Understanding Agentic AI: what it means for not-for-profits

From Generative AI to Agentic AI: what’s the difference? 

If you’ve been exploring Generative AI—tools like ChatGPT, Microsoft Copilot, or Google Gemini—you’re already on the AI journey. These tools generate text, images, or code based on the prompts you provide. But recently, a new AI concept has been making waves: Agentic AI. If Generative AI is a smart assistant, then Agentic AI is more like an autonomous team member—one that doesn’t just respond to requests but can make decisions and take actions on its own. 

For not-for-profit professionals, this shift is important because AI is no longer just a tool you consult—it’s becoming a tool that acts on your behalf. 

What Is Agentic AI? 

Agentic AI refers to AI systems that can plan, decide, and act with minimal human intervention. Instead of just responding to prompts, these AI systems can: 

• Set and pursue goals 

• Make decisions based on real-time data 

• Automate multi-step processes 

• Adapt to new situations without constant human input 

Imagine the difference between asking a chatbot for fundraising email templates (Generative AI) versus having an AI agent that drafts, personalises, schedules, and even sends those emails, then tracks responses and refines its approach (Agentic AI). 

How can not-for-profits use Agentic AI? 

Agentic AI has practical applications that could save time, resources, and effort for mission-driven organisations. Here are a few ways it might help: 

1. Automated grant applications & reporting 

Instead of just suggesting grant proposal content, an AI agent could identify funding opportunities, draft applications, track deadlines, and auto-generate the required reports based on financial and operational data. 

2. Donor & volunteer engagement 

An AI agent could follow up with donors, segment them based on donation history, and send personalised messages at the right time to encourage continued support. It could also coordinate volunteer schedules, remind participants of upcoming events, and collect feedback post-engagement. 

3. AI-Driven project management 

From organising community events to tracking impact metrics, an AI agent could set timelines, assign tasks, send reminders, and even anticipate project risks based on past data, keeping everything on track without requiring constant human oversight. 

4. Automated compliance & policy updates 

Regulatory compliance is a challenge for many not-for-profits. AI agents could monitor policy changes, flag areas that need updates, and even draft internal compliance reports, reducing the burden on leadership teams. 

5. Proactive AI chatbots for service delivery 

If your organisation provides frontline support—whether legal advice, mental health assistance, or job training—Agentic AI chatbots could proactively check in with beneficiaries, track their needs, and recommend next steps. 

What are the risks & limitations? 

While Agentic AI sounds exciting, there are risks and limitations that not-for-profits must consider: 

• Loss of control – AI agents work autonomously, so they must be carefully monitored to ensure they make ethical decisions. 

• Data privacy – Handling donor or beneficiary data requires robust security measures to maintain the privacy of donors, beneficiaries and other stakeholders. 

• Bias in decision-making – AI can reinforce existing biases if not designed carefully. Organisations must ensure that the data used to train AI agents is correct, diverse and representative of the intended outcomes of the project(s). 

• Human oversight is still required – These AI systems are tools, not replacements for human judgment and compassion. 

Should your organisation start using Agentic AI? 

If you’re still getting familiar with Generative AI, don’t feel pressured to jump into Agentic AI right away. Instead, take a step-by-step approach: 

1. Understand Generative AI first – Make sure your team is comfortable using AI for content creation, summarisation, and automation before moving to more autonomous tools. 

2. Identify high-value, low-risk tasks – Start small. Automate administrative work rather than donor interactions. 

3. Test AI tools in a controlled way – Use pilot programs before fully implementing AI agents in critical processes. 

4. Establish ethical guidelines – Develop an AI policy that ensures transparency, data security, and human oversight. If you need help getting started with this, we have a DIY ethical artificial intelligence (AI) policy template available. 

Agentic AI has the potential to transform not-for-profits by streamlining operations and freeing up time for what really matters—your mission. But it’s important to approach it with curiosity and caution. Start small, test its capabilities, and ensure AI supports—not replaces—human relationships and decision-making. 

AI is evolving rapidly but remember, you don’t have to keep up with every trend. Focus on what’s practical and beneficial for your organisation today, and you’ll be well-prepared for the future.