AI is no longer only for IT companies; it’s here to help you, too! How is AI transforming the way we do our work? It is helping organizations working in education, healthcare, rural development, women empowerment, and environmental conservation to advance their agendas. The influence of AI is swift!
For social impact organizations, artificial intelligence and related big data projects are opening new pathways to plan, manage, and deliver their programs to better serve communities. Whether it’s supporting educators in preparing instructional content or health clinics in digitizing patient records, this technology is beginning to transform the working model of NGOs. It’s helping NGOs to capture community needs, monitor and evaluate projects, process information, and reduce time and effort on secondary tasks.
A new survey reveals how quickly this change is happening. As of November 2026, 27 of the 36 NGOs that responded to a survey from the Koita Foundation were already using artificial intelligence. And eight more organizations said that they were looking into how they could start using the tech.
So, what does this mean going forward? It indicates that nonprofits are no longer just curious about AI but now actively seeking applications that help improve the day-to-day and increase program effectiveness.
The survey identified five major areas where AI is being used:
- Training and learning.
- Assistants and co-pilots for staff and frontline workers.
- Assessment and evaluation.
- Analytics and decision support.
- Internal organizational activities.
Are you prepared to witness how AI is revolutionizing our approach to aging problems? It’s not merely about the latest bells and whistles; it’s about smarter, more innovative responses.
Let’s look at the United Nations Development Programme (UNDP). Its story, published February 2026, on “Designing AI for Equity,” looks at India’s U-WIN digital immunization platform. How this platform makes use of AI to support frontline health workers, streamline tedious paperwork, and increase access to critical services.
So, what does it mean going forward? These results hold an optimistic outlook on how technology is creating new potential for India’s nonprofits. Let’s explore how AI is changing the NGO landscape in India and the impact it’s having on social work.
Understanding the Koita Foundation’s Findings: Are Indian NGOs Ready for AI?
Technology in Nonprofits: The New Normal
The nonprofit sector has been slow to adopt technology for decades. Big businesses have their own software programmers, IT departments, and plenty of money for trying out new digital solutions. Meanwhile, for many small NGOs with budgets and a handful of staff, the emphasis is on providing vital services to the people they serve, developing projects and keeping donors onside. New technology can be a leap too far.
However, the November 2026 results from the Koita Foundation suggest positive changes. Out of 36 NGOs surveyed in September 2026, 27 of those NGOs were already utilizing AI, and eight others were investigating how to use it. Three out of four NGOs have begun implementing the technology. The most fascinating part is that these NGOs are not relying on a singular use of AI; they are customizing it to meet their specific needs.
Consider an organization that works on education and employs AI to empower teachers and improve curriculum and learning materials. An organization working in the healthcare space could use AI-based assistants to give frontline workers access to knowledge and expertise. An organization working in rural development may employ AI for analyzing program data and community insights.
The results also mark a major shift in how organizations evaluate technology. In earlier times, the biggest question was if AI could complete a task. Now the question is whether people will use it, whether it’s more efficient to do so, and if it will deliver results in the real world.
It’s a critical distinction. You can’t just bring in an AI tool and expect organizational performance to improve. It has to solve a real problem, be easy for employees to use, and give better results than existing processes. While it is important to recognize that these 36 organizations formed the cohort for the Koita Foundation survey and were not representative of all NGOs in India, they do shed light on the priorities and uses emerging within organizations in the sample.
1. AI Is Transforming Training and Learning in NGOs
Training is one of the most important activities in the nonprofit sector.
NGOs work with different groups of people, including teachers, healthcare professionals, community workers, volunteers, program managers, and local representatives. Each group requires specific knowledge and skills to perform its responsibilities effectively.
For example, an NGO working in rural education may regularly train teachers on classroom management, child development, digital learning, and teaching methods.
Similarly, healthcare organizations need to educate frontline workers about vaccination, maternal health, nutrition, hygiene, and disease prevention.
However, organizing regular training sessions can be challenging.
Employees may be working in different districts, villages, or states. Bringing everyone together requires time, money, and coordination. Training materials also need to be updated regularly to reflect changing requirements.
This is where AI can become useful.
AI-powered learning assistants can help organizations create training materials, simplify complicated information, develop practice exercises, and provide employees with access to learning resources.
Instead of depending entirely on classroom-based training, employees can use digital platforms to learn at their own pace.
How can NGOs use AI for training?
Creating personalized learning materials: AI tools can help prepare training content according to the responsibilities and knowledge levels of different employees. For example, a community health worker may need simple information about maternal health, while a program manager may require more detailed guidance on monitoring and reporting.
Supporting teachers and educators: Education NGOs can use AI to prepare lesson plans, classroom activities, worksheets, and learning exercises. Teachers can also use AI assistants to explore different ways of explaining difficult subjects.
Making training multilingual: India has several regional languages, and language differences can sometimes make training difficult. AI-powered translation and voice technologies can help convert learning materials into languages that employees and communities understand more comfortably.
Providing continuous learning support: Employees may forget certain procedures or need clarification after attending a training session. An AI assistant can help them find relevant information without waiting for another formal training program.
Consider an NGO working with hundreds of community educators across rural India. Instead of preparing separate training documents manually for every location, the organization could use AI to develop basic learning resources and adapt them to different local requirements.
This would not eliminate the need for trainers or experienced educators. Instead, it would help them spend less time preparing repetitive materials and more time supporting teachers.
The larger opportunity is to make quality learning resources accessible to more people, including those working in remote communities.
2. AI Assistants and Co-Pilots Are Supporting Frontline Workers
Frontline workers are among the most important members of any NGO.
They interact directly with communities, understand local challenges, collect beneficiary information, provide guidance, and ensure that programs reach the people who need them.
However, their responsibilities often extend far beyond direct community engagement.
They may need to complete paperwork, update records, prepare reports, answer questions, communicate with supervisors, and follow organizational guidelines.
These administrative responsibilities can take up a significant portion of their working hours.
AI assistants and co-pilots can help reduce some of this pressure.
An AI assistant is a digital tool that can respond to questions, retrieve information, summarize documents, and help employees complete routine tasks. A co-pilot works alongside a person, supporting their activities without taking complete control of the process.
For NGOs, these tools can become useful companions for employees who need quick access to information.
Some practical applications include:
- Helping field workers understand program guidelines.
- Answering frequently asked questions from beneficiaries.
- Summarising long documents and reports.
- Assisting employees with routine documentation.
- Providing information about available services and resources.
- Helping staff communicate with program managers.
For example, imagine an NGO working on women’s empowerment in rural communities.
A field worker may regularly receive questions about skill-development programs, eligibility criteria, training schedules, and available support.
An AI-powered assistant containing verified organizational information could help the worker find relevant answers quickly.
Similarly, a child-protection NGO could use an internal AI assistant to help employees locate safeguarding guidelines, reporting procedures, and relevant program documents.
India’s U-WIN Initiative: A Practical Example of AI Supporting Healthcare Workers
One of the most interesting examples of people-centered AI adoption comes from India’s healthcare sector.
In its February 20, 2026, story, Designing AI for Equity: India’s U-WIN Story, UNDP explained how AI-based features are being introduced to improve the digital immunization system.
U-WIN is India’s digital platform designed to manage vaccination records for pregnant women and children.
Healthcare workers use the platform to record important information about beneficiaries and vaccinations. However, manually entering this information can become difficult when hospitals and vaccination centers experience heavy patient traffic.
UNDP highlighted the experience of a healthcare worker responsible for maintaining vaccination records at a hospital in Haryana.
Under the AI-based text-to-speech feature being piloted on U-WIN, the worker can speak the beneficiary’s information, including details about the vaccine administered. The system converts the spoken information into a structured digital record.
This reduces the need to type every detail manually and can help healthcare workers complete documentation more efficiently.
According to UNDP, the feature had shown promising results in the seven districts where it was being piloted.
This example offers an important lesson for NGOs.
Technology does not always need to be complicated to make a difference. Sometimes, a simple feature that reduces repetitive work can improve the experience of employees and beneficiaries.
For organizations working in public health, nutrition, maternal care, and rural healthcare, similar voice-based solutions could make documentation easier, provided they are properly tested and supported by appropriate privacy safeguards.
The larger goal is to make technology work according to people’s needs rather than expecting people to struggle with complicated systems.
3. AI Is Improving Assessment and Evaluation of NGO Programmes
Every NGO wants its programmes to create meaningful change.
However, completing activities does not necessarily mean that a project has achieved its objectives.
An organisation may conduct hundreds of training sessions, distribute educational materials or organise health camps. But how does it know whether these activities have improved people’s lives?
This is where monitoring, assessment and evaluation become important.
Monitoring and Evaluation (M&E) helps NGOs understand whether their programmes are progressing according to plan, whether resources are being used effectively and whether the expected outcomes are being achieved.
For example, an NGO running a livelihood development programme may want to understand:
- How many women completed the training?
- How many participants started their own businesses?
- Did household incomes improve?
- What challenges prevented participants from finding employment?
- Which activities produced the strongest results?
Finding answers to these questions requires collecting information from beneficiaries, reviewing surveys, conducting interviews and analysing programme records.
For smaller organisations, this can become a time-consuming process.
AI can make several parts of this work easier.
AI-powered tools can organise survey responses, summarise interviews, identify common themes and help programme teams prepare initial evaluation reports.
Understanding Beneficiary Feedback
One practical application is analysing feedback received from beneficiaries.
Suppose an NGO conducts a skills-training programme for 500 women across different villages.
After the programme, participants complete surveys explaining their experiences, the usefulness of the training and the difficulties they faced.
Manually reviewing every response may require considerable time.
AI can help group similar responses into categories such as:
- Difficulties understanding the training material.
- Lack of access to transportation.
- Limited employment opportunities.
- Need for additional practical training.
- Problems accessing financial support.
This gives programme managers a clearer picture of the challenges participants are experiencing.
Measuring Programme Progress
AI can also help compare project targets with actual progress.
For example, if an NGO planned to train 1,000 young people but has reached only 600, an AI-supported reporting system can help organise progress information and highlight the difference.
Programme managers can then investigate the reasons behind the gap and decide whether changes are needed.
Preparing Reports for Donors
Donors often expect NGOs to submit progress reports explaining how funding has been used and what results have been achieved.
AI can assist in organising project information, summarising activities and preparing initial report drafts.
However, the information must always be verified by the organisation.
AI should not invent programme results, exaggerate achievements or make assumptions about beneficiary experiences.
The final evaluation must reflect genuine evidence and the actual experiences of the people involved.
Why this matters: Better evaluation helps NGOs understand what is working, identify areas that require improvement and make more informed decisions about future programmes.
It also helps organisations communicate their impact more clearly to donors, partners and communities.
4. AI Is Helping NGOs Make Better Decisions Through Data Analytics
Data has become an important resource for organisations working in social development.
Every programme generates information.
An education NGO may collect student attendance records, examination results and learning assessments. A healthcare organisation may maintain vaccination information, health survey results and patient records. A livelihood organisation may track training participation, employment outcomes and income changes.
But collecting information is not enough.
Organisations must also understand it and use it to improve their decisions.
For many NGOs, analysing large amounts of data can be difficult because they do not have specialised teams or advanced analytical systems.
AI-powered analytics can help simplify this process.
These tools can process information, identify patterns, highlight changes and help programme managers understand what is happening across different projects.
Identifying Communities That Need More Support
Consider an NGO working to improve school attendance in rural areas.
The organisation collects information from several schools and discovers that attendance is consistently lower in certain locations.
AI-supported analytics can help identify patterns in the collected information and highlight areas that may require additional attention.
Programme managers can then investigate possible reasons, such as transportation difficulties, seasonal migration, household responsibilities or limited access to educational resources.
The technology can help identify where further investigation is needed, but local teams must understand the actual reasons behind the problem.
Improving Healthcare Planning
Healthcare NGOs can also benefit from data analysis.
For example, an organisation working on maternal and child health may want to understand which communities have lower vaccination coverage or limited access to healthcare services.
By analysing reliable programme data, AI tools can help identify geographical patterns and support better planning.
This is also an important part of the U-WIN story.
UNDP explains that an AI-driven analytics utility is being developed for U-WIN to analyse immunisation coverage, disease surveillance information and outbreak reports.
The proposed system is intended to identify patterns and potential risks that may otherwise be difficult to recognise quickly.
Geographical Information System (GIS)-based dashboards are expected to help authorities identify areas with low vaccination coverage and plan targeted interventions.
This could support a shift from responding only after health problems become visible to identifying potential gaps earlier.
For NGOs, this approach offers valuable possibilities.
Organisations working in nutrition, sanitation, healthcare and rural development could use similar analytical approaches to understand community needs and plan their activities more effectively.
Moving from Data Collection to Data-Driven Decisions
AI can help NGOs move beyond simply maintaining spreadsheets and preparing reports.
It can support a more systematic approach to understanding information.
However, the quality of the results depends on the quality of the data.
Incomplete records, outdated information or incorrect entries can lead to misleading conclusions. Organisations must therefore maintain reliable data collection processes and ensure that important decisions are reviewed by people who understand the local context.
AI should help organisations ask better questions and identify useful patterns, not make decisions without human involvement.
5. AI Is Simplifying Internal Organisational Work
While NGOs are primarily focused on social impact, their internal responsibilities are similar to those of many other organisations.
They need to manage finances, communicate with donors, prepare documents, coordinate employees, organise projects and maintain administrative records.
For small and medium-sized NGOs, these activities can become particularly challenging.
Many organisations do not have dedicated teams for fundraising, communication, data management or documentation.
The same employees who manage community programmes may also be responsible for preparing funding applications, writing reports and coordinating administrative activities.
This is where AI can offer immediate practical value.
Unlike specialised AI systems that may require technical expertise, many generative AI tools can assist with everyday tasks through simple instructions.
Proposal and Grant Writing
Preparing a funding proposal requires organisations to explain the problem they want to address, their proposed solution, project objectives, activities, expected outcomes and implementation plan.
NGOs must also ensure that their proposals follow the specific requirements of each donor.
AI tools can help organise project ideas, improve written content, develop initial drafts and simplify complicated donor guidelines.
For example, an NGO planning a youth employment programme can use AI to structure its project background, objectives, proposed activities and expected outcomes.
The organisation can then review the draft, add local information and customise it according to the donor’s requirements.
Budget Preparation
Project budgeting is another important responsibility.
NGOs must estimate costs related to staff, training, transportation, equipment, materials, monitoring and other activities.
AI-powered budget tools can help identify relevant budget categories and organise estimated expenses based on project details.
This can be especially helpful for organisations that do not have dedicated financial planning teams.
However, budget estimates must always be checked against actual costs, donor rules and organisational financial policies.
Communication and Documentation
AI can also help NGOs prepare professional emails, summarise long documents, improve reports, create meeting notes and organise information.
For example, an NGO preparing for a donor meeting may use AI to summarise a lengthy funding guideline and identify important application requirements.
A programme manager may use an AI assistant to turn rough meeting notes into a structured action list.
These applications may appear small individually, but they can save considerable time when used regularly.
Managing Organisational Knowledge
Another important opportunity is helping employees access information that already exists within their organisation.
NGOs often maintain years of project reports, policy documents, training materials and donor guidelines.
Finding the right information can become difficult when documents are stored across different folders and platforms.
AI-powered document assistants can help employees search organisational knowledge and locate relevant information more efficiently, provided the system has appropriate access controls.
This can reduce the time spent searching through old documents and help organisations make better use of their existing knowledge.
The biggest benefit is not simply completing administrative tasks faster. It is allowing employees to spend more time on programme development, fundraising and direct community engagement.
6. The Importance of Local Languages and Voice-Based AI in India
One important lesson emerging from India’s AI adoption journey is that technology must be accessible to the people using it.
India has enormous linguistic and cultural diversity.
NGOs often work with communities where people are more comfortable communicating in regional languages than in English.
Many frontline workers also have limited time to learn complicated software or enter large amounts of information manually.
This creates a need for AI tools that are simple, accessible and suitable for real-world conditions.
Voice-based AI is one promising development.
Instead of typing long messages or filling out complicated forms, users can speak their information into a device.
AI-powered systems can then convert speech into text, organise the information and help complete routine tasks.
The U-WIN example demonstrates how this approach can support healthcare workers.
Similar applications could be explored by NGOs working in:
Rural education: Teachers could use voice assistants to access learning materials, prepare lesson plans and record classroom observations.
Community healthcare: Field workers could use speech-based systems to document visits, subject to appropriate medical and data-protection safeguards.
Agriculture: Community workers could access information about farming practices, weather-related guidance and agricultural programmes through language-friendly digital assistants.
Women’s empowerment: Local organisations could explore multilingual assistants to help women understand training opportunities, available services and programme information.
Disaster response: Field teams could use voice-based tools to record urgent needs, organise information and communicate with response coordinators.
However, multilingual AI must be tested carefully. Regional accents, dialects, background noise and differences in pronunciation can affect accuracy.
A tool that works well in one language or location may not perform equally well elsewhere.
For this reason, NGOs should involve local communities and frontline workers when testing and selecting AI solutions.
Accessibility should be considered from the beginning, not added as an afterthought.
7. What Does Responsible AI Adoption Mean for NGOs?
As more organisations begin using AI, responsible adoption becomes increasingly important.
NGOs often work with people who may be facing economic difficulties, social exclusion, health challenges or other vulnerabilities.
They may collect highly personal information, including financial details, family circumstances, health records and information about children.
Using AI without appropriate safeguards could expose beneficiaries to privacy risks or unfair decisions.
Therefore, organisations must consider not only what AI can do but also what could go wrong.
Protecting Beneficiary Information
Data privacy should be one of the first considerations when introducing AI.
NGOs should understand how AI platforms use, store and process the information provided to them.
Sensitive personal information should not be entered into public AI tools without appropriate authorisation and safeguards.
Organisations should establish clear rules about which employees can access information and what types of data can be used with AI systems.
Avoiding Incorrect Information
AI tools can produce inaccurate answers, misunderstand instructions and generate information that sounds convincing but is incorrect.
This can become particularly dangerous when AI is used for healthcare guidance, legal information, beneficiary eligibility or financial decisions.
Important outputs should be checked by qualified employees before they are shared or acted upon.
Preventing Bias and Exclusion
AI systems learn from the information used to develop them.
If the underlying data does not adequately represent certain communities, the results may be less accurate for those groups.
For example, an AI system used to identify beneficiaries may overlook people whose information is incomplete or who are not adequately represented in the available dataset.
NGOs must ensure that AI-supported processes do not unfairly exclude people based on their location, language, income, gender or other circumstances.
Keeping Humans Involved
AI should not become the final authority in decisions that affect people’s lives.
An AI system may help identify patterns in beneficiary data, but human teams must consider local realities before deciding how resources should be distributed.
Similarly, AI can help prepare a funding proposal, but NGO professionals must ensure that it accurately represents their organisation’s mission, experience and community needs.
Responsible AI means using technology while maintaining human accountability.
8. Why Small and Grassroots NGOs Should Pay Attention to AI
When people discuss Artificial Intelligence, they often imagine expensive software, advanced computers and large technology teams.
This can make smaller NGOs believe that AI is only suitable for large organisations.
However, many useful AI applications do not require an organisation to develop its own technology.
Small NGOs can begin with accessible tools that support everyday activities.
For example, a grassroots organisation working in a rural community may use AI to:
- Prepare basic project proposals.
- Translate awareness materials.
- Draft emails to potential donors.
- Organise survey responses.
- Prepare training documents.
- Summarise project reports.
- Create simple budgets.
- Develop social media content.
These applications may not appear revolutionary, but they can reduce repetitive work and help small teams manage their responsibilities more efficiently.
Consider a small NGO with only five employees.
The team may be responsible for conducting community visits, preparing funding applications, managing accounts, coordinating volunteers and reporting project progress.
Without additional support, these responsibilities can become difficult to manage.
Using suitable AI tools for documentation, proposal drafting and information organisation may help the organisation save time without immediately hiring additional administrative staff.
However, smaller NGOs should not feel pressured to adopt AI simply because other organisations are doing so.
The right approach is to identify the tasks that consume the most time, understand which tools can help and begin with small experiments.
The goal should be to improve the organisation’s work, not increase its technology expenses.
9. How NGOs Can Start Their AI Journey: A Practical Approach
The Koita Foundation findings indicate that many organisations have already started experimenting with AI.
But moving from experimentation to meaningful adoption requires planning.
NGOs should not introduce multiple AI tools at once without understanding how they fit into existing processes.
A gradual approach can make adoption more manageable.
Step 1: Identify everyday challenges
Begin by understanding which activities take the most time.
Does the organisation struggle with proposal writing? Is preparing reports a lengthy process? Do field workers spend too much time entering information? Are employees finding it difficult to analyse programme data?
Identifying the actual problem is the first step.
Step 2: Select one suitable AI tool
Once the challenge is identified, look for a tool that addresses it.
For example, an organisation struggling with documentation can start with an AI writing assistant. An NGO working with large amounts of survey information may explore AI-supported data analysis.
The tool should match the organisation’s actual requirements.
Step 3: Train employees
Even simple AI tools require some understanding.
Employees should learn how to provide clear instructions, review AI-generated responses and identify inaccurate information.
Training should also cover privacy, responsible use and the limitations of AI.
Step 4: Test the tool on a small project
Before introducing AI across the entire organisation, test it on a limited activity.
For example, an NGO could use an AI tool to prepare a first draft of one project report and compare the time required with its usual process.
This helps the organisation understand whether the tool actually provides value.
Step 5: Measure the results
An AI tool should be evaluated based on practical outcomes.
Organisations can consider questions such as:
- Did the tool save time?
- Was the output accurate?
- Did employees find it easy to use?
- Did it improve the quality of work?
- Was it affordable?
- Did it create any privacy or security concerns?
If the results are positive, the organisation can consider expanding its use.
Step 6: Learn from other NGOs
One of the most interesting observations in the Koita Foundation findings is that several organisations are independently trying to solve similar problems.
This creates an opportunity for collaboration.
Instead of every NGO developing its own solution, organisations can learn from existing examples, share experiences and adapt tools that have already been tested.
This can reduce unnecessary costs and prevent organisations from repeating the same mistakes.
10. The Future of AI in India’s Nonprofit Sector
The growing adoption of AI suggests that India’s nonprofit sector is entering an important period of digital transformation.
Organisations are beginning to explore how technology can improve their internal operations and strengthen the services they provide to communities.
In the coming years, several developments could become increasingly important.
More AI-powered community services: NGOs may use multilingual assistants to provide information about healthcare, education, government schemes and community programmes.
Better programme planning: AI-supported analytics could help organisations understand community needs and identify areas requiring additional attention.
Improved digital documentation: Voice-based systems and automated data processing could make it easier for frontline workers to maintain records.
More efficient fundraising: Generative AI could help NGOs prepare proposals, understand funding guidelines, organise donor information and communicate their impact.
Stronger collaboration: NGOs, technology companies, universities, foundations and government institutions could work together to develop solutions for social challenges.
However, the future of AI in the nonprofit sector will depend on more than the availability of technology.
Organisations will need access to funding, training, digital infrastructure and reliable technical support.
Donors and philanthropic institutions also have an important role to play. Supporting digital transformation should involve more than funding the development of software. NGOs also need resources to train employees, maintain systems, protect data and evaluate whether technology is creating meaningful improvements.
Most importantly, technology must remain focused on the people it is intended to serve.
An AI system that works perfectly in a city office may not be suitable for a rural community without reliable internet access. A chatbot that supports English communication may not be useful to someone who primarily speaks a regional language.
This is why local knowledge, community participation and human oversight must remain central to AI adoption.
Conclusion: AI Should Help NGOs Create More Impact, Not More Work
Did you know that India’s nonprofit sector is being transformed by AI? A new report from the Koita Foundation, released in November 2026, shows that 27 out of 36 respondent NGOs are already leveraging the benefits of AI. It’s great to see organisations really beginning to understand the usefulness of this technology.
Whether it’s during training and field support, program evaluation, data analytics, or within your internal operations and admin, AI is creating new opportunities for nonprofits to improve their work. Here’s what we know: the UNDP U-WIN solution demonstrates how well-crafted AI functions can augment frontline services and staff.
Now, to be clear – adopting AI is not the goal. NGOs need to weigh up if a particular tool solves a problem, saves time, improves services or allows the NGO to better understand the needs of its community. Not every NGO will need an advanced high-tech AI system. Sometimes, the simplest tools such as a report-writing system or a translation system, or sorting project files can go a long way.
So, the big opportunity is for us: How can technology be combined with people? AI can analyze data, recognize trends, and support us in our repetitive work. But it can’t duplicate the trust established by our fieldworkers among communities, or the understanding to help people through difficult times.
The future of India’s social sector is a future where technology is used responsibly and where people are at the centre of everything we do. We strongly feel at NGOs.ai that AI can empower NGOs and make their work easier. From writing proposals to planning the budget, the adoption of AI tools has the ability to reduce the administrative load on NGOs and enable them to work even better for their cause.
