These people will talk to you about their vocation, service, and care. However, in the day-to-day life of a social or non-profit organization, the reality of work is very far from that initial ideal. As indicated by recent studies, people spend a valuable part of their time at work on purely administrative tasks.

This time is spent on reporting, managing data, balancing receipts, or writing repetitive documents. That makes CSOs administrators of the paperwork, instead of activists for change. But with the popularization of Artificial Intelligence (AI) and Large Language Models (LLMs) within the reach of citizens, we are facing a turning point.

These tools offer a historic opportunity. Not to work less, but to work better. To let intelligent automation take care of the time needed for administration. And that the time saved (or recovered) is invested to enrich the relevance of the work of CSOs. To be active agents of change.

An opportunity to release, not replace

The 'promise' of automation is diluted by the fear of our obsolescence: "Is AI going to take my job?" And in the CSOs ecosystem, this question has a nuanced answer. Technology will not replace empathy, active listening, the ability to work together with a community, or comfort a victim in crisis. These abilities are irreducibly human.

What technology can and should replace, in most cases, is bureaucracy and more repetitive management tasks. Imagine spending your work week transcribing data from paper to computer, while AI scans and processes it in minutes. Freeing up those hours so that you can analyze that data in depth and thus work on the needs of the beneficiaries of your CSO.

With AI at our fingertips, you don't need days to prepare a funding proposal or struggle with bureaucratic formats and dense technical language. Based on your information, specifications, and samples of previous projects, an AI assistant will generate drafts tailored specifically for you. Meanwhile, you can spend the time refining the strategy and creativity of the project.

From "I have to do everything" to smart management

Adopting these tools implies assuming a change in the organizational and work culture. Redefine what we give value and priority to, what we call: work. It's not just about adopting new software in our toolbox. It is up to us to unlearn, reflect, and act. To face a change of mentality in our organizations and teams. Without forgetting our own change.

To manage it, we can start with three points:

1. Redefining productivity

The era of automation eliminates the productive equations of ‘who gives the most deliverables, or "who does them the fastest". Quantity and velocity are empty indicators. The possibility of doing more and faster is assured thanks to the use of AI. The real productive change is in improving the quality of what we co-create and, in its ability, to generate a real impact.

Any chat will generate a report from a simple prompt of a few words and a data source. The differential contribution is to ask your favorite AI for assistance to find information that you would miss at first glance. Try assigning this AI tool to a role in the prompt that prioritizes analysis over other points of view, and focus on what specific actions are proposed from these discoveries.

2. Losing the fear of 'letting go', without losing control

A very human challenge everyone faces when using Generative AI is to assume the emotional cost of human-machine co-authorship. That leads to a major dilemma: whether delegating our intellectual value and what we consider makes us relevant in our work: knowledge, creativity, our experience, and human experience, or not allowing Generative AI to take full control of decision making.

It is crucial to evaluate whether the answers of an AI are sufficient and trustworthy. Nobody should trust LLMs in what they can give without using corresponding filters. Make sure to continue to delegate tasks, goals , and your team by yourself, rather than leave AI in charge.

Both scenarios can be balanced with responsibility and critical thinking. To generate synthetic content with quality and truthfulness. Creating methodologies with AI tools in which CSOs can rely on the mechanical tasks , letting humans time to think, validate , and enrich the results. Having 'control' of the project doesn’t mean doing all the work manually.

3. Skills, erasing the 'hard' and the 'soft'

It is no longer enough to know about project management or cooperation. People who work in CSOs today must be radically curious. Do not stop learning. And gain technological knowledge. While it is not programming, you do need to know what programming is and become comfortable with code. In result, you will know how to take advantage of digital tools.

These skills are framed within the so-called soft skills. That increases our human abilities to understand and connect with the deep human context and our personal resilience. Socio-emotional competencies that allow humans to interact effectively with others and adapt to complex and changing environments (something that is difficult for machines).

Traditionally, they were subordinated to "hard" skills such as academic or technical knowledge (skills that AI does very well). But the labor market in the age of AI erases these hierarchies and elevates soft skills as essential skills. Strengthening these skills is an incentive for professional relevance.

Among the most relevant 'soft' skills at work in the social, environmental, and activism fields, we can highlight:

Deep empathy and intercultural communication. The ability to connect with people's realities beyond data, understanding cultural and emotional nuances.

Critical and ethical thinking as basic questioning skills. This can be applied to the results offered by technology to detect flaws and biases in AI. And take complex moral decisions in situations of uncertainty.

Adaptability and resilience. This skill is important to work in changing environments with the ability to learn and unlearn continuously. It’s essential to adapt to the constant changes and challenges imposed on us by our times.

Creativity as a strategic skill. Try to view AI as a great ally and a tool that empowers, not relegates, creativity. It is critical to imagine innovative solutions to structural or other problems that we are unfamiliar with.

It is the beginning of an unexpected journey

We must embark on the idea that AI is a great paradox. May it be used well to make us more human. Freeing up our scarcest and most valuable resource: time. Because the meaning of work and employment is changing. The role of humanitarian workers is evolving. We stopped being paper managers to become solution designers and community connectors.

Embracing AI is not 'surrendering' to technology. It is to use it to recover the essence of our value. The next time you're overwhelmed by repetitive tasks in front of a computer, remember that's not your call. Machines should be machines and take care of data , so that humans can take care of meaning and feeling. And let's be full-time activists and agents of change and not of bureaucracy.

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Additional sources used for the article:

Office for National Statistics (2024). Time use in the public sector, Great Britain: February 2024. Asana (2023). Anatomy of Work Global Index.

Disclaimers

This piece of resources has been created as part of the AI for Social Change project within TechSoup's Digital Activism Program, with support from Google.org.

AI tools are evolving rapidly, and while we do our best to ensure the validity of the content we provide, sometimes some elements may no longer be up to date. If you notice that a piece of information is outdated, please let us know at content@techsoup.org.

This content was created with AI assistance and has been reviewed and edited by Gustavo A. Díaz G.

"The Role of Humanitarian Work in the Age of AI: From Management to Activism", by Gustavo A. Díaz G. 2025, for Hive Mind is licensed under CC BY 4.0.