Isaac hosted a special episode of “Coffee with Digital Trailblazers” focused on AI in nonprofits ahead of Giving Tuesday.

Participants

Hosted by Isaac Sacolick, CEO of StarCIO

Special Guests – Non-profit executives

• Larry Lieberman, CEO of Mouse.org
• Stephen Rockwell, Chief Innovation Officer of Amplifi
• Teresa Duran, Technology Advisory Council of Big Brothers Big Sisters of America
• Glen Ford, Former Director of International Development and Trustee at Aegis Trust
• Derrick Butts, Board President and co-founder, Prostate Health Matters

Digital Trailblazers

• Joanne Friedman
• Liz Martinez
• Joseph Puglisi
• Martin Davis
• John Patrick Luethe

Summary

Featuring a panel of nonprofit leaders discussing their experiences with AI tools to drive impact and reach donors. The episode explored various nonprofit use cases, including education, public benefits access, and health initiatives, with panelists sharing their experiences and challenges in implementing AI solutions. The discussion emphasized the importance of AI adoption in nonprofits, highlighting the need for strategic planning, collaboration with tech companies, and focusing on social impact rather than just efficiency.

Transcript

[00:00:05] Speaker B: Welcome to this week’s coffee with Digital Trailblazers, our 150th episode.

I’m really excited to announce that I’m really excited to have a full house today, our largest speaker panel on this program and we’re talking about something really important to me. I am not an expert around nonprofits, but I have worked in nonprofits and we are heading into the holiday season.

Giving Tuesday is coming up right after the Thanksgiving holiday.

And in planning November’s episodes, I wanted to have just a special episode just talking about not only AI for social good, but just giving some of our nonprofit leaders the mic to talk about all the special things they’re doing to drive impact with their constituents, how they’re using AI, how they’re using technology to drive their cause, how they’re using AI and technology maybe to become more efficient, to reach a wider donor base and obviously to impact their social causes as well.

I have five special guests today and I’m going to allow every one of them to introduce themselves so I don’t overstate or understate all their contributions to this space.

In a couple instances, I have worked directly with the folks that I’m going to introduce. In a couple instances, there are people that I’ve just met and this should be a really interesting conversation. I want to thank everybody who’s joining on the comment stream. Just say hello. Thank you Martin, for the 150th episodes. Thank you Vaibhav from joining from India. Hello Nicholas.

Thank you for joining this week.

I will encourage you if you are involved in a nonprofit, do share a little bit about that, your involvement, what the nonprofit is.

Please do share a URL where people can donate.

I think that’s just that time of season when we should be doing that, encouraging people to participate in nonprofit causes that they are passionate about.

This episode will be available on my Coffee with Digital Trailblazers podcast both on Apple and Spotify. You can go to startcio.com/coffee to get access to those. And with that, let’s just get started with our 150th episode talking about AI for social good. Insights from nonprofit leaders. First, one person I want to bring up is Larry Lieberman. Larry and I have gone have worked together a long time ago.

Larry is now the CEO of Mouse.org but has a long history working with nonprofits.

And Larry, let’s talk about some of the nonprofits that you’re passionate about and especially mouse.org let’s talk about how you impact. Let’s talk about how you’re using AI today and maybe just share some of the challenges and opportunities my speaker board maybe even be able to help you out with during this program. Larry, welcome to the floor.

[00:03:29] Speaker C: Thank you so much, Isaac. It’s great to be here. And you’re absolutely right, you know, MOUSE is at the intersection of seemingly every aspect of AI.

Mouse provides technology, computer science, and AI education primarily in New York City public schools.

I think the enormity of the challenges that we all face can be summed up by the scale. New York City has over a million students in our public schools. That means that roughly one in every 300Americans is currently enrolled as a student in New York City public schools. And what we do at MOUSE is provide career oriented technology education.

We help expose students to technology and AI in a way that gives them the agency to feel like they’re creators.

And the scale is enormous. We started teaching AI in the schools in 2023.

Since then, more than 12,000 students at 95 different schools have completed our AI league course.

And what we found in three years, more than anything, is the speed with which change is impacting all of us in education, all of us in nonprofits. And it’s really just like what every business around the world is experiencing with regard to adjusting to AI, while AI is itself growing and adjusting to the world.

[00:05:02] Speaker B: Larry, just a question. You talk about speed and impact in the education space, can you talk about the impact with the actual educators?

This is a brand new world for them.

And just some of the steps you’re working with the teachers about how they are embracing AI and maybe even quelling some of their fears.

[00:05:25] Speaker C: Yes, absolutely.

My feeling about teachers in AI is that I am extraordinarily optimistic. When we first brought AI education into the classroom in 2023, we were greeted by a lot of skeptics.

At that point, the only thing most teachers knew about AI was that their students were either currently using it to cheat or they were going to use it to cheat.

And when that’s the mindset of an educator, it’s extraordinarily difficult to penetrate and show them the essential nature of AI education for all our students.

I’m really, really pleased to report that, first of all, as we expose teachers to AI and AI apps and the tools, they come on board almost immediately. And of course, the world has come on board, and it’s a very different environment right now that while we might have been surrounded by people who thought AI was going to go away and it was a whim, we are now at A much different time as 2025 comes to a close and educators understand that the efficiencies and excitement that’s coming to the private sector and other areas also can come to education.

[00:06:46] Speaker B: Wow, that’s great to hear.

There’s a little bit of fear that, you know, the younger generation are going to struggle to get those entry level jobs, that they’re not going to be prepared, that companies aren’t going to be hiring them as much and you know, you’re working with, you know, a very large student base to get them prepared for this new era of transformation, this new era of where AI is a companion. And I want to thank you for being a friend, a mentor and for joining our program today.

How can folks contribute to Mouse.org? is it right on the website?

[00:07:28] Speaker C: Yeah, there’s a donate button right@mouse.org we appreciate not only your financial support, but your guidance and introductions. If there are folks in your world for whom AI education, especially at the middle school or high school level, is important, we’re happy to reach out and help them. But donations@mouse.org would, would be greatly appreciated.

[00:07:52] Speaker B: Thank you, Larry. Let’s bring up our second special guest, Stephen Rockwell. I’ve also known Stephen for a very long time. Stephen, share us a little bit about the causes that you’re involved with, how you’re using AI today and what do you see some, as some of the challenges?

[00:08:08] Speaker A: Sure.

[00:08:09] Speaker D: Thanks Isaac. Thanks for having me. It’s great to be back connected. I’m usually on the other side listening to you folks, so it’s, it’s nice to share some time with everyone. Today I’m doing a, I’m doing a number of different things around AI for social good. I, I think one thing I’d like to highlight, at least initially, is the work I’m doing with Amplify.

We co design tech tools to simplify, you know, complex processes of connecting people in need to resources and public benefits.

And we’ve got two fairly innovative, I think industry leading AI use cases or builds that we’re doing right now.

We have a benefit screener that caseworkers use and we’re integrating a caseworker chatbot that allows the caseworker to focus on the person who’s presenting the person who they’re with and be able to ask information, referral questions and complex public benefit questions to the chatbot and get, you know, reliable trusted information.

And then the other thing that we’re, and that was funded by gates foundation and google.org, the other new project we’re working on, funded by google.org is with our partners. NAVA is an agent that takes data from case management systems and directly applies folks for public benefits.

So it, you know, the goal here is to remove any and all administrative burden to getting people the benefits they need and that they’re entitled to.

And so that’s a big part of the AI for good work that’s happening with Amplify.

And it’s really, I think, the first use of agents in a social impact context where we’ve actually got something going.

We’re piloting starting this week with caseworkers outside of Los Angeles in Riverside county.

And it’s really, I think it has the potential to be the sort of holy grail in public benefits access.

So we’re really, really pretty excited about that.

[00:10:39] Speaker B: Stephen, you and I had a great conversation earlier this week and you were telling me about all the work you’re doing around AI agents.

I’m putting you in my list of experts who it’s really hands on with what it takes to build AI agents. Can you talk maybe a little bit deeper for those interested in agents and those interested in nonprofit? What does it take to put together an agent for an AI for social good type of application? How do you think about data? How do you think about privacy?

Maybe give us a sense of what’s happening underneath the hood a little bit?

[00:11:17] Speaker D: Yeah, sure.

This probably two, maybe three modalities.

The one we’re using is really if you’ve been in something like ChatGPT and you see it in its agent mode where it opens up a VM and then it’s doing work within the screen. Within the screen.

That’s a little bit of the modality that we’re using. Early on we want to give humans sort of ultimate control of the process, especially early on to be able to catch things. And humans really want to need to sort of hit that submit button on a benefit application.

But essentially what we do is we have a chatbot window on one side and we have a screen on the other and the agent is pulling data from the case management system where it’s connected via API or MCP server, and putting data onto the page and explaining to the caseworker, I’m doing this now, I’m doing this now, I’m doing this now. So the caseworker can intervene at any point if they see something that’s off, they can review the work and then they take the screen back over to click submit.

Agents, like all this technology is a year old, right? Or less. And so, and accuracy is really important.

And so having that human oversight and building trust is what we’re doing early on.

We can foresee eventually using some other modalities where some of that is happening on the back end, where you just set up the workflow and let it run.

And I think we’ll get there.

But with this audience, it’s really important that we validate and build trust with the technology. And so that’s why there’s a big sort of visual display component to what we’re doing with agents right now.

[00:13:14] Speaker B: Super.

Thank you for joining, Stephen, and for sharing what you’re doing with Amplify. What is the website for Amplify? Just for.

[00:13:22] Speaker D: So I make sure I’ll put it in the chat. It’s amplify with an I.org so put in chat so people don’t, don’t lose it.

[00:13:33] Speaker B: Excellent. Thank you, Stephen. We’ll come right back to you. Let’s go to Glenn Ford. Glenn, I only met a few weeks ago.

We were at just an amazing event of an amazing people, an event called Spark Executive Forum.

And Joe was there. Joe and I are normals at that event.

Glenn was sitting at a table alone. I came up to him and just was floored about some of the work he was doing.

Previously on the.

Is it the. It’s the Rwanda Foundation, Glenn, do I have that labeled right?

[00:14:12] Speaker E: Yes, it was the, it’s the Kigali Genocide Memorial.

[00:14:16] Speaker B: Yes, I want to hear about that. I want to hear what you’re working on with Champions.

Thank you, Glenn, for joining us.

[00:14:23] Speaker E: Thank you so much, Isaac. And it was, it was really a great event in New York, the Spark Forum. And so in terms of my work with non profits, it really started about 22 years ago. Prior to that, I was a senior leader in the UK road building industry.

But anyway, I had occasion to volunteer in rwanda in early 2004, so 21 years ago to help build the Kigali Genocide Memorial.

For those not familiar, there was a genocide in Rwanda in 1994 where a million people, innocent people, were very sadly murdered in three months. And this was neighbors killing neighbors and in many cases, some cases family members even.

And just to say, in the time that I was there, I learned more about myself and more about humanity than I had done in the prior years I’d been on this planet.

I then subsequently left my management career and basically worked alongside that nonprofit in a volunteer and semi volunteer capacity for the next 21 years. And I was really privileged to see obviously, you know, going to Rwanda. In that context, you see what is the worst of humanity is capable of. And I think, you know, one of the real lessons from that is we’re all capable of some really bad things, but also we’re all capable of some really good things. And I was privileged to see how the an educational program about values of humanity emerged from that memorial, from those ashes, and then was privileged to see that being taken into places like South Sudan, Kenya, Central Africa Republic, Zambia, Zimbabwe, and even in a pilot program to the United States in parts of Chicago and elsewhere.

And I just really saw the transformative power of human stories. And I think that was the key here, that stories of humanity have the ability to inspire, activate and strengthen the humanity within all of us. And that was my experience. And indeed I, you know, Isaac, it was great meeting and sharing. I just regard myself as a beneficiary of having been involved for such a long time on what I’m doing now and how that relates to AI is I then about six months ago set up a company called Champions. It’s not actually a non profit, but it works. It’s designed to work in partnership with non profits to really take my experience and learning about how humanity, if you like values of humanity, what it means to be a human being can really transform ordinary life, you know, life in the workplace, students, nonprofits, and in terms of specifically then AI and how that I we’ve been using AI so firstly in the really in those human stories and being able to both document those human stories, but also then communicate them in ways that people can relate to, whether it be language or terminology.

And we’re just seeing that power of AI to take kind of information, various forms of information, and to really storyboard that in a way that different people can relate to those stories.

But even more so, of course we’re seeing the power of AI to be able to prompt questions to people and to help them tell their stories.

So anyway, so that’s the main ways in terms of using AI today and in terms of being able to scale up that really that, that kind of movement.

So Isaac, that’s my short summary.

I don’t know if you or other people have got questions related to that.

[00:18:36] Speaker B: Well, we’re going to get around the questions in our second half. I want. Thank you for sharing that story.

Maybe just go a little bit deeper on some of the challenges. You say you talked about stories of humanity inspiring it in all of us, this new world of AI sort of on one hand inspiring us, but also frightening us about what our purpose Is how do you work that paradox in the programs that you do at Championship?

[00:19:09] Speaker E: Yes, well, thank you for asking that. And I’ll just give you two illustrations where we’ve started to use this, the Champions program.

So first of all, I’ve been using it, as you can tell from my accent, I’m from the uk, but I’ve been using it with a non profit health organization in Chicago.

This is sort of like a large outpatient clinic. They have about 40,000 members, about 250 staff in Chicago. And we’re using this program in terms of leadership training, but also in terms of cultural transformation and really to help, to support their, that they’ve been going some 70 years really to support their vision of being entirely patient focused and really bringing the humanity, bringing the shine back into just their kind of everyday life just for that humanity in terms of whether it be customer care or in terms of how they deal with their co workers or indeed how they deal with themselves. You know, the ability to forgive, not just your co workers, but also, you know, ability to forgive yourself. You know, we all make mistakes, it doesn’t excuse them, but the ability to have resilience in that way.

And so we’re applying this program with this health organization, health nonprofit in Chicago. And we’re seeing transformative effects. We’ve just been there for 16 weeks.

We’re seeing personal transformational effects. We’re seeing culture change. I’m also seeing people saying to this that this is helping them with their relationship with their kids, with their spouses and with their families in terms of relating to each other.

And as I say how we’re using AI, there is really being able to tell those stories of humanity in a, in a cost effective manner.

And we can all see the danger of AI being in effect dehumanizing the workforce or dehumanizing the customer experience.

And then the other application, I’ve started to use it, we’ve just done this as a pilot and this is a nonprofit activity is we’ve started to partner with a student founded nonprofit to actually bring this to college kids in America, to really enable young leaders to have the ability to agree to disagree and if you like, developing those really strong human skills. And obviously in the world of AI, you know, the focus is then much more upon developing those human skills, how to relate to people, how to relate to others, how to relate to yourself, how to have that fire in your belly, how to have that resilience.

So those are the things that we’re, that we’re seeing and I have to say it’s just great to see the impact from the participants of the program.

[00:22:06] Speaker B: Glenn, fascinating story in a lot of different areas.

The organization that’s working that supports the foundation for Wanda, what is the URL for that that I can capture?

[00:22:22] Speaker E: Yeah, so the so so champions is is championsmovement.com that’s my organization. And if you want to connect with the Kigali Genocide Memorial, that is KGM rw, but you could just put into Google Kigali Genocide Memorial and you’ll find their website.

[00:22:42] Speaker B: Thank you for joining us. We’ll have some questions for you in just a bit. I want to bring up our next special guest is Teresa Duran.

Teresa Duran and I just met and she has a background as being a cio, CTO and a board member.

Teresa, tell us about the charities and nonprofits that you’re most involved with.

[00:23:06] Speaker F: Sounds good. Hi everyone. Such a pleasure to meet you all.

So just a real quick intro of my background. So I was a repeat chief information officer across many industries.

Two out of three had a nonprofit area. So one was Carneagen Sight Life.

So basically giving the gift of sight to people who needed to get surgeries or different products and services.

And then I was also the CIO of Make a Wish America and earlier in my career path.

So I’m pretty well versed in the healthcare space and seeing some of the AI outcomes of what happens with improving and accelerating preclinical data and trials with AI.

Today I’m actually heavily involved as a technology council member with Big Brothers Big Sisters of America. It’s an incredible nonprofit that’s been around for about 120 years. It’s really improving outcome outcomes for many children that are, you know, growing up in poverty.

They’re help and setting up that mentor mentee relationship so, you know, these young children can grow and thrive and have a positive role model with them and in addition have improved outcomes from an education perspective. So it’s a really, really ambitious mission that I’m so excited to be a part of.

I’m also a board member for Change.org and if you’re not familiar with them, they actually help bridge for profit companies that want to have different types of donation types, whether it’s cryptocurrency or roundups that you see. But it’s basically an ability to have easy ways to get donations from everywhere and they seamlessly handle the payments on the back end to help nonprofits and ease friction. There’s but today I’m also a CIO and VP of Unified Consulting. So we’re a management AI management consulting firm.

So we do provide a lot of different types of services, if you will, to help clients in various capacities. Many are for profit, but we do help nonprofits as well. And I do think that you’re going to see a lot of incredible usage of AI with Big Brothers and Big Sisters. They use agents for the matching process to improve that operational efficiency, to try to get matches as quick, as quickly as they can to help some of these children’s in needs.

But then I also, from a consulting perspective, help a lot of different types of firms as they’re working through the challenges and having a background in technology and leading departments. A lot of us know it’s not the technology itself, itself that’s going to help improve these outcomes is how are you going to move organizations through understanding what that ROI looks like? I think that’s the biggest challenge today is the majority of these initiatives are failing even for for profit companies.

So when you’re looking at philanthropy or different types of organizations, a lot of times their funding models don’t allow for a lot of spend with innovation and modernization.

That coupled with, you know, you have many that maybe not be they’re not as digitally savvy.

So how do you help move them through that change curve? How do you help them see the benefits and the art of the possible, if you will, of what AI can do?

I also think, you know, I was the top risk officer at several companies when I was cio and there’s a tremendous amount of risk when you start looking into some of these AI solutions as well. So really passionate about AI from an innovation perspective, but also making sure to look at the lens of the type of data that you’re collecting. Could you be also at risk from a bias perspective and how you’re training your language models?

It’s one of those things that I think that needs to be done pretty carefully as you’re looking at rolling out a lot of these different solutions.

[00:27:33] Speaker B: We have talked about AI bias here quite a bit, even dedicated a special episode to that.

I do want to revisit this question after the break and I get everybody speaking this challenge of helping nonprofits be able to invest in innovation, knowing that their ratings and they’re scrutinized for what their levels of investments are and how they’re portrayed. I’ve got a couple of experts around this here on the panel that might be able to answer that question for everybody. But I want to ask you a question that I want to bring Derek up, have him Talk about his nonprofit.

Theresa, in your exposure to AI across all the organizations that you’re working with, it’s quite, quite a list.

And now your work at. In your consulting firm, can you just share one or two AI use cases that just show the promise of AI in the nonprofit space?

[00:28:36] Speaker F: Absolutely. So I first should say I am pretty bullish when it comes to using agents. So I do run a salesforce practice, but I do see a lot of nonprofits doing a really great job. So starting to use salesforce agents through agentforce and the ability to when you think you can find different types of workflows. So case in point, Big Brothers Big Sisters uses this with their matching process.

You can help automate, say a child lives in San Diego and wants to find a mentor that lives within that specific region.

And you want to find that that person, the mentor has maybe shared hobbies, maybe shared, you know, outlooks on, you know, they both are going the. The child wants to go in the same direction. From a career perspective, with a mentor, you can add a lot of different various attributes. Right. And if a person, a manual process would be a person would try to match and do a lot of the interviews. But imagine how Agent Forces is working today where it can help identify and help prioritize different potential mentors more quickly. There’s kids waiting. So I think the ability for that to reduce the administration overhead and then the human touch always has to be in place. They can handle a lot of the matching process towards the end versus a lot of the initial, what I call sausage making, where a lot of the data is just maybe everywhere and you’re having to collect it.

The ability to get kids through their workflow and their life cycle faster the better.

So I think that’s the number one. I think others you’re seeing a lot of operational efficiency at different nonprofits where they’re using AI to help at Make a Wish. There was a pilot I was working on where it could actually help predict donors and donor segments.

So, you know, if you can imagine, I think with philanthropy, a lot of donor sentiment can change over time. The type of donors, whether it’s corporate or individual. But the ability to predict donors from different segments helps from a marketing perspective as well. So I think it’s one of those things when I look at AI, it’s not just the technology itself and maybe the operational efficiency, but how can you also help grow your revenue to help fuel your mission as well as Teresa.

[00:31:10] Speaker B: Thank you for that. I. I think both are very interesting. Use cases with applicability not just in nonprofits and corporate, to this, you know, matching process and speeding it up and then, you know, taking a page out of corporate America where we spend a lot of time optimizing how we market and how we reach audiences and really applying that within the ability to improve development for nonprofits. I thank you for sharing that.

Let’s bring up Derek. Derek is a one of our normal speakers here. I got to meet Derek for the first time this week, a couple of times.

Derek, thanks for joining my event. Yesterday at the AI Salon, I spoke about AI leadership and in the course of the day I heard about what you’re doing in nonprofits, your passion, why you’re involved with it. So share, share a little bit with the group about the non profit that you’re involved in and how you’re using AI in non profits.

[00:32:12] Speaker A: Thank you, Isaac, really appreciate it. I was interested to see you twice in the same day, so that was great.

The nonprofit I work with is called Prostate Health Matters. It started about five years ago and their main focus was really help men understand and navigate their prostate health before the cancer diagnosis. Prostate cancer is a number two silent killer of men in the United States.

And one of the things the nonprofit was geared was trying to help those underserved communities pair up with those prostate cancer treatment entities in their particular state or city.

The organization started in dc, expanded to Maryland, Virginia, and then over the years expanded to New York, New Jersey, Atlanta, and also Connecticut. It’s been growing quite a bit. But the biggest thing in using artificial intelligence is trying to figure out those cities that have the highest prostate cancer incident rate over a period of time. So it helps to correlate the data. So when we go out to do presentations to the different cities, whether it’s social organizations or churches or community centers, is really identify what’s the biggest challenge within that particular city.

And by doing that, it’s bringing information that the residents may not have had and understanding how their city is being impacted by this disease.

Because men are not getting their prostate checked normally with a PSA test or they’re not going to doctors regularly. Most men, they have the machismo attitude, it will go away. Not realizing that cancer like this is usually asymptomatic, which means they’re not going to experience anything till later. So what the AI helps us do is correlate that data, bring the information to them so they can understand. These are the impacts and the challenges that exist within your community. And these are the reasons why you need to be more proactive with Your prostate health in doing that is helping them better understand. Now, one, to go to the doctor to get a simple blood test, which usually takes three minutes, but also really think about asking questions about their family history. The correlation between prostate cancer between all the different ethnicities, it varies between the different SKUs based on the African American community having a two and a half times more likely susceptibility being diagnosed with prostate cancer, and then also the fact of treatment. So there’s also a lot of health deserts that exist around the country and trying to help correlate where those health deserts are and bring that information to those communities. They really can need it the most.

One of the other things we’re using the AI for is writing grants.

We realized by taking information for some of the grantors that are actually providing these grants, correlating the data based on information and experiences that we’ve done over the years, it actually has helped us write better grants to the point we want our first $10,000 grant a couple months ago to really look at how we can increase cancer awareness in the city of Newark, New Jersey. The state of New Jersey has the highest incident rate of prostate cancer cases in the US and just kind of pinpointed, we asked what are the correlations. So not only looking at the city of New Jersey, but AI helped us pinpoint what are the neighborhoods within the city of New Jersey that have the highest concentration. So help to correlate that data that exists across the Internet to really figure out what, what are the target markets we can go to and then bring it in those Virginia. Not Virginia, but those New Jersey type facilities like the Hackensack Meridian Health or JBR Barnabas or the Rutgers and help them really now move to those communities because they’re also trying to figure out how they can connect to get more information out to the communities. And our organization helps to bridge that gap.

[00:35:43] Speaker B: Wow. So I captured two data, very generalized use cases here in our, on our whiteboard, Derek. One of them is just using data to determine and optimize where you’re driving impact, where the people who need the most need. I mean, I think that’s a very generic nonprofit use case. And then writing grants and winning grants, you know, winning funding, how important is that? I think that’s just a good area to share for everybody who’s listening. We have a great audience here this week at the coffee with digital trailblazers. I want to thank Everybody joining our 150th episode on this very special topic, AI for Social Good.

Giving Tuesday is coming Up. It is the Tuesday after every Thanksgiving and many corporations provide benefits to charities for making your donations in and around this period of time.

We’re talking about a whole dozen, two dozen of them. Some of them I captured here in the whiteboard. Some of them are in the comments stream. And if you are involved in a nonprofit, I encourage you to share about the nonprofit who they try to impact your involvement in it in the comments train. Just share it with everybody. This is just a very special episode for the coffee with digital trailblazers to really give the mic to some great people and really trying to drive impact through their nonprofits. I want to thank Larry and Steven, Teresa, Glenn and now Derek for sharing their stories.

Heather, I want to bring you to the floor. You’ve been sending me like all this really great research. Heather is an executive recruiter, but she’s also a researcher. And I said rather than me sharing all that detail, I said, heather, take the mic. And what can you share from the research that you found around AI and nonprofits?

[00:37:44] Speaker G: Thanks Isaac. And really great information.

One of the things that I value is data for good.

So with that context, I found two great sources. The 2025 State of AI and nonprofits reported by TechSoup and Tap Network. And I can put those links in the live stream. The and what was interesting is that there is a tremendous number of non profits, over 85% in two different studies saying that they are exploring AI tools. But it has shown dramatically over the, over the years adoption by nonprofits is lags. So that by the time that really will happen, not only approaching it, but getting it into their business may take quite some time because they say also while interest is high, only 24% of organizations have actually developed a formal AI strategy.

So the opportunity is there.

And the risks I think were actually highlighted by Teresa. You know, the notion of bias and province, where the provenance, where the data comes from is really, you want to make sure that the, the value of it is not overshadowed by what the impact negatively could be. And anytime you are dealing with a social organization or charity, you want to make sure that whatever you’re doing, the focus should be on the social impact.

I will put those two tools in the two different sources. But what I found interesting is that some organizations that were quoted was Amnesty International monitoring human rights abuses and identifying areas of conflict, being able to have a faster response. You can, you know, some of the obvious ones, repetitive sourcing and analyzing large data, which may seem very obvious, but Teresa had mentioned how great that is with the with some of the Boys and Girls Clubs. So I’ll put those sources. It’s very interesting and I think the opportunity is there to bridge that gap to make sure that a formal strategy that right now is only 24% of organizations really has the opportunity to grow.

[00:40:07] Speaker B: Thank you for sharing those insights and for posting the research with everybody. I think, you know, data is always an analysis, is always good for helping us figure out where and how to go about making investments and also spending our time and where nonprofits can exceed.

We do have a couple of our normal speakers here joining today.

Joe, anything to share with the group? I do have a question for Larry and Steven lined up, but any questions, thoughts that you want to share with the group?

[00:40:40] Speaker H: Well, sadly the nonprofits that I’m involved with are totally directed toward social good and don’t leverage AI a whole lot. But I will put in a shameless plug for sim. I’ve been a board member of a local chapter of SIM for over 25 years and this is a nonprofit dedicated to furthering professional careers of information technology executives. And we certainly do our share of talking about AI and where AI could play a significant role. The other one I should mention is that I’m on the board of mtech, which is an organization devoted to advancing the use of technology in manufacturing, small businesses regional in the Hudson Valley.

They’re again not quite up to using AI yet. They’re just kind of getting their toes into the whole technology revolution a little behind the curve. But you know, these are non profits in which I’ve been involved for some time.

[00:41:41] Speaker B: Thank you Joe. And let’s bring John up. John, long history of helping people in general.

Any thoughts for the group or any non profits that you’re involved with?

[00:41:53] Speaker I: Oh, I’ve really fond of volunteering. I was in the Peace Corps. I used to teach physics on this little island in the Philippines. And just hearing this stuff, it’s so great because we were so resource constrained when I was a Peace Corps volunteer trying to teach physics and I’m so excited for some of the individualized learning that’s going to be through AI. I’m a huge fan of the book Diamond Age by Neil Stevenson and they had this primer book and it’s coming to life with what I’m hearing.

And then I was on the search and rescue team and I used to spend 10 years carrying people out of the mountains and I had to travel a whole bunch and so I stopped and so I’m looking to get back into but I actually want to be Less management, more just. Just helping out with things. And so I’m just so happy to hear about the neat stuff that’s going on here. And so my question is for the people doing education.

I’d love to hear what you’re most excited about on the individualized learning.

[00:42:53] Speaker B: Interesting. I’m going to throw that question to Larry first.

And then Larry also, I want you to comment on this question of how nonprofits can make investments in AI when their administrative costs are factored into their charity Navigator ratings, and how people view whether or not the money they’re donating is going toward dollars that are driving direct impact.

So maybe you could take a crack at both of those questions for us, Larry.

[00:43:28] Speaker C: Sure. Two really great questions.

Individualized learning is an extraordinary opportunity for.

[00:43:35] Speaker B: Education.

[00:43:37] Speaker C: And I think we’re seeing an openness to it again that goes beyond what I had expected.

I am really optimistic, and I think a lot of it, a lot of my optimism is derived from the enthusiasm that teachers are showing now that they understand that AI will not replace them. And I think that’s a really big point in education, that in many fields, jobs are being eliminated because of AI. And we read a lot about employment threats and we hear all of Amazon’s announcements and all the rest.

Teachers who now use AI are understanding that it doesn’t replace them, that it is a tool to make them more effective, have greater impact on their students, including individualized education.

And most educators are really optimistic that AI will support greater learning and more opportunities for development of young people.

So there’s real optimism there. I also think this is a great audience to talk to.

The idea that most of us can look back on the tech education that we received in school and realized that we don’t use a whole lot of it very often at work, that much of what we learned in high school and college in CS classes and tech classes is obsolete.

[00:45:07] Speaker A: Right.

[00:45:08] Speaker C: But what we all learned and what we really do use every day is the agency and empowerment that we felt by using technology to be creators.

And our goal right now with AI at MOUSE and other organizations all around the world is to teach that level of agency to groups that are underrepresented right now in tech employment.

And I think that’s part of the optimism.

Does that make sense and support hopefully the idea of individualized?

[00:45:49] Speaker B: I think it makes sense. I mean, I think every time you clear away something that is work that you have to do behind the scenes and then you get people, you know, really excited about what comes next.

What comes often what comes next Is people doing a better job interfacing directly with the people they’re trying to help.

Right. And, you know, so that’s what you’re describing for, you know, involving with teachers is, you know, partially efficiency, partially just getting smarter and getting them over the hump and realizing that they still have a very important role to play, and then looking at the individual and saying, you know, what is their learning style? What interests them? What types of problems can we show this person that will get them excited about learning more? How do we evolve our learning more aggressively and faster, given that the world is changing? I think it’s super helpful, Larry. And then maybe Stephen, also comment on this.

How should nonprofits think about investing in innovation so that they can show the value and get the grants they need to be able to pull that off?

[00:47:05] Speaker A: Sure.

[00:47:06] Speaker C: I mean, I’ll tell you what we do@mouse.org because we’re really fortunate.

I would say most organizations should be reaching out for either larger philanthropic support or government support to help facilitate and expedite AI innovation within their organizations.

We’ve got all our staff trained on using AI. We have great AI partners, all of whom have been providing their services to accelerate efficiency at MOUSE and operational growth at MOUSE at no cost to our organization.

[00:47:50] Speaker B: I mean, are you working with any big tech companies around that?

Larry.

[00:47:57] Speaker C: Most of the support comes from either the larger philanthropic groups or from state government.

And now even in New York City, city government has now been providing grants. And what’s really been very organized, at least in New York, is that organizations who are providing the support are connecting to us through our trade organizations. Like, we have a tech NYC group in New York City, which is the Economic Development Corporation, both of whom have done a great job of vetting suppliers to help really accelerate this growth.

[00:48:41] Speaker B: Thank you, Larry. I’m going to bring Stephen up and then Derek after that. Stephen, anything to add about how nonprofits can get the funding, the partnerships involved, to be ahead of the curve when it comes to AI?

[00:48:56] Speaker D: Yeah. And also I heard you make reference to the Charity Navigator efficiency piece, which I’ll also address first to say that part of my job at Charity Navigator was to redo the rating system. So it actually focuses on things like efficiency in a very, very small way now. And it really is about impact and the likelihood of you making impact into the future.

And that was a pretty big shift there, so don’t worry about that.

But. And AI really can help efficiency quite a bit. Many of the use cases that we’re looking at are those efficiency, automation, use Cases where there’s some real value in that. And then on the other side it’s programmatic use cases.

[00:49:43] Speaker A: Right.

[00:49:44] Speaker D: So you are expanding your impact with the use of AI. So just to say that. And then on the financing side, the good news is, is there’s a lot of.

There’s a number of AI accelerators that GitLab has, GitLab Foundation, Google.org and and a handful of others that are, that are actually trying to get those sort of investments going. I also consult with another google.org project that’s actually targeting smaller organizations in five communities around the country.

And so there’s lots of.

I would say now is maybe not a great time for, for fundraising in general if you’re a non profit but if you’re doing AI, there’s a lot of opportunity out there.

There are networks of philanthropies that are really paying attention to this. There’s a lot of energy and funding around it. And so jumping in and getting started if you haven’t is really important.

[00:50:52] Speaker B: Thank you. Stephen. Let’s bring Derek up. You’re raising your hand. I know you are working with an accelerator and your nonprofit. Can you talk a little bit about that experience?

[00:51:02] Speaker A: Yeah. So it’s just, just go back to the, you know, how do you get funding and whatnot.

One of the things we did also reach out to AI to say who are some of the philanthropic arms that are out there that would be willing to invest in our non profit based on our community impact? And that’s something that came back with a list of different things. So that’s one thing to do, but the accelerator part of it is really looking at the passion. You know, when you’re looking at things that you’re doing and you’re passionate about. With me being a nine year old prostate cancer resilient survivor working with prostate cancer health and empathies that also has an impact for those people looking to make donations and stuff because now it’s more personal, it resonates. And the fact that you bring in an artificial intelligence to help they want, if they, if they like the cause, they’re going to help you and give funding to help accelerate that using artificial intelligence because they see the greater good. And I think that’s the biggest challenge is how do you connect with those philanthropic arms or those donors that really looking at those causes, that’s where artificial intelligence can help and that’s what we found to actually make an impact or a difference where to get funding. Because as most non profits out there, as a lot of the people can speak to. You know, there are a lot of limited fundings, a lot of limited resources, and you’re trying to do the, to get the biggest bang for the buck, but you’re not always going to have the resources to do that. So any help that you can get in that aspect, artificial intelligence for us, has helped make that impact, to help bridge that gap in some cases to work better, faster, more effectively to reach the community outreach we’re trying to do.

[00:52:26] Speaker B: Thank you, Derek. I do have a question for Teresa and then one Joe has that I’m hoping Glenn can answer for us.

Teresa, you know, let’s take a nonprofit down this journey. Maybe they have some idea and some funding, and they’re going to embark on looking at how AI can solve a problem for them.

What are, what are some suggestions in those early stages of working with an AI problem and an AI solution that you have to get right early on so that it’s not just an experiment, it’s something that you can bring to the organization and see value from this? I just see a lot of mistakes early on that prevent. And then we start saying, you know, why didn’t that AI ever make it into production? What can. What some are some of your suggestions.

[00:53:19] Speaker F: Around that I, I agree with you and I think you lose the momentum. Right. So I’m a big fan of starting small and trying to prove out different use cases first and making sure that it actually ties back to something that’s close to the mission. So you’re not just testing what I call the shiny object, and you’re just chasing something just from a technology perspective. But I think there’s two major ways that I got really creative being ahead of a the technology department. You’re always worried about rationalizing costs every year because of rising software and vendor costs. So every year I think I had ended up saving 7 to 8% just to remain flat. So to do innovation, a lot of times, first off, you have to find the money, and some of it is cost savings by rationalizing your own applications. I’m really good about saving money on the back end to be able to help fund innovation.

The second thing is I always made sure that I had incredible relationships with a lot of the products that we had purchased. So Microsoft and Salesforce and others, a lot of those firms have really special relationships already with nonprofits. So the ability to make sure that you’re leveraging all those free credits and different ways to take advantage of those relationships is key. Because if they know you’re interested, a lot of times they’ll not only offer support, offer support at a discount, but they’ll even, a lot of times invite you to improve your exposure, to accelerate your mission and get your knowledge out there by joining a thons and doing other things.

And then thirdly, I would say I would also have special relationships with a lot of the vendor firms that I had been partnering with.

And in many, many cases, their organizations care so much about giving back themselves.

So what ends up happening is a lot of times they’ll be delivering work for you and you’re going to want to test out some innovative pilot. There’s many times that they’re going to offer discounts or do some things for free if you just ask.

There was one time we were testing an innovative augmented reality experience. Experience. There’s no way I would have received the funding to do it, but it was a way to connect people, to see innovation in a different way. At a huge conference at Disney World, and it was a wild success. And it was basically me just partnering with this strategic firm and saying, hey, here’s some things I’m thinking about. What do you think? And there was advantages to them too, because they could leverage their, their brand from a marketing perspective too. So I’m always trying to find creative ways to, to co brand, co market, co deliver in creative ways to get funding with the various partnerships that I had had.

[00:56:12] Speaker B: Theresa, I was hoping you would go in that direction. The one thing I would add to this is that every one of the big tech companies are looking for stories to market, you know, use cases. And they cannot get that from corporate America for different reasons, mostly, you know, proprietary reasons. They should be able to get that from nonprofits.

They will champion your cause. They will put it up in front of 30, 40,000 people during their keynotes.

If you need help around AI as a nonprofit, definitely start with your technology partners and see where they can give you not just platform, but also expertise and guidance. And they’ll be there for you. We have a couple more minutes. I want to bring up a question with Glenn that Joe raised in the chat. Glenn, there’s a question here about how do we prevent AI from dehumanizing the relationship a nonprofit has with their constituents?

Do you have any thoughts around that before we close out today?

[00:57:13] Speaker E: Yes, certainly. And the simple answer is education.

But that education is not necessarily about how to read, write skills. It’s about values education.

You may or may not be familiar. You know, sort of several centuries ago there was a philosopher that said that, you know, ignorance leads to fear. Fear leads to anger, anger leads to hatred, that leads to violence. That is the equation, I. E. The answer to all of these things is about education, but it’s obviously about humanity education. So it’s really about helping to build and to foster those human, those natural human talents and skills that were all born with. You know, nobody taught us how to smile. It was just something that is part of being human and having empathy, having compassion, having that humanity for others is something that’s within us. But it needs to be fostered, it needs to be activated, it needs to be strengthened. But also it can be deactivated, it can be nullified.

And so just really my learning and my experience is about there are known and established ways that we can increase our own humanity and indeed increase the humanity of those around us.

[00:58:31] Speaker B: Thank you, Glenn for joining us. Thank you Larry, Teresa, Stephen and my other guests.

John, thank you for being here. Heather and Joe. If I’m missing Stephen, I think I got everybody here. Thank you for joining us on this very special episode. AI for Social Good insights from nonprofit leaders. Folks Giving Tuesday is coming up, the Tuesday after Thanksgiving, December 2nd.

Please think about reaching out to your causes and charities that you feel passionate about.

I’ve left a ton of them over here on the whiteboard and in the comments.

Thank you for joining this week. We’re gonna have a another special episode next week.

It will is digital to AI natives. How are how is Gen Z using Gen AI? We’re gonna try to do a little bit of reverse mentoring with some younger folks who are growing up in the age where Gen AI is just plugged into everything that they do.

That will be our episodes on the 21st.

We are going to take a break on the 28th for Thanksgiving and then we’ll be back in December with a whole bunch of new episodes. A couple ways you can find episodes, you can go to starcio.com coffee and that will always that will redirect you to the next and upcoming episodes. And if you want to see previous episodes, please visit drive.starcio.com Coffee I have all the other episodes up there for you guys to listen to. Everybody have a great weekend. Again, thank you for all my special guests, Teresa, Stephen, Larry, Joe, John, Heather, Glenn and Derek for your stories around AI for social good. Have a great weekend and we will be back here next week for another episode of the Coffee with Digital Trailblazers. Have a great weekend.

[01:00:26] Speaker F: Thank you.