Artificial Intelligence (AI) has garnered a lot of attention recently as the technology to watch, with leading experts in the AI space proclaiming it as ‘the new electricity’.

The improvement in the accuracy of modern techniques, especially deep learning and ease of access to AI computing infrastructure, means that more organisations are able to access AI technology. However, one of the biggest challenges is in understanding AI technology, where it can be used and how to use it.

For not-for-profits, it’s all well and good that the latest AI solutions recognises objects in video, creates artwork and predicts traffic patterns, but understanding where to use it in the organisation is a far cry from what is happening in the market.

AI is not remotely at a level where you can explain a problem to it and it will figure out the solution. The technology is still quite specific in its application and requires human intelligence to decide which specific model (or combination of models) to apply.

Based on my experiences and some of the common challenges I see, here are some of my suggestions on where AI can benefit NFPs.

Automating customer service with chatbots

Chatbots have been around for over a decade, however, recent years of improvement and ubiquity of National Language Processing (NLP) algorithms have made it much simpler to create a useful chatbot.

There are a range of chatbot platforms that let you create a conversational tree with a series of intents, with the ability to extend the platform with custom APIs if you need. Basically, it’s like creating a script and AI will try to match the best answer in your script to the question.

While large-scale case studies are relatively rare, IBM is predicting 85 per cent of all customer interactions will be handled without a human agent, which means streamlining of service interactions across many different industries and a general expectation to be able to interact with an organisation in this way.

For not-for-profits, chatbots offer a way to streamline common interactions and answer enquiries, as well as some specialised interactions. Instead of requiring staff to answer basic questions such as services, availability and locations, the chatbot is capable of answering these questions in a person’s stead.

They can also be extended to answer more unique questions with a bit of additional technical work. While chatbots will not replace human interaction for a complex query or interaction, they can save valuable staff and volunteer time in answering basic and repetitive questions and can be extended to perform medium-complexity tasks.

Donation modelling/prediction

While donation analysis has traditionally been primarily expert opinion and statistics, there is space to solve some of the most intricate challenges with AI.

Based on some of the problems I have seen, I believe there are a few specific problems in the area of donations and fundraising AI techniques can help with:

• Review the best candidates to become donors from a cold or warm dataset
• Predicting candidates for regular donors based on previous interactions
• Classifying regular donors into groups to maximise engagement and retention
• Classifying and re-engaging lapsed donors

Allocating resources in service delivery and volunteering

In NFPs that deliver service interactions and need to prioritise specific resources or engage specific supporters, AI can offer faster, automated ways to prioritise resources.

Two examples from other industries and their potential applications are:

• Predictive policy – where you best put your resource from the data you have available in response to capacity and time-based problems
• Finding blood donors – in this example, an NGO used public data to predict which people were likely to match different blood groups and be willing to donate

Getting started with AI in your organisation

With AI now a lot more accessible and comparatively easy-to-use than in the past, there are many opportunities for AI to streamline not-for-profit operations and provide additional insight and structure that was not possible before.

I expect that other the next few years, not-for-profits that wish to be leaders will find effective ways to streamline a few key areas of the organisation through digital technology and AI, giving them more time and scope to focus on strategic work and better service delivery.

As the sector is relatively early in its use of AI, our recommendation is to start with a small MVP with a well-defined and specific problem, and then expand into other areas of the organisation over the next few years as experience and internal support is built.

James Hornitzky is the Co-Founder and COO of Leafcutter. In my role at Leafcutter, I drive the tools, structures and direction of our organisation. Our mission at Leafcutter is to partner with not-for-profits and purpose-driven organisations and provide them with the digital tools and know-how to enable them to succeed in the way they fundraise and tell their stories online, to the way their teams work to deliver their programs and services.