AI is one of those buzzwords that has recently taken over people's minds. We imagine AI as a futuristic, thrilling, and scary opportunity. But we don't always recognize how it affects us or our work. The cool thing is that AI is being brought into our sector and has a lot of potentials to help organizations leverage their data to do more focused work or analyze and find new opportunities.
In today’s podcast, our guest, Nejeed Kassam, Lawyer, CEO, and Founder of Keela, an impact technology company, talk about AI and how it helps small nonprofits manage their donors, mobilize resources, and raise more money.
Myths that Nejeed wants us to walk away from:
AI will replace your job as a fundraiser. Nobody's coming for your jobs. You can't automate fundraising. That's not realistic. What you can do is allow folks to be less burnt out, allow them to prioritize more effectively, allow them to see patterns, and focus their work in different ways. Effective use of artificial intelligence in fundraising is going to happen when it's deployed appropriately and then the fundraisers can take that knowledge and make decisions, steward better, and build stronger relationships.
Spending time on data has no benefits for your organization. Quality data has many benefits for organizations. Aside from compliance, data helps organizations to prepare for donor meetings, and then to use it for reporting and analytics. Nejeed advises organizations to spend time, be disciplined on their data, and do things right when setting up to save time going forward. Data can be a really foundational pillar for institutional capacity.
Nejeed’s thoughts around AI and Fundraising
AI predictions help drive decision-making - Using patterns from data that you have collected will help drive your decision-making. It gives you a good probability of the giving behaviors of the donors from your database. Data can tell your organization a story about your donors that is not recognizable when we don’t see the big data picture. It can also help you identify ask levels or make decisions about where you spend your time and energy.
Forecasting helps fundraisers. Understanding forecasting can help you understand your organization’s programming realities. It can understand whether you’re on track for where you want to be. You can make decisions when you have an idea of where you're going. It also helps identify when to ask for support, how much to ask for, and more.
Benchmarking for fundraising. Data helps your organization to measure efficacy and focus on thinking about how you are doing relative to your goals. Being able to check yourself, being able to hold yourself as an organization and as a fundraiser accountable is really valuable because then you can lean on all these data points in these predictive analytics and know where you really need to dig in and not.
Favorite Quotes from Today’s Episode
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“No, you can't automate fundraising. That's not realistic. What you can do is allow folks to be less burnt out, allow them to prioritize more effectively, allow them to see patterns, and, um, focus their work in different ways because of the AI ultimately the effective use of artificial intelligence and fundraising is going to be because it’s deployed appropriately and then the fundraisers can take that knowledge and make decisions and steward better and build stronger relationships.”
“But, you know, that's what I'm saying. It's predicting the future, but it's not, it's guiding behavior. If I can, instead of cold calling 900 people on my list who I don't know maybe interested, if instead, the data is signaling something is possible or likely, or has a high probability of happening that helps me do my job better.”
Resources from this Episode
Cindy W.: AI is one of those buzzwords that I feel like has really taken over a lot of mind space for people of late. We think about artificial intelligence as this futuristic and exciting and scary time or opportunity, but a lot of times we don't really see how it impacts us or our work and, the cool thing is there's actually a lot of opportunity or things that we, ways, I guess that AI is being brought into our sector and has a lot of opportunities to help organizations let's say leverage their data to do more focused work or understand and find opportunities that we might not have seen before. And really, if you think about AI or how this conversation is really talking about a way to filter or funnel your data to generate insights that will help you choose action or choose what action is most appropriate. So there's some really cool stuff in this conversation, all about AI and fundraising in the nonprofit sector. I'm really excited to dig in.
My name is Cindy Wagman, and I'm your host of The Small Nonprofit podcast where we bring you practical and down-to-earth advice on how to get stuff done in your small organization. We know that you are going to change the world, and we're here to help.
Today's guest is Nejeed Kassam. He is the CEO and founder of Keela, an impact technology company, dedicated to empowering nonprofits with accessible software. He's also the founder of Fundraising Kit, K I T, the world's leading AI-powered, predictive analytics tool built exclusively for fundraisers and nonprofits. He is a lawyer by training and also the founder of public policy organizations, Better Canada Initiative and Believe Vancouver, definitely very multi-passionate. He has done a lot of amazing work in the sector. He's also the writer author of the book High on Life with the cool foreword written by former Canadian prime minister, Jean Chretien and co-producer of the documentary Conversations for Change. There is a lot more, I could say about Nejeed but this conversation really speaks for itself. I think there's a lot of interesting things we can start to look at within our sector on using AI. So without further ado please join me in welcoming Nejeed to the podcast. Nejeed, welcome to the podcast.
Nejeed K.: Thanks so much for having me.
Cindy W.: I'm so excited about this conversation. I feel like it's very forward-thinking. Or maybe it's catching up.
Nejeed K.: Maybe but I'm not throwing shade anywhere, but I think at the office, my nickname is old man, and I'm like a curmudgeon. So to be talking about forward-thinking things is ironic and also you don't validate.
Cindy W.: Yeah. I think we could agree that as a sector. We're not quite the most digitally forward. And today we're going to be
Nejeed K.: How about we have a lot of opportunities.
Cindy W.: We have lots of opportunities to leverage what other people have paved the way for us to do. And today, specifically, we're going to be talking about AI. And I think most people like to have an inkling of an idea of what is AI? We think of it as, Amazon recommendations, Netflix recommendations.
Nejeed K.: Which is pretty good. That's a pretty good understanding of what it is. Yeah.
Cindy W.: Okay. Maybe I have, I don't, I think most people have that understanding and how it is emerging in our sector and how we can start to think about leveraging AI for fundraising. So let's start with what is AI because just because I can throw out Netflix and Amazon doesn't mean I have, and certainly, it doesn't mean I listen to it have a good understanding of what it is. So let's start there.
Nejeed K.: So I think what's really interesting about that question is sometimes we forget that the fluency that folks like yourself may have and something like AI isn't necessarily common knowledge. Even the term, AI is an acronym, which not everyone may know. AI stands for artificial intelligence and it's not like the matrix is taking over. So folks don't have to worry, but simply put it's the intelligence or predictive capabilities demonstrated by computers, by machines and unlike natural intelligence, which is displayed by humans and animals, which kind of has consciousness and emotional, it's an evolving decision-making framework, so to speak, that's built on more and more data. So think of it as like a technology that can take all these data points, processes, and ultimately make suggestions or recommendations and it's not going to take over the world. It's not going to be, it's not super scary. It's also not, it is based on what data, right?
It's not like you just say, here's data, go make decisions. There are software engineers and folks, and that, that go in and say, these are the inputs we think are useful. And then they train it on, previous sets of data to check how effective it is. And I think what's really exciting about AI as it evolves, it gets better. So it becomes more accurate. It learns how to weigh things differently. And I'm not an engineer, I'm a lawyer. Let's be clear, but that's the way that I understand it.
Cindy W.: Yeah. So if we use the Netflix example, it's not like the machine is watching all the films and analyzing them for what you might like next. It's saying the people who liked this film, like the more data we collect of like the people who have the same viewing patterns, they then go on to watch these things are those. So I'll put those in front of you.
Nejeed K.: And I think the term machine learning is like one that's also thrown around and that's like where it takes data and it makes recommendations or predictions and from those and the accuracy of those, it learns, okay, this is not as, as accurate. Cindy didn't watch Breaking Bad as suggested or she did, and she binge-watched it. I'm not going to judge on that one. What I am going to know is, over time those recommendations continue to get better. And a lot of it is around pattern recognition. A lot is around like you said before, somebody similar watched something. So maybe, it's making predictions on that. It's not like it's following your eyes and your giggle every time you laugh at a show, it's not Terminator. Although I'd love to have sitting in my computer and be like you should watch this.
Cindy W.: Oh my God fun fact. My husband thinks my son looks like Sean Connor from The Terminator, he keeps bringing photos.
Nejeed K.: I want to meet your son now? I'll be honest with you or maybe your husband. I can't tell ya.
What's exciting about AI that we kinda miss is it is just a tool, ultimately we can use it to help us automate mundane tasks, identify things that no human can possibly see support fundraisers, which is what today is really about in doing their job better. And I want to be clear right at the top of this post.
Nobody's coming for your jobs. You cannot hop, but so many folks like my God, we're going to fire the hole. No, you can't automate fundraising, that's not realistic. What you can do is allow folks to be less burnt out, allow them to prioritize more effectively, allow them to see patterns and focus their work in different ways because of the AI ultimately the effective use of artificial intelligence and fundraising is going to be because it's deployed appropriately and then the fundraisers can take that knowledge and make decisions and steward better and build stronger relationships. I think that is really, people, are scared of that, it's just not that scary.
Yeah, it's, that's such an, I hadn't even thought of that. But I totally can appreciate that people that it does feel like, we've, there's increasing dialogue around, the machines are coming for all of our jobs.
I'm happy to retire. I'll go golfing like that if they can cover my job that'd be great.
Cindy W.: Yeah. Well, I've heard, interestingly, I've heard that in the context of talking about universal income, but regardless of the other thing I hear, which I think is super relevant, a lot of smaller organizations feel overwhelmed by the idea of having a lot of donors because it's more information. They can't manage those relationships.
Nejeed K.: And spreadsheets you're right. By the way. And that's the thing like if you're on spreadsheets if you're not using your CRM effectively, if you are, ultimately, if it's just piles and piles, like my desk of paper that you need to know, oh, I talked to Cindy on Thursday, I took notes. I didn't record them, but there's a sticky somewhere. Yeah. The more data you have, the more stressful it's going to be. Yeah, I think, and this is I love this analogy because somebody told it to me really early in my career because I'm not a technologist. There are two fountain pens sitting on my desk.
Like I'm old, one of them was made in 1960. Okay. Like I am, I like it is pretty cool, but. We're not trying to build a faster horse, we're trying to build a car. And by saying, by, if you try to build a faster horse, you're in trouble, you are in trouble, you're going to be, it's scary. It's uncontrolled, it's out of hand, but if you're trying to do something, that's going to actually become more efficient and actually help the smaller works, I believe. It's actually the little orgs, the sub 5 million orgs that are going to benefit the most from AI because they're going to see opportunities that they're missing and ultimately be able to leverage potential gifts much better.
And I think. It goes to unwillingness or a fear of the unknown. For and you said it at the top of the podcast, you said sometimes we've been a little laggard. And I think that's because we operate from a place of fear. And I think that as we transition generations as gen X, gen, Y gen Z, kids become more and more engaged in our sector, they're going to move forward, whether the rest of us like it or not. And I think that changes the train coming. We can either get out of the way or get on it this is my assumption.
Cindy W.: Yeah. And, and hopefully, we can see how it can help us do better. So let's, I want to talk about that, the use case scenario. The other thing that I want to talk about is data in or data out is only as good as data in.
Nejeed K.: Yes. Ma'am
Cindy W.: Pick your order. Is it helpful to understand, how the data is used, how the data is being used before we understand that we have to have clean data or vice versa?
Nejeed K.: I think it's like asking, which came first, the chicken or the egg. It doesn't really matter. They're both important. So let's talk about data in and for, for a quick second, I'm going to go back and lean on my legal background.
The CRA requires those of us that are Canadian registered charities to have good data. And because it affects our ability to receipt, it affects, if we ever get audited, it protects the responsibility that we're given to steward being a charity, ultimately. And that's a designation that it's hard to get and it's easy to lose to be really honest.
Now you don't have good data and you're in trouble. You need to know who your donors are when they did, whether they were receded, where they issued receipts were issued. We all know all these things in Canada, in the US it's not that different, right? If someone makes a gift, you still have to receive that. You have to track all of that. I think what gets dangerous is when we think of data as only for those purposes, and if we take the approach that we don't have time to clean up our data, to record it in our CRM, to have that discipline, it's not make work.
And I think the, sometimes the assumption, especially from young technologists, like me who are like, oh, he's just, that's what he does. No. It's because it has so many benefits from compliance to ease of use, to prep, preparing for donor meetings, of course, and then to using it for reporting and analytics. I think that we. You're absolutely right. That it's only as good as the data comes in, but it's not that hard to have good data. You're not doing any algorithms. You're not doing math or pulling out your Abacus. You're simply just having discipline. And I think that's a, sometimes that's a scary thing, but really even a spreadsheet can have great data quality. And as long as you're disciplined about it, does that answer your question? Kind of
Cindy W.: And to bring that back to the AI piece, like you're only going to get. Good predicts or like a good record.
Nejeed K.: Forget about AI. I'm going to report it.
Cindy W.: Oh yeah.
Nejeed K.: AI is a little scary maybe possibly. Reporting is required. Your board needs to know how many donors do you had last year, how many repeat donors, how many people are recurring givers, what was your donor lapse rate? You can't do that unless you are disciplined. And I think, forget about AI, which we'll talk about it. Yeah. So to me, it's not like a no-brainer like, I don't want to be, I don't want to be pejorative here. I just think it's. It's important. Yeah, it's important. And sometimes, and it's, and the misconception is, oh, it's taking too much time. It's not going to pay dividends. The dividends are going to undoubtedly come from putting that time in. And it's a fraction of what it is relative to the return on that investment
Cindy W.: and it's foundational to you getting the kinds of insights that we're going to talk about, you cannot generate any meaningful insights or look at opportunities unless you understand and have good data. Yeah. Yeah. All right.
Nejeed K.: And I would tell everyone, use your donor management systems. It doesn't matter which one you have. We always used to do. Th the best CRM is the one you use doesn't matter the brand. It doesn't, of course, it matters, but it doesn't matter, ultimately, because if you are in love with it, if you are disciplined in it, the dividends are going to pay off so much.