Building the Future AI Enabled?NGO

Challenges, opportunities, and next steps to build the 21st century NGO.

Artificial intelligence (AI) has the potential to help tackle some of the world’s most challenging social problems. 

This sounds good in theory but how do we walk the talk? 

First of all, we need to understand that despite a lot of attention toward fancy and futuristic AI, there are hundreds of problems that can be addressed with current technology. 

What is needed is a mindset shift towards innovative and collaborative practices to solve current adoption challenges. 

Walking the talk

Gathering data 

Data is a prerequisite for AI. After identifying their use case, NGOs need to find creative ways to gather relevant data to train their AI algorithms.

It is a common problem that there is not enough quality data to work with. However, there is also a common misconception that you need a perfect data set to get things started. This is not only technically wrong but also would mean that the vast majority of organizations will not be able to do any meaningful work with AI any time soon. 

NGOs can leverage the evolving amount of open-sourced datasets as well as generate their own data, which results in incremental progress towards creating higher returns on impact and value. 

Realizing quick wins 

No meaningful AI implementation has happened by preparing a few slide decks only.

The actual learnings to make AI a success are happening in the real world. NGOs should use pilot projects to get the flywheel turning as soon as possible. Instead of doing only one pilot project, several pilot projects will increase the odds of creating at least one significant success. This will result in lots of lessons learned, buy-in from stakeholders, and thus in overall progress towards adoption. 

Embracing collaborative models 

More than 50 percent of AI solutions fail due to a misalignment of stakeholders, no metrics, and no contextual AI strategy.

One big reason? Trying to apply old development practices and top-down approaches including silo-driven work. However, running AI projects successfully requires solving multiple problems in various domains. No single person has all the knowledge to cover everything.

A bottom-up approach takes the development process out of the lab and into the real world by embedding diverse perspectives and open dialogue, where the user or customer of the solutions can be integrated into the development process. This increases the chances to build inclusive and trustworthy solutions.

Today, still most AI is developed in isolation of the people and social circumstances that make them necessary in the first place. To change this, we the people need to come together and enable truly human-centered development making the world a better place.

There’s no doubt that AI can help non-profits advance their missions and make the world a better place. However, like with any organization, they must have a plan in place as they launch their AI journey.

An invitation to discuss the present & future of AI in the NGO space

If you are interested in a meaningful conversation including real-world case studies, feel free to join us in our upcoming demo day with leading tech executives in the NGO space.

Register at here