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The Smart Communications Podcast
Episode 202: How can you put AI to work for your nonprofit?
00:34:32
AI is here, now what? Explore how nonprofits can move past the hype to use AI thoughtfully, ethically, and strategically to support your mission and people.
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This is the Smart Communications Smart Communications.
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Smart Communications Podcast Developing the Voices Voices.
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Developing the voices of determined nonprofits Brought.
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To you by Big Duck.
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Welcome to the Smart Communications Podcast. This is Farah, Trumpeter, Co Director and Worker owner at Big Duck. Today we're going to ask the question, how can you put AI to work for your nonprofit? It's a question I know continues to be on many people's minds minds these days and we're in fact recording this conversation in December to publish right away in the New Year in January. So I am sure as you're starting the year you continue to wonder about this and I hope this conversation provides value. We have had several other conversations on the Smart communications podcast about AI, including episode 185, how can you approach AI with an equity lens? And episode 173, how can you use AI for strategic communications? So if you're wondering about that and more, you can always find links@bigduck.com insights including the transcript for this conversation. But let's zoom out. We're going to talk bigger picture today with two folks I've known for many years. First, Cheryl Conti, who uses she her, is the Chief innovation officer@brightworksai.com which helps mission driven teams adopt AI confidently, ethically and in ways that strengthen your people, programs and purposes. She is also a Senior advisor for PosterChild AI and co founder of Change Agent AI, mission driven and game changing AI powered startups. Cheryl, welcome to the show.
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So glad to be here with you Farah. Thanks for having us.
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Of course we also have Darian Rodriguez Heyman, who uses he him pronouns. Darian is the founder of Helping People Help, specializing in AI implementation, fundraising, board development and strategic planning for mission led organizations as well as the former Executive Director of the Craigslist foundation, which I think is how I met him many moons ago through the Craigslist bootcamp for Nonprofits, I think 2008 or so. So we're going back. Darian is also the founder of ai4np.org, a fiscally sponsored initiative by NTEN, a digital learning hub for AI for good resources and responsible AI adoption. He he's written several books including Nonprofit Fundraising One Hundred and One, which I also had the pleasure of contributing to as an expert in a chapter about year end annual appeals and membership campaigns. Darian, welcome to the show.
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D
Thanks so much for having us. Great to see you again.
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Always. Well, Cheryl and Darian co wrote a best selling new book called AI for putting artificial intelligence to work for your cause and we're going to get into that and more. So let's start with the book. The book, AI for Nonprofits features insights from over 50 AI experts intended to help nonprofit leaders embrace new tech to advance fundraising, marketing, program delivery and operations, including several folks who've been on the show before. Afuwehr Bruce, Amy Sample Ward, Joshua Pesque, and George Wena. Just got to give them all a shout out and we will link to their podcast conversations. So there are so many different roles people can play in an organization. They could be an executive director, they could be running comms, they could be running fundraising, they could be a board member, they could be a consultant like Big Duck or a funder. But who is this book for? If you had to say who should read this book? Cheryl, let's start with you.
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Sure. Well, lots of people are reading this book. You know, we were really excited that when it launched, you know, it achieved the top 10 of business and finance, which is a big, very general category. It hit top five in AI number one one in office automation, which is also, weirdly, a pretty big category, number one in nonprofit and charitable organizations. But, you know, I think there's a broad appeal and you know, they're of course nonprofit leaders, philanthropic professionals, people in higher ed, bcors, mission driven startups. Lots of chiefs of staff have reached out to me. So, you know, I think there's a broad appeal to the book. And I think that even in the business world, you know, the more for profit world, there are people who are looking to the nonprofit community, you know, as a place where they can find out, how can I, how can I ethically and responsibly integrate this technology?
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B
I love when we can talk about the business community learning from nonprofits. It's not always the other way around. In fact, the business community has a lot to learn from the nonprofit community. So definitely appreciate that. Well, AI is everywhere these days and everyone is talking about it. But when it comes to using it strategically, I know many folks are overwhelmed. They're not really sure how to approach it beyond just using it ad hoc. Darian, why do you think that is?
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D
I mean, I think like many technologies before it, people kind of dive into using it without taking the time to think about what does success look like. And ultimately, to your earlier question about who's this for? It's for mission led leaders, you know, first and foremost. And by definition that means we are led by our missions. And so the question has to start with how can this new tool help me advance my mission? And in particular, we sort of looked at four different top use cases and applications, around fundraising, around marketing and community engagement, around program delivery and evaluation, and around back office operations. Because those are sort of the four things that we're all trying to do, whether we're focused on climate change or education. And so really starting with what we're hoping to achieve is absolutely critical.
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Cheryl, anything you add to that, I.
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Mean, Darian is brilliant. So not really, except just sort of zooming out. I think people sense that a big change is on the horizon, that life is going to look different. And we talked to a number of futurists and independently they all said, look, in the next five years you're going to notice things changing, things being a little bit, you know, new and different. In 10 years, everything, everything will be different. The way we work, the way we play, the way we shop, the way we teach, the way we learn, everything is going to get touched by this. And I think that's overwhelming. I think people are right to feel a little freaked out, you know, social media, I don't think anyone expected how much social media would rock our global civilization. So that said, there's a real opportunity here, I think for mission led leaders, as Darian put it so well, to take the reins and show real initiative, drive and leadership in this moment.
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D
And if I can just add one more comment, I think we talked about the critical first step of what are we trying to achieve here. But the other thing to the heart of your question, Farah, about how should leaders be adopting this tool in order to ensure, to Cheryl's point that it's responsibly adopted is part of why they get overwhelmed is they try to dive in the deep end of the pool. And so the really critical piece is to sort of crawl, walk, run and start with some of the really simple use cases, encouraging at home use, using it for things like social media like Cheryl just mentioned and content creation where it's low hanging fruit really and you know, as you graduate and get more comfortable to move up the ladder. But ultimately I think the idea of organizational and strategic adoption as opposed to just, oh, that's something that two or three of our people like to play around with, that's at the heart of what is truly needed from a standpoint of adoption.
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B
Now I imagine when you were doing research on the book, you found some organizations that maybe were higher up on that ladder, as you were saying, Darian, are getting it, are using AI responsibly organization wide, not just through one or two people. And I'm curious, what does that look like in practice, maybe there were things you've seen organizations do which are evident of that. Maybe there's a story of a specific organization. But I'm wondering if you can paint a picture for us of that sort of more organization wide, responsible, intentional use of AI.
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D
Yeah, you know, what I would say is that in truth, when Cheryl and I first started this project, I wanted to use nothing but case studies from on the ground, smaller to mid sized nonprofits speaking in the past tense about what they had used AI for and what they learned in the process. And I still can't write that book because we're not there yet as a field. And so instead we did talk with a lot of consultants and providers, and there are a couple of case studies from Save the Children and Lung Cancer foundation of America that can provide a really helpful roadmap. But in general, it's still really early days. And where we're at as a field and as an industry is there's a lot of interest. But I mean, the numbers drop off a cliff when you go from the standing room only workshops on AI101 to the amount of organizations under 10% of nonprofits in the country that have any kind of organizational strategy or policy in place. And so that, vera, is at the heart of the question is just starting out with a couple pieces of paper of what are we trying to do here? What's the sensitive data that we need to protect and how do we handle that? What are the acceptable use cases and what are the painful processes that we're trying to automate and enhance and streamline, whether that's around fundraising or other needs. And so that is sort of like first step. And it also goes to your last question, but then they're also taking this sort of pilot program approach to rolling it out. In the case of Lung Cancer foundation of America, they worked with whole Whale, you mentioned George Williams and his team over there to create a custom large language model. It was sort of a virtual member of their team that they called onug. And the idea was, first of all, that directly addresses the needs around sensitive data and data security, which is one of the biggest barriers impeding adoption. But it also was trained on their programs, on their organization. So it spoke in their voice. It helped them with their podcasts, with their social media, with their fundraising and beyond. You know, we're all creating content all day long. And if we can use an army of robots to, you know, serve as our digital interns and kind of backfill us so we can focus on the critical Work of building human relationships and strengthening those ties. That's at the heart of really what I would say is the answer to that question.
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Yeah. And I would add, you know, as a co founder of Change Agent AI, you know, Change Agent AI was created sort of by the nonprofit, you know, community. For the nonprofit community. Right. It is an alternative for those people who are pretty squicked out by, you know, OpenAI and Anthropic and Google and, you know, have concerns about, you know, whether it's the ecological effect or, you know, data privacy and security. You know, Change Agent really answers a lot of those questions, you know, in terms of can we rely on this language, Right. Being something that feels authentic, you know, to mission led folks, you know, and Change Agent, you know, they have a bunch of people, a growing list of folks like seiu, Moms, Rising Community Change State voices who get it right, that, you know, we need to take control internally and create an environment because the reality of the situation is the ostrich model of coping. That cope is not going to get it, y'.
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All.
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Something. Studies pretty reliably show that 30 to 50% of employees in any given organization are already using AI. That might be overtly. A lot of it is covertly. That creates an awful lot of, you know, risk, I think, for organizations. And the time is now really to get on top of this, you know, so smart orgs are setting policies, you know, they're upskilling their people, they're analyzing their workflows and figuring out, you know, where you can insert AI, where I can intervene. Because I think, you know, Darian and I say all the time, look, you know, like, think about the things that your team is doing that are the most repetitive, the most boring. Right. The most time consuming, the most expensive. And there's a pretty good chance that there might be an AI intervention that takes that more or less off your team's plate so they can do the things that only human beings can do and enjoy their work. You know, the reason they got into this in the first place, which is connecting and helping other people.
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Great. Well, I want to, I want to direct something more to those ostrich friends out there. Ostriches. What is a plural? I guess ostriches. So for the folks who might be skeptical and still deeply concerned about AI, maybe they're putting their head in the sand. Maybe they're just turning away from it. What advice would you offer to help them overcome their fears or their worries?
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D
Yeah, I mean, I think we are seeing sort of our heads in the sand largely across the sector. And there's a couple key reasons for that, Farrah. I mean, number one is, I mean, Cheryl and I wrote a book on AI for nonprofits, so we're obviously drinking the Kool Aid, but as we get out there in the world, what we're seeing is a couple problems where we're not meeting the sector where it's at. And that starts with people are more worried than excited about the potential for AI in the sector. And so we cannot talk around the fears and concerns that are providing a big obstacle to adoption. We need to help people understand that those concerns are valid, whether it's around job loss or data security or environmental impact. Again, we're mission led organizations, so there are a lot of concerns. They are very well founded and we need to tackle those head on and sort of demystify some of those so people understand the tactics and the strategies that they can use to mitigate those very realistic concerns. We also need to talk about AI as a tool because nonprofits are busy. We're facing unprecedented demands on our service and headwinds from the federal government and beyond. And so people are busy. And unless you could talk to them in the language of here's how it can advance your work and make your life easier and help you solve some of the problems that are at the core of your mission, then we're going to miss folks. And we can't just talk about technology for technology's sake or how it works or, you know, and so I think those are some of the key issues is really, you know, talking to those fears and talking about the fact that you can use a custom large language model to address different data security, that you can look at the environmental implications and in context. There's a lot that can be said about that and ways to mitigate that, that we can directly tackle fears around job loss by looking at AI as the next version of the spreadsheet or the calculator. And I've been doing this work for 25 years. I've yet to meet a nonprofit that is overfunded and over staffed and has solved all of the people who need help from them. We're all struggling and under resourced and under capacity. And so if we can leverage this technology to double our effectiveness and efficiency and free us up and sort of offload some of the more menial tasks so we can focus again, to Cheryl's point, on those human relationships, hallelujah. But it needs to be framed as such. And we also need to provide people with the really Clear, tactical advice of how to adopt this stuff responsibly and at a pace and a scale that they're comfortable with.
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A
Yeah. And I would just add, you don't want to be using a quill pen when everybody else is using a computer, y'. All. Okay. Like, literally, you know, the Constitution in the United States was written with, like, people who use knives on feathers, and then they would dip it in ink. And, like, you don't. We're past that now. And, you know, competing messengers, competing organizations who see very different solutions or no solution to the problems you're addressing are going to be using this technology. So you don't want to bring a spork to a gunfight. I think the time is now to start listening, start educating yourself. Consider a survey internally just to see where people are. There's so much that you can gain with this technology. And more importantly, there's no getting around it. There's no getting up over it. There's no getting down under it. Like, it's coming for you. Every. There is no area of your life in which AI is. Is not going to play a role. And I. And just quickly, Farrah, I know that you have a very sophisticated audience, but sometimes people find it helpful when I sort of break down kind of the three different kinds of AI, right? So there's classifier AI, and, you know, that's AI that's in the background, and you have been using that for 10 or 15 years and more. More importantly, it's been using you. You. Right? This is your spam filters. These are, you know, figuring out which of your emails are most important. This is digital advertising, right? Like, this is how UPS gets your Amazon packages to you and how Amazon knows, you know, what you looked at yesterday, right? So then that's classifier. Then there's generative, and I think that's the AI that really sort of woke people up. Oh, my goodness. This is AI that can create. Right? And so, you know, that's really having a big impact on our culture, you know, that we're still, I think, adjusting to. And then finally there's agentic AI. And agentic AI is AI that can think, plan, and act. So, for example, you know, Farrah, you probably met Lexie@skedge.com, you probably figured out. But I would say 80% of people to whom I introduce, Lexi, don't realize that she's a robot. So I use skedge.com as sked k e j.com as a scheduling tool. And I can just say, hey, Lexi, you Know, I just CC her, you know, someone wants to meet with me or have a podcast, you know, can you work it out? Because I can barely cope with this space and time, let alone, you know, figuring out other spaces and other times. So Lexi is a robot that can literally just start having a conversation. She can look at people's calendar, you know, their calendar links, you know, she can look at a doodle and just suggest times and when, you know, when she's decided with the other person or people what a time is, she'll put the calendar invite in my calendar. I don't have to do any of that. So, you know, that's relatively new technology. I mean, skedge is new probably within this last 12 months or so. So you're going to see more AI that looks like that. And I think now is a good time to start experiment. As Darian mentioned, start pilots. Start thinking about, you know, the future of your organization, which is probably going to involve not just a new look at the technology you're using and how your vendors, your software vendors, like an action network, are integrating machine learning and AI into their products, but also change management. You know, if, if AI can take over certain tasks, what does that then create in terms of what your staff, how you can reposition your staff. You don't have to fire people. It just means you can do more. Right. There are things that I do now that used to take hours or days that, like in, in two to 20 minutes, I'm, I'm good. And, and when it first started to happen, I would sit because I had planned my, you know, a block of time and I'm like, well, now what? Dang. I guess I'll just make a salad or.
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B
Yeah, that's a good problem to have, right?
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It is a good problem, but I had to adjust. I had to change management my own self of like, how do I restructure my time knowing that, you know, it's going to take less time to do certain tasks, which then leaves me available to do other things of things.
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B
Well, let's say someone is taking their head out of the sand or they did that survey you talked about and they found out there's interest and excitement or at least openness, and they're ready to embrace AI organization wide. What are the first steps they take and how do they get started? Either of you have a thought about that?
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D
Yeah, I'm happy to kick it off. I mean, I think, you know, Cheryl's point about a survey is really well founded, which is just taking the pulse of the Organization and are people more worried or hopeful, excited? Have they already been thinking about some use cases themselves? Again, just like we're talking about meeting the sector where it's at, each organization has to meet their team where they're at. So I think that's a critical first step. The other thing is actually creating, I've talked about this a few times, some kind of organizational level policy. And this is a work in progress. It's not going to be perfect, but it's literally two to three pages. Fast forward it and 10 both have some useful template generators that can help streamline this. So it doesn't have to be fancy, but it's ultimately a forum in written, explicit format to ask the question, what does success look like? And again, it's what data is sensitive and how do we protect that? What are the key use cases and applications that we want to streamline or enhance? And what are some of the most painful processes that we're spending the most time on? Whether it's five minutes every time someone donates and we send them a thank you letter or big slogs of four hours at a time to create my next annual budget or whatever it might be that we think there may be an opportunity for AI to enhance. And starting with that is really critical. The third and final thing I would say, Farah, is just the idea of bringing AI out of the shadows and creating a public forum of discussion and dialogue so that the organization is seen, seen as embracing this technology and facilitating its responsible adoption and encouraging people to kind of learn as a group and unlock a culture of innovation. And that can be as simple, frankly, as a weekly or even a monthly meeting where it's in all hands. You know, maybe it's on Monday, we bring out the bagels and coffee and people could talk about their weekends. But we also go around and say, has anybody been using AI for anything personally, organizationally or beyond? And what did you experience? What did you learn? What went well, what went poorly? What would you do differently next time? What tools are you using? And just by inviting that conversation to happen in a public forum now you're embracing the adoption of AI at an organizational level. And that creates sort of a pathway for your team to feel more comfortable and confident really playing around with this technology and not feeling like they have to get it perfect, but that it's okay to experiment.
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A
Nothing to add that he said it perfectly.
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B
Check, check. Darian. Okay, well, before we go, we have mentioned a little bit equitable and ethical use of AI, and I want to talk about that and I want to think about it for the entire nonprofit sector, what are some resources or ideas that you have for ways we can start thinking about that? I mean, I hear from you all a sort of, you can't ignore this. You've got to figure out how you want to accept it and use it. But what about still for those that are raising some, some really strong concerns about equity and ethics? I know you both care about those personally as well, and I know from your previous work too. So what do you think about that, particularly as it relates to the nonprofit sector? Are there any thoughts you have there, Cheryl? You want to start us off?
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A
Sure. I would say, you know, I know people that what I hear a lot about are environmental concerns, right? Like how is, how are these big data centers that are creating, you know, how is that impacting communities? And you know, we can see in Memphis with Elon Musk's bizarrely methane powered. Why would he choose that? As someone who is a clean energy guy, I don't, you know, he owns a solar panel company. I don't know, you know, that's pretty dirty, that, that's very dirty fuel. But clean energy, you know, number one is on a snowball of acceleration. California, which is the fourth largest economy in the world, is now 2, 2/3 clean energy. Europe as a whole is about 50% clean energy. Saudi Arabia, one of the world's largest oil producers and the poster child for oil says that they plan to be 100% clean energy in about five years. We'll see if they get there. But you know, you feel me, right, that clean energy is just technology and what do we know about technology? Over time it gets smarter, more powerful, less expensive. Right. So, you know, I think that pushing these companies towards clean energy is, is ultimately going to be a win, win for everyone because it's going to be cheaper for them. Right. And it's going to be cleaner for the rest of us. And I think that they're going to make that change anyway. But I think we can, we can push them along towards prioritizing that. The other thing I would say on the environmental front is look, look, the cheeseburger you ate last Tuesday was probably a lot harder on the environment than the last 10 prompts you put into ChatGPT. Okay. Just keeping it real. Like the scale that people are talking about, I think in terms of balancing things like meat eating or you know, industrial pollution, you know, these are areas that are equally if not more damaging. So it's, it's not wrong to be concerned But I think it's important to keep it in perspective in terms of, you know, we're on this. There are about four things that are radically going to change the way we live over the next five to 15 years, and that's AI, clean energy, bioengineering, and quantum computing. Okay. And the, the convergence of these forces is really going to, you know, make things very interesting very shortly.
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D
Yeah, I agree completely. And I think Sheryl's right that it is important to look at things in context. And absolutely, if you compare individual prompts to anything like leaky pipes or eating a hamburger, it's not even in the same ballpark. But I think we also need to be transparent about the fact that it's not just those individual prompts, it's all the training that goes into these models and all these data centers that are getting built. And again, it's important to keep it in context. An acre, where you have a state of the art AI facility, uses less water than the farm next door. Right. So from a water standpoint, it's relative. The thing that's freaking people out are two things. One is the growth rate, which is increasing significantly, especially compared to other needs on electricity and water. But the other is just poor urban planning, frankly. Like these water. These electricity companies know what's coming, and it's their fault that the well's running dry with the farmer next door. They need to be doing a better job. And so there's a big effort underway with cities and counties around the country to accommodate that. But the other thing I think we need to be honest about, because environmental concerns. And I've done a lot of work on climate, worked on the SDG for both climate and gender, was a commissioner. And so I'm deeply focused on that and actually planning to do some research to bring more transparency to this conversation. But the other thing is, that's just one example of concerns around ethics and bias that, again, are one of those very valid concerns that we can often talk around. And I think we need to be honest about the fact that this technology was largely created by a bunch of white guys drinking too much Mountain Dew hanging out in a laptop in Silicon Valley. And maybe it's Red Bull now, I don't know, whatever.
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A
Or ketamine. On ketamine. Okay, let's keep it real.
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D
But, you know, so the point is like, like. And not to mention, we live in a world that's biased. So based on the fact that this technology is just making connections and patterns from huge amounts of data, if you ask it What a beautiful woman looks like. You're probably not going to see a woman of color. If you ask it who the beneficiaries of some of these social service programs are, you're probably not going to see Caucasian folks. And that's deeply upsetting to many of us working in equity. But it's, it's one of the reasons why we need humans in the loop is to counterbalance this cold, technical, pattern recognition, only focus, and counterbalance that with the human connection, with the focus on equity, and with the values that really underpin not just our organization's work, but the work of the sector as a whole.
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A
Yeah, I would just jump on that and say I do feel like people let the far right take over the Internet in many ways. Rather than pumping in nutritious content, you know, they allowed a whole bunch of bots to speak louder, you know, and to define certain issues. And we should not let that happen with AI. We should make sure that, you know, if we're interacting with it, that we're helping to train it in certain ways because there is an opportunity. The flip side of this is that ultimately it's a computer. These are, these are robots. And, you know, what do machines do? They are logical. And at the end of the day, sexism, racism, ableism, homophobia. This is illogical. Okay? It doesn't make any sense. And, you know, ultimately what they're starting to find is that these bots ultimately start to resist. Because if a bot has been trained to look at certain resumes for certain attributes, and it's looking at someone who happens to be a Latina, Right. Versus, you know, someone who is not. And, you know, rather than choosing the mediocre, not Latina just because you like their, their surname better, you know, the, the bot, over time, is going to pick the person who actually has the better qualifications. So while we have a lot of work to do, goodness knows, I think that there are, you know, some opportunities ahead. And I do encourage people to think about building your own LLMs, building your own spaces that are, you know, built from your branding, your message, your mission. Right. Your photos, your videos, you know, such that you can produce generative content that really feels authentic to you and your mission. Great.
- [30:24]
B
Well, lots, lots of things for folks to chew on. If you'd like to connect more with Cheryl Conti and Darian Rodriguez Heyman, be sure to follow them both on LinkedIn. We'll link to their profiles@bigduck.com insights where the transcript for this conversation will live. You can also learn more about their consultancies@brightworksai.com and helping people help.com I also of course encourage you to view the resources@aifornp.org and read their book. Well, Darian and Cheryl, any other thoughts or words of wisdom you'd like to share before we part ways?
- [30:58]
A
No, I just, you know, I hope that people, even though, you know this is going to be a time of rapid and rocky social and technical innovation. You know, I would like to believe that much like the end of the last Gilded Age, that the flip side is going to be a world in which there is more freedom for more people, more prosperity for more people and just better lives, healthier lives for more people.
- [31:26]
D
And I think from my side, even though long term I am very bullish on the prospects for humanity, I feel like we've got some really serious and alarming headwinds in the current and short term. And the best way I've heard it said is that we, we have moved as a sector from an era of planning to an era of navigation and the age of the three or the five year strategic plan. And I've done many of those big plans. For large organizations. The need for the short term action plan has never been more critical. And even more importantly, the need to build more resilient and responsive organizations that can tack on a dime and, and adjust strategies based on things that happen unexpectedly from the federal government or the world in general has never been greater. And so I understand. I work with small grassroots led organizations all day long. I get why they feel overwhelmed and scared and unable to really put thought into some other thing. But this is your compass. This is an opportunity for you to have a tool that will make you more plugged in, responsive and enable you to sh. Shift gears in the midst of this storm. And it can be directly helpful with raising money, with reaching new members of your community because the demand on our services has never been greater. And so this is a tremendous tool that I really invite organizations to look at at an organizational and a strategic level instead of just leaving it to the two or three people on most teams who are already playing around with the tool on a personal basis.
- [33:06]
A
And what I would add is in our book AI for Nonprofits, there's an awesome chapter towards the beginning from Insights from Charlene Lee that's called the 90 day blueprint. And this is a great time at the beginning of next of, of 2026 to really take that short term sprint to then plan out the next 18 months. So you know, that's a, that's a practical thing that you can do.
- [33:30]
B
Great. Well, thank you for giving us so many big ideas and practical things we can do, and hope everyone has a great year ahead.
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C
Are you a fan of this podcast or Big Duck's other resources on nonprofit communications? If you are, we'd love to hear from you. Please drop us a line by writing to helloigduck.com to tell us what you're working on and what topics you need help with. We also welcome getting your feedback via. You can review this podcast wherever you listen. We'd love to hear from you.
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B
This is the Smart Communications Podcast, Developing the Voices of Determined Nonprofits, brought to you by Big Duck.
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C
Big Duck is an agency that puts smart communications in the hands of nonprofits. We help our nonprofit clients develop strong brands, strong campaigns, and strong teams that advance their missions and achieve their goals.
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B
Connect with us@bigduck.com.