What problems does generative AI solve for NGOs, municipalities, and businesses

1. Effective content creation One of the key problems for civil society organizations is the lack of resources for regularly updating websites, social media, and information platforms. Generative models such as ChatGPT or Copilot allow creating articles, reports, letters, and information campaigns without the need to engage large editorial teams. This enables maintaining constant communication with the community, donors, and business partners without spending significant effort.
2. Communication automation AI tools help not only create content but also set up communication with users in real-time. ChatGPT-based bots can answer typical citizen questions, help with form filling, consult on municipality or NGO services, even at night or during peak load periods. This reduces pressure on staff and improves service quality.
3. Inclusivity through language support International organizations often work in multilingual environments, and adapting content for each audience takes a lot of time. Generative AI can instantly translate texts and adapt them to the local cultural context, making information accessible to more people. This is important not only for businesses entering new markets but also for civic initiatives that strive to be closer to each community member.
4. Scaling educational programs NGOs and socially responsible companies often conduct training and educational activities for different population categories. Generative AI helps create adaptive educational courses that adjust to each student’s knowledge level, generate examples, tests, explanations, increasing learning effectiveness.
5. Resource savings For many organizations, access to technology means a compromise between quality and budget. Generative AI allows significantly reducing costs for content, communication, and training without losing quality. This helps direct saved resources to other important areas — for example, expanding activities or launching new programs.

Examples of use

• ChatGPT — as a virtual assistant Organizations use ChatGPT to create chatbots that provide instant feedback. For example, municipalities launch bots to advise residents on administrative procedures, social services, or local initiatives. This allows quickly responding to standard requests and relieving hotlines.
• Copilot — for increasing specialist productivity Copilot from Microsoft is a tool that integrates with Office 365, helping specialists create presentations, reports, and analytics much faster. Imagine that a project manager in an NGO can prepare a grant proposal or detailed report for donors in a few minutes without engaging external consultants.
• Midjourney and DALL·E — creating visual content Social initiatives often need bright visualizations to draw attention to their campaigns. Generative models like Midjourney or DALL·E allow creating unique images for posts, presentations, or banners in a few minutes. For example, an NGO working on ecological issues can create a series of creative visualizations about climate change without engaging expensive designers.
• Signpost — information support for refugees This is an example of large-scale AI use, where the system helps refugees receive necessary information in an understandable format. Thanks to generative AI, these services can work 24/7 and adapt to user needs.

Benefits of using generative AI in social initiatives

• Productivity and scalability The main advantage of generative AI is the ability to scale efforts without additional team load. Content creation, responding to requests, idea generation — all this can be performed at a much larger scale than human resources allow. For NGOs, this means the ability to simultaneously conduct several information campaigns, cover a larger audience, and remain constantly active.

1. Cost reduction AI allows significantly reducing costs for content creation, user service, and educational material development. Organizations that previously needed specialists in copywriting, design, analytics, can now automate a significant part of these processes, leaving human participation only for strategic control and verification.
2. Response speed AI works without breaks and weekends. This allows responding to user requests instantly, even at night or during peak load periods. In crisis situations — for example, during humanitarian emergencies — such immediate reaction is critical for providing support.
3. Increased personalization quality Generative AI can adapt responses and content to specific user needs. For example, a bot can offer information considering the user’s age, region, or language, which increases engagement and trust levels.
4. Knowledge accessibility Thanks to generative AI, even small organizations can access advanced technologies and knowledge that were previously the prerogative of large corporations. This helps reduce digital inequality and gives NGOs the opportunity to compete for audience attention with big players.

Challenges and risks

1. Need for human control

2. Ethics and responsibility issues

3. Trust in AI

4. Dependence on large corporation technologies

5. Data privacy issues

Socially responsible businesses: how generative AI helps scale good deeds

• Educational initiatives. Companies create automated educational platforms or chatbots for teaching clients, employees, or citizens. Generative AI allows scaling these initiatives, making learning accessible to a wider audience — from school students to people who need requalification. For example, Microsoft uses Copilot for teaching programming or improving digital literacy among youth and veterans.
• Communication campaigns. Brands use AI to create content that supports social initiatives — from environmental campaigns to mental health support. For example, automated videos, social media posts, email newsletters can be generated by AI, which significantly reduces costs and accelerates project launches.
• Supporting volunteers and charity programs. AI helps in logistics, managing volunteer or donor databases. For example, chatbots that answer volunteer questions or automatically coordinate their work ease the operational load on socially responsible companies.

Recommendations for NGOs: how to implement generative AI effectively

1. Start with small but meaningful projects. You don’t need to immediately integrate AI into all processes. Start, for example, with creating content for social media, automating responses to common questions, or generating educational materials. This will help the team understand the potential and limitations of the technology without unnecessary risks.
2. Invest in team training. Before scaling AI use, it’s important to prepare the team to work with these tools. Organize workshops, training sessions where specialists can learn the capabilities of ChatGPT, Copilot, Midjourney, or other services. This will reduce the fear barrier for new technologies.
3. Create ethical policies for AI use. Define clear boundaries within which AI use is allowed. For example, specify which topics require mandatory human verification (especially sensitive issues related to human rights or health). Write rules for working with personal data to avoid privacy violations.
4. Collaborate with technology partners. Find IT companies or consultants who will help properly configure generative AI tools for your needs. This can be not only bot or platform integration but also auditing existing processes to determine where AI will bring the most benefit.
5. Test different tools. ChatGPT, Google Bard, Copilot, Midjourney — each has its strengths. For text content, it’s convenient to use GPT, for design — Midjourney, for automation in office documents — Copilot. It’s important to find the combination that works best for your organization.
6. Ensure transparency with beneficiaries. Notify your audience when you use AI, for example, when creating educational materials or responding to requests. This helps maintain trust and avoid misunderstandings.
7. Use low-code/no-code solutions. Such platforms allow configuring automation processes, integrating AI into work tools, and creating basic digital services without deep technical knowledge.
8. Regularly review results. After implementing AI solutions, it’s important to evaluate their effectiveness: which tasks were successfully automated, how much time was saved, how much audience satisfaction increased.

Generative AI — a driver of change for civic initiatives and business