Adopting AI Doesn’t Have To Be All Or Nothing Nonprofits!
I have heard nonprofit community members express everything – from ‘we use AI daily’ to ‘we
want to adopt AI’ to a more panicked ‘our team is living a FOMO on AI moment.’
While I initially planned to write this piece for small and medium-sized organizations, I found
that even large organizations with fewer resource constraints often feel overwhelmed by AI due
to ingrained legacy constraints.
ChatGPT is just one high-profile avatar of AI. However, unlike most other technologies, this
technology seems (deceptively!) within reach for non-technical audiences. As such, AI evokes a
range of emotions – curiosity, fear, eagerness, nervousness, and anxiety.
Regardless of organization size, my consistent recommendation to resource-constrained
nonprofit clients and prospects remains – take it easy with AI!
First, let us take a step back!
But what exactly is AI, and how can nonprofits start leveraging it without getting in over their
heads? Let us break it down with a simple analogy.
Assume you do not live too far from your office. You now have several options to get to work –
either walk, ride a bike, or hop into your car. These are simply different modes of transportation,
each with its efficiency and speed.
Now, if we were to extend that example to options available to visualize your data – you could manually create charts and graphs in Excel (potentially labour-intensive and time-consuming), or you could use the advanced features of Excel such as pivot tables or basic macros for some automation (requiring some human effort), or better still, you could use a Business Intelligence (BI) tool to build automated, interactive dashboards that update in real-time (involving initial setup and a learning curve). Each choice increases efficiency, with AI, in this context, being all about choosing the most efficient ‘method/vehicle’ to handle your data visualization needs. AI transforms your data from one format to another using a blend of code, math, and/or algorithms. While doing so, it extracts insights for your organization or team.
Again, consider manually reading donor survey comments to identify broad themes
(Positive/Negative/Neutral) vs. using an AI model to classify those comments in seconds. The
common thread in both the above examples is the burst of efficiency brought about by the choice
made – whether it relates to the mode of transportation to work or the data transformation (for
visualization or to extract insights).
And the good news! There are several ways that nonprofits can experiment with AI without
breaking the bank, in other words without a significant upfront investment.
Dip your toes in AI Cost-Effectively!
Time and again, I find myself advising nonprofits not to dive into the deep end of AI right away.
A beginner in swimming classes starts in the shallow end before graduating to the deep end. So,
why not start with nibbling? Free or low-cost AI tools are great ways for nonprofits to nibble on
AI and experience it first-hand without a significant investment. Additionally, you can look for
tools with free trials to check functionality and alignment with needs, freemium plans, or open-
source options, and first understand how these can save time and expand reach and engagement
without additional staff time.
There is a host of tools that require little technical expertise but can get you more comfortable with automation and/or AI – from tracking expenses and spending patterns (e.g., Fyle, Expensify, Melio) to analyzing engagement metrics (e.g., Hootsuite, Buffer, Later), from extracting insights from surveys (e.g., SurveyMonkey, Typeform, Qualtrics) to scheduling meetings (e.g., Calendly, Doodle) – to name a few. However, you can significantly reduce process inefficiencies and free up staff time from repetitive manual work by switching to these automated and, in some cases, AI-enhanced tools.
To genuinely reap the benefits of AI, you need an incremental, experimental approach. The not-for-profit sector would not just be more innovative but, ironically, more impactful.
Preparing your Nonprofit Team for Adopting AI
AI is here to stay, so whether you are ready or not to plunge into the AI pool, there is tremendous
value in prepping your organization and team for the future. Knowledge is Power!
Consider setting aside some time each week to future-proof your organization by preparing for
an AI-led world. Despite the resource constraints of nonprofits, encourage your staff to pursue
online courses, attend workshops, and explore free resources to demystify AI and get
comfortable with it. If you are just starting out, I often recommend online courses such as ‘AI for
Everyone’ (by Deep Learning) or ‘Introduction to Artificial Intelligence’ (EdX). Other
invaluable resources for nonprofit teams include Google’s ‘AI for Social Good’, Microsoft’s
nonprofit community blog or AI for Good’s learning hub. Do keep an eye out for webinars or
conferences tailored for nonprofits on LinkedIn. The information is available out there. All you
need is some time, curiosity and an experimental mindset.
Common AI Pitfalls to Avoid
It is critical to ensure that chosen AI tools have proper security measures to protect sensitive
data. Even beginner AI solutions require careful implementation to avoid exposing sensitive
data. IT/legal experts are your best bet to ensure the chosen AI tools meet your security
standards.
Further, the risk of overreliance on AI outputs without human supervision, ethical concerns and
potential biases are other pitfalls to watch out for. For example., a conversation with a nonprofit I
advised on donor prediction models revealed their inadvertent use of a dataset biased against
certain demographic groups through their exclusion from the staff generated list of high-value
donors.
Start Small, Experiment & Always Question
Always remember, adopting AI does not have to be an all-or-nothing proposition. It never does.
Start small, experiment, and question if it is the right tool/approach for your team. Focus on
specific pain points or on improving existing processes. With more experience and confidence,
you can gradually expand your AI initiatives to more advanced use cases.
In my experience, a step-by-step approach to running an AI pilot project can be invaluable. Start
by identifying a specific, manageable problem, gather relevant data, choose an appropriate AI
tool or technique, implement on a small scale, measure results and gather feedback, and iterate
and improve. Measure the success of these experiments by looking at the time saved or increased
donor satisfaction. By thoughtfully kickstarting your AI journey, you can see substantial payoffs
over time!
In conclusion, making AI work for you does not have been a daunting exercise. By starting
small, prioritizing education and incremental steps forward while being aware of the potential
pitfalls, organizations can indeed thrive on their journey into AI.
The future of AI-led nonprofit work is here – take it at your own pace. Just do not be afraid to
take that first step.
PS. Any time freed up by adopting AI-powered tools is an investment in staff – it is theirs to
keep and invest in their well-being and health. Empower your team through AI!
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Indu Sambandam brings 20+ years of finance experience with global institutions, where data analysis was critical to decision-making. In 2019, she added a data science certification to enhance her analytical skill set. Since then, Indu has applied her business and data science skills to various impact projects. Over the last 18 months, she has exclusively focused on supporting the non-profit sector.