGO using AI to identify families eligible for financial assistance may unintentionally exclude households because their information is missing from the database.
This is particularly concerning for communities that are already underrepresented in official records, including remote rural populations, people without formal identification, and displaced families.
An AI system may appear to provide an objective recommendation, but its results can still reflect problems within the information used to train or operate it.
NGOs should regularly review AI-generated results and ensure that vulnerable communities are not unfairly excluded because of inaccurate data.
3. Misuse of Personal Information
AI can process information from different sources and identify connections that may not be immediately obvious.
While this can be useful for research and planning, it can also create privacy concerns.
For example, combining location information, photographs, social media activity, and personal records could make it easier to identify individuals who were previously anonymous.
This is known as the risk of re-identification.
For refugees, survivors of abuse, and people living in conflict areas, being identified through combined datasets could create serious safety concerns.
Organizations must therefore think carefully before combining datasets or sharing information with external partners.
4. Third-Party Platforms and Unclear Data Policies
Many NGOs depend on external software providers for cloud storage, communication, project management, fundraising, and AI-powered services.
These tools can make everyday work easier, but organizations must understand what happens to their information after it is uploaded.
Some important questions include:
- Who can access the information uploaded to the platform?
- Is the data used to train AI models?
- How long is personal information stored?
- Can the organization permanently delete its information?
- Is the information shared with other companies?
- What happens if the service provider experiences a cyberattack?
- Where is the information stored, and which privacy laws apply?
NGOs should not assume that a platform is safe simply because it is popular, affordable, or easy to use.
Before introducing new technology, organizations should review its privacy and security practices.
5. Deepfakes and the Misuse of Humanitarian Images
Another emerging concern is the misuse of photographs, videos, and personal stories through AI-generated content.
Humanitarian organizations regularly use photographs and videos to communicate their work, raise awareness, and attract donations.
However, AI tools can manipulate images, create misleading videos, or generate realistic-looking content involving people who never participated in the original material.
This can damage the dignity of beneficiaries and create confusion about the authenticity of humanitarian campaigns.
NGOs should obtain appropriate consent before using photographs and personal stories, verify the authenticity of published content, and clearly communicate when AI-generated or significantly AI-altered material is used.
The dignity of beneficiaries should never be compromised for engagement or fundraising.
Practical Ways NGOs Can Protect Humanitarian Data
Protecting sensitive information does not always require expensive technology or a large IT department. Even smaller organizations can take meaningful steps to improve their data security.
Here are some practical measures NGOs should consider.
1. Collect Only the Information You Actually Need
One of the simplest ways to reduce data risks is to avoid collecting unnecessary personal information.
For example, if an NGO only needs to understand the number of families requiring food assistance, it may not need detailed medical histories or unrelated personal information.
Organizations should clearly define why each piece of information is being collected and how it will be used.
Collecting less data means there is less information that could be exposed during a security incident.
2. Use Anonymized Data Whenever Possible
Anonymization involves removing personal details that could identify an individual.
Instead of uploading a spreadsheet containing beneficiaries’ names and addresses, an NGO could remove identifying information and use general statistics for analysis.
For example, an AI tool may only need:
- The number of families receiving assistance.
- The age groups of beneficiaries.
- The number of children enrolled in education programmes.
- The percentage of households requiring healthcare support.
- The total number of people reached through a project.
This allows NGOs to use AI for reporting and analysis without unnecessarily exposing personal identities.
However, removing names alone does not always guarantee anonymity. People may still be identified through combinations of location, age, occupation, or other details. Organizations should assess these risks before sharing datasets.
3. Introduce Strong Data Security Practices
NGOs should establish basic security measures to protect their digital systems.
These include using strong passwords, enabling two-factor authentication, regularly updating software, restricting access to sensitive files, and maintaining secure backups.
Access to beneficiary information should only be provided to employees who genuinely need it for their work.
Organizations should also regularly review who has access to their databases, especially when employees leave or external partners stop working with them.
4. Train Employees to Use AI Responsibly
Technology policies are only effective when employees understand how to follow them.
NGOs should train their teams on responsible AI use, including what information can and cannot be uploaded to external platforms.
For example, employees should understand why they should not copy private beneficiary records into public AI chatbots or share confidential project documents through unsecured links.
Organizations should establish clear internal guidelines for using AI in proposal writing, fundraising, research, reporting, and project management.
Even a short training session can help employees recognize common data protection risks.
5. Choose AI Platforms Carefully
Before introducing an AI tool, NGOs should review its privacy policy, security standards, data retention practices, and access controls.
Organizations should prefer platforms that offer clear data protection policies and appropriate security features.
They should also understand whether information entered into the platform can be used for model training and whether sensitive information can be deleted.
A tool that saves employees a few hours of work may not be worth the risk if it exposes confidential community information.
6. Keep Human Oversight in Every Important Decision
AI can help NGOs analyze information, identify patterns, and organize their work. However, important humanitarian decisions should always involve qualified people.
For example, AI may help identify communities that could require emergency assistance, but humanitarian workers should verify the information before deciding how resources are distributed.
Local knowledge, community feedback, and human judgment remain essential.
Technology should support humanitarian workers, not replace their understanding of the communities they serve.
7. Prepare for Data Breaches Before They Happen
Even organizations with good security practices can experience cyber incidents.
NGOs should have a basic response plan explaining what employees should do if personal information is accidentally shared, stolen, or accessed without authorization.
The plan should identify who needs to be informed, how access to compromised systems can be restricted, how affected information can be secured, and when beneficiaries and relevant authorities need to be notified.
Organizations should also conduct regular security reviews and test their response procedures.
Preparing in advance can help reduce confusion and limit the damage caused by a data breach.
The Importance of Data Protection Policies for NGOs
As AI becomes part of everyday NGO operations, organizations need clear policies explaining how personal information should be collected, stored, shared, and used.
A data protection policy should not be limited to large international organizations. Small nonprofits, local charities, and grassroots organizations also need basic rules to protect the people they serve.
An effective policy should cover:
Data collection: Explain what information is collected, why it is necessary, and how it will be used.
Data access: Define which employees, volunteers, and partners can access sensitive information.
AI usage: Establish rules about which AI tools employees can use and what information they can share.
Data storage: Ensure personal information is stored securely and protected against unauthorized access.
Data deletion: Remove information when it is no longer needed or legally required to be retained.
Incident response: Establish a clear process for reporting and responding to data breaches.
Third-party partnerships: Review the privacy and security practices of external technology providers and organizations that receive personal information.
Organizations should also follow applicable data protection laws. For example, India’s Digital Personal Data Protection Act, 2023, provides a legal framework for processing digital personal data. NGOs working internationally may also need to consider regulations such as the European Union’s General Data Protection Regulation (GDPR).
Having a clear policy helps organizations build trust with beneficiaries, employees, donors, and partners.
How AI Can Actually Help NGOs Improve Data Protection
Although AI introduces new privacy risks, it can also become part of the solution when used responsibly.
NGOs can explore AI-powered tools to strengthen their data security and improve internal processes.
Identifying unusual activity: AI-powered security systems can help identify unusual login attempts, suspicious access patterns, and potentially unauthorized activity.
Monitoring digital systems: Certain tools can help organizations monitor their networks and identify possible security threats before they become larger problems.
Supporting document reviews: AI can help teams identify personal information in documents before they are shared externally, although employees should verify the results.
Organizing information securely: AI can help organize non-sensitive information, summarize reports, and identify patterns without requiring employees to manually review every document.
Supporting risk assessments: AI can assist teams in reviewing internal processes and identifying areas where personal information may be unnecessarily exposed.
However, AI security tools are not a complete replacement for cybersecurity professionals, proper policies, or regular security checks. Organizations must still verify alerts and take appropriate action.
What Small NGOs Should Do When They Have Limited Resources
For smaller NGOs, data protection can feel like an additional responsibility when teams are already managing fundraising, project implementation, reporting, and community activities.
Not every organization has the budget to hire a dedicated cybersecurity expert or invest in advanced security software.
However, protecting beneficiary information does not always require a complicated system.
Smaller organizations can begin with a few practical actions:
- Review the information currently stored in organizational databases.
- Remove unnecessary personal information where appropriate.
- Use secure passwords and two-factor authentication.
- Avoid uploading sensitive beneficiary information into public AI tools.
- Train employees and volunteers on basic data protection practices.
- Review the privacy and security policies of external software providers.
- Limit access to confidential documents.
- Create a simple procedure for reporting suspected data breaches.
- Regularly review who has access to organizational accounts and databases.
- Explain to beneficiaries how their information will be collected and used.
These steps can help smaller organizations build a stronger foundation for responsible technology use.
NGOs can also collaborate with technology partners, cybersecurity professionals, and nonprofit support networks to improve their digital security without carrying the entire responsibility alone.
The most important thing is to make data protection part of everyday organizational practices rather than treating it as something to consider only after a problem occurs.
Building Trust Through Responsible AI Use
Trust is one of the most important things an NGO can build with the communities it serves.
People share personal information because they believe an organization will use it to provide assistance, improve services, and support their well-being.
If that information is misused or exposed, it can damage the relationship between communities and humanitarian organizations.
This is why transparency matters.
NGOs should clearly explain what information they collect, how it will be used, who may have access to it, and whether AI systems are involved in processing it.
For example, an organization collecting information for a healthcare programme should explain why certain medical details are necessary and how those details will be protected.
People should also receive understandable information about their privacy rights and how they can raise concerns.
Organizations should avoid making unrealistic promises about data security. Instead, they should demonstrate that they are taking reasonable steps to protect personal information and respond responsibly when problems occur.
Responsible AI adoption is not simply about using the latest technology. It is about ensuring that innovation respects human dignity, privacy, and safety.
The Future of AI in Humanitarian Work
The application of artificial intelligence will expand in humanitarian organizations as other NGOs implement digital tools for fundraising, health services, project coordination, emergency response, and community building.
In future years, we can expect AI to assist organizations in forecasting humanitarian demand, identifying areas of funding need, allocating resources, assessing climate-related vulnerabilities, and responding to crises.
Additionally, leveraging AI in the analysis of data will also enable NGOs to learn more about their long-term issues including food security, education, public health issues, and displacement.
It is essential for technology to be combined with stronger data protection measures.
NGOs should not focus only on the time or money saved by AI. They must also consider if the technology genuinely safeguards the individuals it aims to assist.
For example, an AI that speeds up food distribution for an organization can be advantageous. However, it may also lead to greater issues for another family in need.
Humanitarians of the future using advanced technology should develop solutions that prioritize safety, transparency, fairness, and people.
NGOs must realize that data protection does not cease with its implementation. As technology evolves and AI systems are improved along with emerging security threats, NGOs need to consistently reassess their practices.
How NGOs.ai Can Support NGOs in Their Digital Transformation
As NGOs explore new technologies, they also need practical tools that help reduce administrative pressure without creating unnecessary risks.
Platforms such as NGOs.ai can support organizations in everyday tasks such as proposal preparation, concept note development, budget creation, fundraising research, and project planning.
AI-powered tools can help smaller organizations save time on repetitive documentation and focus more attention on programme development and community impact.
However, responsible AI use should remain central to this process. NGOs should avoid entering confidential beneficiary information into AI tools unless the platform’s data handling and security arrangements have been properly reviewed.
The goal is not simply to introduce more AI tools into the nonprofit sector. It is to help organizations use technology in ways that support their work while respecting the people and communities they serve.
Technology should make NGO operations easier, but human judgment, local knowledge, transparency, and data protection must remain essential.
Conclusion: Protecting People Must Come Before Technology
AI has the potential to make humanitarian work faster, more organized, and more effective. It can help NGOs understand community needs, manage large amounts of information, improve healthcare planning, distribute resources, and respond to emergencies.
However, these benefits come with important responsibilities.
Humanitarian data is not just a collection of names, numbers, addresses, or medical records. Behind every record is a real person, a family, and a community that may be depending on an NGO for support.
A data breach can expose vulnerable individuals to serious risks. Poorly managed AI systems can produce unfair decisions. Sharing personal information without proper safeguards can damage the trust that humanitarian organizations work so hard to build.
That is why data protection must be a fundamental part of every organization’s digital strategy.
NGOs should adopt AI carefully, collect only necessary information, protect sensitive records, train their employees, review external technology providers, and ensure that important decisions remain guided by human judgment.
The future of humanitarian work should not be about choosing between technological progress and people’s privacy. Organizations must find ways to achieve both.
Technology should make humanitarian organizations more capable of helping people, not make the people they serve more vulnerable.
As AI becomes a bigger part of the nonprofit sector, the organizations that combine innovation with responsibility will be better positioned to build lasting trust with the communities they support.
Ultimately, the real success of AI in humanitarian work will not be measured only by faster processes, lower costs, or better data analysis. It will also be measured by how effectively it protects people’s rights, dignity, and safety.
For NGOs, the future of AI should not simply be about working faster. It should be about helping people better, while keeping their information and dignity safe.
