Artificial Intelligence has quickly become an integral part of everyday work. From text generation to document analysis, many organisations are experimenting with it, and its use is also growing rapidly within the non-profit sector.

Yet practice shows an interesting pattern: many organisations now use AI regularly, but only a small proportion experience actual structural changes in their work. In many cases, AI mainly saves time, while the real impact on processes and decision-making is still limited. This is not surprising, as in many teams AI is mainly used as a loose tool for individual tasks, such as rewriting a text or summarising a report.

From tool to the ‘Agentic NGO’

The real value of AI only arises when technology is linked to existing processes and systems. Within organisations, we see the deployment of AI evolving. On the one hand, there are simple chatbots with set rules. One step further are ‘copilots’: smart assistants that support employees in a variety of tasks.

However, the most significant shift is the arrival of AI agents through platforms such as Agentforce. This paves the way for the so-called ‘Agentic NGO‘. In this model, non-profits work with specific agents, such as a Fundraising Agent or one Grantmaking Agent. These agents can independently plan, reason and execute actions based on data from your own CRM (Customer 360).

Practice: Start with processes

For non-profits, there are great opportunities there, for example around relationship management, communication with volunteers or processing large volumes of documents. In practice, for example, we see how AI can successfully help in automatically checking incoming project applications for completeness. This reduces manual work and ensures more consistency in reviews.

An important lesson here is that AI does not start with the technology, but with the processes. A useful exercise is to first identify which day-to-day tasks (such as filing, incoming communication or reporting) take a lot of time. Only then look at where AI can help speed up those tasks.

Look for the ‘Quick Wins’

You then map these processes onto a cross-section of axes. By ordering processes on impact (what does it deliver?) and feasibility (how easy is it to implement?), you immediately discover the so-called ‘Quick Wins‘. These are the solutions at the top right of the matrix that add a lot of value and are easy to implement. They often turn out to be surprisingly practical applications.

Data, trust and small steps

Of course, for organisations with social impact, privacy, data security and transparency also play a crucial role, especially when working with sensitive donor data. A simple rule applies here: AI enhances what is already there. When your data is well organised, AI provides valuable insights. If the data is messy, AI compounds that problem.

The most successful organisations therefore start small. They improve one process or automate one concrete task, and build from there.

Technology as a silent force in Marketing and Service

In the coming years, AI will increasingly integrate seamlessly into the systems organisations already use. It thus directly helps save time for the things that really matter. Think, for example, of applications within the Marketing Cloud, such as intelligent segmentation and the optimisation of shipping times. Also in the Service Cloud AI can speed up processes, for example by automatically creating a case summary (case summary) to generate a draft reply (draft reply) ready.

As a result, technology is becoming less and less a visible, separate tool, and more and more a natural part of the way they work. The organisations that benefit most from it know how to effectively connect AI to their mission, processes and data. That is where the real power of AI lies: in quietly improving how we work and making the world a little bit better.