By: Alexander Jivov | Co-Founder & CEO at Hopeful Inc. | Full-Stack Web Developer | Published Author
The move to artificial intelligence in the nonprofit world has been a steady, albeit slow march forward. While the space has generally been slow to adopt technology, the increasing competition surrounding noise on social media and declining donor pools has necessitated an acceleration in the adoption of digital solutions that bring in dollars.
Artificial Intelligence in particular is well oriented to not only handle, but completely transform the myriad of issues that nonprofits have been facing in the past two decades. With costs rapidly falling for AI technologies that focus on managing large data sets, in addition to their capability to streamline internal nonprofit processes and better targeting potential donors, the nonprofit sector is on the precipice of a technological advancement not yet seen before in its history.
The Battle of Data Overload
Hopeful was started because nonprofits, at their base level, were struggling to manage and act upon the massive amount of data they were handling. Without an ability to manage existing donors and internal data, it became extremely challenging to set internal goals and Key Performance Indicators, much less bring advanced technologies online to reach them.
To illustrate how critical the handling of data is at this point in society, it is estimated that 17 megabytes of information will be generated by every human being every second by the end of this year alone. No person is physically capable of accurately processing such a high volume of data for any given organization. With nonprofits collecting data points including payment information, demographics, donor interests and more, this issue is a particularly acute one for the space.
This is where we introduce artificial intelligence as a solution. AI, at its base level, is meant to accomplish three key objectives:
- Capture data
- Learn from Data
- Act on insights
Utilizing such a framework, the process of helping a nonprofit is fairly straightforward:
- Help smaller, younger nonprofits capture their data
- As the nonprofit grows and acquires more data, have the AI and the nonprofit’s users learn how that data can help them
- Provide data-backed insights to spur fundraising and reduce overhead related to content production
The volume of insights that a nonprofit can glean from its data is already staggering in its opportunity, but also provides a large barrier to entry for any nonprofit technology companies hoping to immediately tackle large, enterprise level charities, foundations, and supporting players. Each piece of a nonprofit’s operations must be closely examined to identify if and when AI is required – should AI be acquired before other essential functions are fulfilled, the organization risks its stability and success.
AI’s Impact on Internal Nonprofit Processes
According to a recent report from the AI in Advocacy Advisory Council (AAAC), 89% of nonprofit leaders believe that AI will make their organizations more efficient. Additionally, 73% of nonprofits believe AI innovation aligns with their beliefs and 75% believe AI makes their life easier.
This is a trend that has already started to appear on the implementation side, with 15% of nonprofits surveyed already having put AI technologies in place in the last year.
Despite this, 72% of nonprofits are either in the early stage of research or have no plans to implement AI in the next 12 months. While this clashes with the original statistics of heavy nonprofit support for AI’s impact on efficiency, it is also important to note that only 23% of AI nonprofit solutions are actually reaching their intended users today, which indicates a lack of adequate market penetration.
The strong support for AI Implementation stems from the immense impact AI can have on internal nonprofit processes. At nearly every level of a nonprofit organization there exist base tasks that can be easily automated to return much needed time to overstretched marketing, executive, and fundraising teams within the organization.
How AI can impact the inner workings of a nonprofit can be divided into what we call fully internal and internal/external processes. In effect, processes that allow the nonprofit to efficiently function from within and processes that allow them to bring in donor dollars. In the for-profit world, these would essentially be your ‘customer-facing’ processes.
For fully internal operations, much of AI’s impact comes from its ability to automate routine tasks. Specifically, AI’s ability to sort through the massive amounts of financial data nonprofits receive in order to quickly identify abnormalities and fraud is something that can be quickly applied to the sector and render massive benefits for nonprofits both large and small.
Furthermore, utilizing such data parsing abilities can also quickly allow nonprofit HR staff to screen qualified candidates and move them through the hiring process significantly quicker than a non-AI empowered team would be able to be able to.
Despite these benefits, however, it is the impact AI has on internal/external processes where nonprofits can truly benefit. From the ground up, nonprofits external advocacy, support, and fundraising services can be radically improved with the proper implementation of AI.
For instance, AI can provide advocacy and fundraising experts sophisticated metrics to assess what their donors really care about both on and offline. In Hopeful’s case, we have been working with nonprofits to harness AI’s processing power to identify which keywords, hashtags, videos, and images post
ed on an organization’s social media causes donors to support their cause. Using this information, Hopeful’s AI then creates automatic draft posts to save marketing teams time and energy from crafting messaging that is traditionally unsupported by supporting data.
AI, while being extremely effective at bringing in new donors, also has a key role to play in keeping existing donors in the funding cycle. Donor retention has been an extremely important challenge for the nonprofit space, with an average donor retention rate of just 45.5% across the industry as of 2018. This has been constant for the last decade, indicating a huge area of opportunity for new technologies to come in and change the status quo for the better.
AI’s ability to recognize patterns in massive datasets allows nonprofits to focus on what existing donors care about, and craft their programs and storytelling to maximize opportunities for re-donation. This is a critical revenue driver for nonprofits in its own right, with every $100 gained being subsequently offset by a staggering $96 in losses through donor attrition.
Conclusion
Nonprofits are ideally situated to benefit from Artificial Intelligence based technologies to increase their efficiency and drive extraordinary levels of revenue in the years ahead. While nonprofits have been slowly recognizing the need to begin implementation of innovative solutions to ensure their future growth, world conditions have been accelerating the sentiment that more needs to be done to catch up with for-profit technology practices.
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This article serves as a follow up to a recent talk I gave for the Canadian AI, Machine Learning, Data Science & Engineering Meetup, which covered the same topics as this article at a high level.
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