The legacy we’ve developed with our nonprofit partners wields a massive treasure trove of experience. Find out how we could help.
Artificial intelligence, machine learning, data science and data analytics are powerful techniques used in private corporates to increase revenues and reduce costs. Data-driven strategies proved their efficiency in creating massive added values and revenues for traditional businesses. Before I clarify the reason nonprofit organizations should look to develop artificial intelligence for their processes, I recommend reading a survey McKinsey published in November 2020 to help you learn more about where AI is implemented so far and how private companies are increasing their revenues by developing AI technologies.
Artificial intelligence is not a new technology. In 1956, it was defined by John McCarthy, a Stanford professor for more than three decades, as the “science and engineering of making intelligent machines.” AI is when machines learn from human intelligence in order to automate repetitive tasks, augment cognitive capacities and facilitate the decision-making process.
There is overlap in the needs of private corporations and nonprofit organizations. Nonprofits have the opportunity to develop AI powerful algorithms to raise more funds, improve the efficiency of their resources and learn more about their members’ needs.
In this post; from an AI expertise perspective, and due to the fact that I help co-found Data for Good, I would like to share a few concrete examples where AI can make a difference for nonprofit organizations:
Organizations have a huge number of repetitive tasks that are time-consuming and not necessarily involving high-cognitive capacities. For these tasks, two solutions can be deployed to automate the repetitive tasks, reduce costs and risks of human inputting errors. Machine learning extracts patterns to define repetitive tasks and automate them. Once tasks are known, robotic process automation (RPA) tools automate the process.
Nonprofit organizations have a great asset of data about their members and consumers. Machine learning and data analytics algorithms extract valuable insights that help the organization propose the most appropriate offer to support members. AI proposes actionable insights by exploring various contexts to personalize messages for the best consumer experience.
Answering routine questions by staff members can be time-consuming. Developing AI chatbots and cognitive research engines can reduce costs and increase consumer satisfaction. In many cases, waiting for an answer for hours or days can break relationships with members. AI chatbots should remain very clear and rapid so members don’t get frustrated. We all have experience with chatbots that cannot answer our questions, even if we express them very clearly. Machine learning and natural language processing algorithms can create efficient communications with internal and external users.
Artificial intelligence extract knowledge from data. These valuable insights can help clarify the big picture and help managers and executives make better decisions. By analyzing the massive data assets around offers, member feedbacks, sponsors and information on social platforms, nonprofits can augment the cognitive capacities by using these valuable pieces of knowledge to refine strategies and drive the best operational decisions.
Understanding your supporters’ interests helps you proposing the right program and ask for the appropriate donation amount. Supporters are communicating via social platforms and their interests can change. This year of pandemic presents many examples of flexibility even for supporters. Learning from internal and external data by developing Machine learning and deep learning algorithms extract valuable insights about existing supporters but also potential new supporters.
A Study from AI in Advancement Advisory Council mentioned that 89% of nonprofit professionals believe that AI can make their organization more efficient. However, before investing in AI solutions, I recommend nonprofit organizations look into the services of AI experts. Industry experts can identify where AI can help reduce costs and improve the efficiency of resources. This, in turn, can help nonprofits learn more about their members, supporters and potential new audiences. In some cases, developing internal AI capacities is less expensive than acquiring an AI solution.
Artificial intelligence is a powerful technology with a bright side to increase your impact and the benefit for your members, but tech engineers and top managers should be aware of the potential challenges and risks that accompany it.
For instance, to automate repetitive tasks, you need to exploit your data legacy; this means collecting, understanding and cleaning your data to extract from it meaningful insights. When machine learning algorithms are deployed in your systems, users are invited to work more efficiently. This step must be prepared by redesigning business and operational processes to help users learn their new way of working. AI implementation is more than a tech journey. It’s a human being’s major challenge to learn from all the data legacy and redesign processes to create the less expensive execution and the best member experience. People need to be supported to integrate the transformation challenges and contribute on achieving the successful outcome.
When it comes to user data, it’s very important to care about the AI ethics principles to avoid bias, discrimination and other forms of injustice. AI algorithms predict from the existing data and extract patterns that reflect defined processes. In other articles, we can dive deeply into AI ethics principles and how nonprofit organizations are working to save our privacy and freedom as human brings.
Machine learning, deep learning and other artificial intelligence techniques can be daunting to implement and potentially cost-prohibitive, depending on the experts and solutions you employ. The best first step to approaching this tech is defining the pain point you are trying to solve using AI. Then, using this information, build incremental experimentation to be aware of the progress and challenges alongside. Nonprofits don’t have to integrate AI into every single area of the organization. Leaders should evaluate and consider if an opportunity exists in their nonprofit for innovative tech like AI.
Apogee Suite of NLP and AI tools made by 1000ml has helped Small and Medium Businesses in several industries, large Enterprises and Government Ministries gain an understanding of the Intelligence that exists within their documents, contracts, and generally, any content.
Our toolset – Apogee, Zenith and Mensa work together to allow for:
Check out our next webinar dates below to find out how 1000ml’s tool works with your organization’s systems to create opportunities for Robotic Process Automation (RPA) and automatic, self-learning data pipelines.