# AI Maturity Model for Nonprofits pt 1

An episode of [Community IT Innovators Nonprofit Technology Topics](https://invisiblenetwork.ai/podcast/1536843269), 17 Jul 2026, 30 min.

Audio: https://www.buzzsprout.com/1029925/episodes/19509308-ai-maturity-model-for-nonprofits-pt-1.mp3

In the first part of this two-part conversation, Carolyn Woodard and Mimi Yeh, Engagement Director at PTKO, and George Danilovics, Vice President of Information Technology at AHIP, walk through an AI maturity model designed to help nonprofits move from pilots and experiments to AI that is genuinely embedded in how the organization works: quiet, boring, and everywhere. The conversation opens with a striking data point: 80% of nonprofits are already using AI in some form, yet 90% of nonprofit professionals still feel unprepared to fully leverage it. Mimi and George use a five-stage maturity model that moves from ad hoc, experimental, systematic, strategic, and pioneering - to help organizations find where they are now and what intentional progress looks like. The heart of the discussion is the systematic stage, where AI stops being someone else's project and starts becoming part of the organizational DNA. As George puts it, the destination is a world where AI is as unremarkable as email. This episode covers: • The five stages of AI maturity and how to identify where your nonprofit currently stands. • Why the experimental stage is necessary but not the destination, and what it takes to move past it. • What the systematic stage looks like in practice: defined goals, shared prompt libraries, documented best practices, and governance that evolves alongside your AI use. • How strategic AI adoption shifts the question from what tool should we use to how should we organize ourselves to get the most value. • Why reaching the pioneering stage is not the goal for most nonprofits, and why that is perfectly fine. Resources Mentioned • PTKO • AHIP • Mission-Aligned AI Adoption Model – Community IT Innovators • Full Webinar: AI Maturity Model for Nonprofits – Community IT Innovators • Nonprofit IT Management Community – Reddit _______________________________ Start a conversation :) • Register to attend a webinar in real time, and find all past transcripts at https://communityit.com/webinars/ • email Carolyn at cwoodard@communityit.com • on LinkedIn • on reddit/r/nonprofitITmanagement • on the Community IT website Thanks for listening.

## Transcript

[0:23] Community IT Intro: Thank you for joining Community IT for this podcast, part one.
[0:27] Community IT Intro: Subscribe wherever you listen to podcasts and leave us a rating to help others find this leadership resource for nonprofits.
[0:34] Community IT Intro: Listen for part two in your podcast feed.
[0:39] Carolyn Woodard: Welcome everyone to the Community IT Innovators webinar.
[0:43] Carolyn Woodard: This is the AI maturity model for nonprofits, how AI becomes quiet, boring, and everywhere.
[0:49] Carolyn Woodard: We have experts from PTKO and AHIP with us today.
[0:53] Carolyn Woodard: If your nonprofit has gotten into AI and you have a policy, you've done a pilot program, you have an AI champion, small group of staff who are actively using AI tools, you're probably wondering what comes next.
[1:06] Carolyn Woodard: So, how do you move from that experimentation phase to genuinely embedding AI in how your organization works?
[1:13] Carolyn Woodard: Today we're going to hear, we're going to talk to Mimi Yeh from PTKO and George Danilovics from AHIP about what best practices they can share with us about finding your place on that AI maturity model and moving to where you want to be on that model.
[1:31] Carolyn Woodard: My name is Carolyn Woodard.
[1:32] Carolyn Woodard: I'm the outreach director for community IT.
[1:34] Carolyn Woodard: I'll be the moderator today.
[1:36] Carolyn Woodard: I'm very happy to hear from our experts, but first I want to go over our learning objectives.
[1:41] Carolyn Woodard: So
[1:42] Carolyn Woodard: Today we're going to focus on these themes.
[1:44] Carolyn Woodard: What is the AI maturity model, and where does your nonprofit fit?
[1:49] Carolyn Woodard: How do you build AI as a standard core competency across your workforce?
[1:54] Carolyn Woodard: And what does strategic AI implementation look like?
[1:57] Carolyn Woodard: What are the emerging best practices?
[2:00] Carolyn Woodard: And now I'd like to let Mimi and George introduce themselves.
[2:03] Carolyn Woodard: So, Mimi.
[2:05] Mimi Yeh: Great.
[2:05] Mimi Yeh: Thank you so much, Carolyn, and welcome to everybody.
[2:09] Mimi Yeh: Thank you for joining us.
[2:10] Mimi Yeh: I'm Mimi Yeh, and I'm an engagement director at PTKO.
[2:15] Mimi Yeh: Most of my work focuses on helping organizations improve how they work.
[2:20] Mimi Yeh: And I typically do that through strategy, organizational change management, and technology adoption.
[2:27] Mimi Yeh: AI is probably the newest example of a challenge that looks on the surface like it's all about technology, but at the heart of it, it's really about people, processes, and building new capabilities.
[2:42] Mimi Yeh: So thank you for joining us.
[2:44] George Danilovics: Hello, everyone.
[2:45] George Danilovics: My name is George Kanalovics.
[2:47] George Danilovics: Thank you all for joining this afternoon.
[2:49] George Danilovics: I am the VP of technology at AHIP.
[2:51] George Danilovics: We are a healthcare trade association in Washington, D.C.
[2:55] George Danilovics: In addition to leading the technology team, I've been getting guiding uh AHIP along our AI adoption journey.
[3:04] Mimi Yeh: I'm going to tell you a little bit about what we do at PTKO.
[3:07] Mimi Yeh: And one of the reasons that I really enjoy co-presenting with George is because we come from at AI from complementary perspectives and points of view.
[3:18] Mimi Yeh: As George just mentioned, he leads massive technology efforts and he blends strategic direction from within an organization.
[3:27] Mimi Yeh: And at PTKO, I work alongside nonprofits and other organizations to help them figure out how to adopt AI across their organization.
[3:37] Mimi Yeh: And that comes from leadership and governance to training and change management and then incorporating it into day-to-day workflows.
[3:46] Mimi Yeh: And that means that we get to see the patterns that emerge from a lot of different organizations.
[3:52] Mimi Yeh: And it's those patterns that shaped today's discussion.
[3:56] Mimi Yeh: And we're also really fortunate to work with partners like Community IT, which you'll hear about a little bit more from Carolyn.
[4:03] Carolyn Woodard: So, yes, before we get started with the presentation, if you're not familiar with Community IT and want to tell you just a little bit more about us, we are a 100% employee-owned managed services provider.
[4:15] Carolyn Woodard: So we provide outsourced IT support.
[4:17] Carolyn Woodard: We work exclusively with nonprofit organizations.
[4:20] Carolyn Woodard: And our mission is to help nonprofits accomplish their missions through the effective use of technology.
[4:26] Carolyn Woodard: We are big fans of what well-managed IT can do for your nonprofit.
[4:31] Carolyn Woodard: We serve nonprofits across the United States.
[4:33] Carolyn Woodard: We've been doing this for 25 years.
[4:36] Carolyn Woodard: We are technology experts and are consistently given an MSP 501 recognition for being a top MSP, which is an honor we have just received again in 2026, and we are the only MSP on their list serving nonprofits exclusively.
[4:51] Carolyn Woodard: I want to remind everyone that for these presentations, we are vendor agnostic.
[4:56] Carolyn Woodard: So we only make recommendations to our clients and only based on their specific business needs.
[5:00] Carolyn Woodard: And we never try to get a client into a product because we get an incentive or a benefit from that.
[5:06] Carolyn Woodard: We do consider ourselves a best of breed IT provider, though.
[5:09] Carolyn Woodard: So it's our job to know the landscape, the tools that are available, that are reputable and widely used.
[5:16] Carolyn Woodard: And we make recommendations on that basis for our clients based on their business needs, priorities, and budget.
[5:23] Carolyn Woodard: We did also get a lot of good questions at registration.
[5:25] Carolyn Woodard: So we're going to try and answer as many of those as we can.
[5:28] Carolyn Woodard: But it's only an hour.
[5:30] Carolyn Woodard: So anything we can't get to, you can join us and our experts today over on our community on Reddit at r/slash nonprofit IT management.
[5:38] Carolyn Woodard: And I'll share that link with you in the chat.
[5:40] Carolyn Woodard: We're going to continue to answer some questions over there after this webinar until about 4:30 Eastern.
[5:45] Carolyn Woodard: So another 30 minutes or so after the webinar.
[5:49] Carolyn Woodard: And then we do from community IT, we pop back in to our Reddit community every so often.
[5:54] Carolyn Woodard: So if you have more questions that maybe this webinar prompts in you, go ahead and you can ask them there and we'll try to answer them.
[6:01] Carolyn Woodard: And then a little bit more about us.
[6:02] Carolyn Woodard: So as I said, our mission is to create value for the nonprofit sector through well-managed IT.
[6:07] Carolyn Woodard: We also identify four key values as employee owners that define our company: trust, knowledge, service, and balance.
[6:15] Carolyn Woodard: So we seek always to treat people with respect and fairness, to empower our staff, clients, and sector to understand and use technology effectively, including AI where appropriate.
[6:25] Carolyn Woodard: We seek to be helpful with our talents, and we recognize that the health of our communities is vital to our well-being and that work is only part of our lives.
[6:34] Carolyn Woodard: And so with that, I'm going to turn it over to George and Mimi for the presentation.
[6:39] George Danilovics: Thanks, Carolyn.
[6:40] George Danilovics: So let's put our whole webinar on one slide in one line.
[6:45] George Danilovics: The more successful AI adoption becomes, the more boring it gets.
[6:53] George Danilovics: So think about what AI looks like in most organizations right now.
[6:58] George Danilovics: It's loud.
[7:00] George Danilovics: There are pilots, there's demos, there's lunch and learned, there's brown bags, there's a champion, or maybe there's champions in your organization, you know, forwarding articles around and best practices and new features.
[7:15] George Danilovics: And you know, that energy, it's real and it matters.
[7:19] George Danilovics: But it's also a sign that AI is still special.
[7:24] George Danilovics: It's an event.
[7:27] George Danilovics: Now think about the technologies that actually run your organization, your email, your calendar, your spreadsheets in Excel.
[7:37] George Danilovics: Nobody demos them, nobody champions them, they're quiet, they're routine, they're load bearing, they're just there.
[7:47] George Danilovics: That's what mature technology looks like, and that's the direction that AI is heading.
[7:54] George Danilovics: So in today's talk, we're gonna talk about that journey from the loud AI that we have today to the boring AI that is coming.
[8:04] George Danilovics: One caveat though, to you know, keep in mind as we go through this conversation boring doesn't mean it's unwatched or untethered or set to go run free.
[8:16] George Danilovics: We're not saying in any way to just close your eyes and let AI go rogue and do whatever it wants.
[8:25] Carolyn Woodard: Yeah, no, I think that's a good thing to say.
[8:28] Carolyn Woodard: Um, because you know, there are some parts of AI that that can in fact do their things unregulated.
[8:35] Carolyn Woodard: So we we always want to keep an eye on everything.
[8:38] Carolyn Woodard: All right, so we are gonna do our first poll.
[8:41] Carolyn Woodard: Um, so I'm gonna launch that.
[8:43] Carolyn Woodard: And um, this poll is about where is your organization on AI now?
[8:51] Carolyn Woodard: So the options you can answer are that you have no formal AI activity yet.
[8:56] Carolyn Woodard: That's totally fine.
[8:58] Carolyn Woodard: That's where you are.
[8:59] Carolyn Woodard: Uh, just let us know.
[9:00] Carolyn Woodard: Um, another option could be you have a pilot underway or pilots underway.
[9:05] Carolyn Woodard: Um, the third option is that you have AI in core workflows and you have defined goals.
[9:12] Carolyn Woodard: And then a fourth option is that AI is shaping decisions and strategy at your organization.
[9:19] Carolyn Woodard: And then you also, of course, have the option that it's not really applicable.
[9:24] Carolyn Woodard: So we always have people in the webinars who may be here to learn and maybe not working at an organization.
[9:31] Carolyn Woodard: So if this isn't applicable, go ahead and click that in.
[9:34] Carolyn Woodard: But
[9:34] Carolyn Woodard: Mimi, can you read those results?
[9:36] Carolyn Woodard: Can you see that and let us know what people answered?
[9:40] Mimi Yeh: Yeah, absolutely.
[9:41] Mimi Yeh: It looks like a good majority, over half of the respondents, say that they've got AI pilots underway.
[9:49] Mimi Yeh: And that's followed by about 28% of respondents saying that there's no formal AI activity yet.
[9:57] Mimi Yeh: That might mean that there's some experimentation and there's some one-offs, but nothing that's been structured into the organization.
[10:06] Mimi Yeh: Um, then we've got a little bit of a tie between uh AI shaping decisions and strategy, which is great.
[10:14] Mimi Yeh: That's over on the far end of the spectrum.
[10:17] Mimi Yeh: There's an equal number of respondents saying not applicable.
[10:21] Mimi Yeh: So
[10:21] Mimi Yeh: I find that interesting.
[10:22] Mimi Yeh: It does seem to follow a bit of a bell curve shape that we typically see in these types of situations, followed last but not least, by AI in core workflows and defined goals.
[10:36] Mimi Yeh: So a good smattering and you know, good scattering of different spaces and places within their AI journey.
[10:44] Mimi Yeh: That is so interesting.
[10:46] Carolyn Woodard: And so, George, is is that what you expected to see?
[10:49] Carolyn Woodard: Like, what is the state of nonprofit adoption of AI generally right now?
[10:54] George Danilovics: Well, I think our results that we got from the folks on this uh webinar fit what we're seeing others report in the state of the industry and what nonprofits and associations are doing with AI.
[11:07] George Danilovics: Um, and the results we just saw, and you know, what I recently read in the nonprofit resource hub, is that we're moving beyond that experimentation phase.
[11:20] George Danilovics: You know, we had a good chunk of people already doing the pilots, and they're thinking about what's what's next, what's beyond the pilot, which is great, you're in the right spot.
[11:28] George Danilovics: Um the
[11:30] George Danilovics: The headline of all of this is that experimentation is now normal.
[11:34] George Danilovics: Um, a few years ago, we were, you know, at AI and nonprofits, we're having conversations about whether we should be using AI.
[11:44] George Danilovics: You know, is AI coming for our work?
[11:46] George Danilovics: Is this something we should be approaching or just you know, say no?
[11:50] George Danilovics: That debate has largely been resolved, and the association in nonprofit space is moving forward.
[11:57] George Danilovics: You know, your peers are experimenting, many hopefully have policies in place.
[12:02] George Danilovics: And the real question now isn't whether to move forward, but how and how widely.
[12:10] George Danilovics: Uh,
[12:10] George Danilovics: I mentioned the nonprofit resource hub.
[12:13] George Danilovics: Uh, earlier this year, they put out a report where 80% of nonprofits are already using some form of AI.
[12:20] George Danilovics: 80%.
[12:21] George Danilovics: And what they're seeing is operational staff are saving 15 to 20 hours a week on average for work by using AI.
[12:31] George Danilovics: Uh, donations are seeing a 20 to 30 percent increase in donations when the fundraisers are leveraging AI to personalize campaigns and outreach.
[12:44] George Danilovics: But on the flip side of all that great news, 90% of nonprofit professionals still feel unprepared to fully leverage AI.
[12:55] George Danilovics: So why are we talking about this?
[12:59] George Danilovics: This is your permission to move forward, it's your permission to start doing AI, learning about AI.
[13:07] George Danilovics: But don't feel the pressure to do something hastily.
[13:11] George Danilovics: If your organization is still having the, you know, if having a should we scale this, great.
[13:19] George Danilovics: But if you're still having the, I don't know where to begin, it's it's not too late.
[13:25] George Danilovics: You know, the late starters they get to inherit better tools, they get guidance from from folks like me who have already, you know, figured out what to do and what not to do.
[13:36] George Danilovics: And you get to learn from those lessons.
[13:38] George Danilovics: And today we're gonna spend some time talking about what comes after that pilot, which is where a lot of you are today.
[13:45] Mimi Yeh: Um, okay.
[13:46] Mimi Yeh: So, like George said, there's good guidance out there for thinking about adopting AI, starting from a foundational place, which includes community IT's own mission-aligned AI adoption model that you see on this slide.
[14:01] Mimi Yeh: As Carolyn mentioned, that'll be part of the set of materials that you'll see in your follow-up email that comes out.
[14:10] Mimi Yeh: Eventually, a lot of leaders ask this particular question, and most of the time, there's usually no written guidance on how to navigate this.
[14:20] Mimi Yeh: And that is how do we move beyond a handful of enthusiastic users?
[14:25] Mimi Yeh: How do we move past a couple of pilots here and there to make this something that all of my staff know how to do?
[14:34] Mimi Yeh: And for the folks who responded earlier in the poll that said that they've embedded AI into their day-to-day operations, would love to maybe see in the chat window how you've done that and where some of your successes have been, and maybe some of your lessons learned.
[14:51] Mimi Yeh: But that's really what today's webinar is about.
[14:54] Mimi Yeh: So it's less about getting started because, you know, as we saw, many of you have already gotten started.
[15:01] Mimi Yeh: It's really about building the capacity to move past the starting line of AI.
[15:09] Mimi Yeh: Here's a map for the rest of our conversation today, and it covers the five stages of AI maturity, which we've adapted from cognitive path research.
[15:19] Mimi Yeh: And it ranges from ad hoc through pioneering.
[15:22] Mimi Yeh: We're going to go into each one of these in a little more detail.
[15:25] Mimi Yeh: I'm going to give you a quick explanation of each of those stages right now.
[15:30] Mimi Yeh: So on the far left, in the ad hoc stage, that's when individuals are quietly experimenting on their own.
[15:38] Mimi Yeh: The experimental stage is when the organization is catching up with pilots and policies that are being distributed out throughout the entity and not just in little pockets here and there.
[15:52] Mimi Yeh: Systematic is when AI is integrated into everyday workflows with real accountability.
[15:59] Mimi Yeh: And then strategic is when AI is used to help inform and make organizational decisions that matter.
[16:08] Mimi Yeh: And then lastly, at the end, on pioneering, that's when AI is enabling work that just wasn't possible before.
[16:16] Mimi Yeh: And we'll spend some time in each one.
[16:20] George Danilovics: But before we do that, look at those two curves at the top because this picture is pretty important.
[16:25] George Danilovics: That dashed line that's novelty, that's the buzz, it's the excitement, it's the demos, and it peaks very early.
[16:33] George Danilovics: You know, many of you right now that are in that experimental phase, you're hopefully seeing all that excitement, but it eventually drains away.
[16:43] George Danilovics: The solid line is business value and it runs in that opposite direction.
[16:47] George Danilovics: It's very low in those early stages, but it begins to compound as you move to the right.
[16:53] George Danilovics: You've probably seen similar uh curves like this from other organizations.
[16:59] George Danilovics: Gartner hype cycle is one that folks are probably pretty familiar with.
[17:03] George Danilovics: You know, excitement goes down, value goes up.
[17:07] George Danilovics: But notice where they cross right in the middle at systemic.
[17:11] George Danilovics: This is the stage where AI starts to feel routine.
[17:15] George Danilovics: It's the stage where value begins to take off.
[17:19] George Danilovics: So let's walk for, let's walk through the first two stages.
[17:22] George Danilovics: And as we saw in the poll, a good chunk of the folks on this webinar are are already in that second stage, that experimental stage.
[17:32] George Danilovics: Some of you are still on the ad hoc and getting ready to begin your AI journey.
[17:37] George Danilovics: So ad hoc, it looks like this.
[17:39] George Danilovics: You know, you've got a couple people in your organization, they're using ChatGPT, Claude, Copilot.
[17:46] George Danilovics: Maybe they got a corporate account.
[17:48] George Danilovics: Maybe they're still using their personal account.
[17:52] George Danilovics: We won't tell anybody.
[17:53] George Danilovics: Um, there's no policy, no objectives, no business cases.
[17:58] George Danilovics: But some of this is actually useful.
[18:01] George Danilovics: Um, the downside is it's invisible to leadership.
[18:06] George Danilovics: There's no structure to it, there's a lot of risk.
[18:10] George Danilovics: So, you know, what if somebody pastes donor data or member data into one of those free tools?
[18:17] George Danilovics: Nobody knows what happens, nobody finds out until it matters later.
[18:24] George Danilovics: So we really want to think about that first step, that big important step, to moving from ad hoc to experimental.
[18:31] George Danilovics: And this is where the organization begins to catch up.
[18:34] George Danilovics: You've got a basic policy, some guardrails around what you can use AI for, what you shouldn't use AI for.
[18:43] George Danilovics: And people start to talk about it.
[18:45] George Danilovics: They're using AI.
[18:46] George Danilovics: It gets talked about in staff meetings.
[18:49] George Danilovics: This this energy, it's it's normal.
[18:52] George Danilovics: And if you're in this stage right now, really you should be encouraging it.
[18:56] George Danilovics: Every organization passes through this experimental stage.
[19:01] George Danilovics: The mistake is confusing this stage as the destination.
[19:08] Mimi Yeh: So this stage gets its own slide.
[19:11] Mimi Yeh: That is because it's one of the most important stages in the maturity model.
[19:16] Mimi Yeh: Systematic is where organizations really start to make that transition from experimenting with AI to building a real organizational capability.
[19:27] Mimi Yeh: And it starts becoming a natural part of how the organization operates.
[19:33] Mimi Yeh: And you begin to see AI integrated into core workflows rather than one-off uses here and there.
[19:42] Mimi Yeh: Teams will have defined goals for how they're using AI.
[19:45] Mimi Yeh: Managers will have a sense of what success in using AI looks like for their particular teams or departments.
[19:53] Mimi Yeh: And this is a really big change because this is where best practices get documented and shared along with lessons learned instead of just living in somebody's notebook or somebody's chat history.
[20:07] Mimi Yeh: And this is also the stage where organizations should start investing in the infrastructure that supports the adoption of AI.
[20:15] Mimi Yeh: And those are the things like training, shared prompt libraries, some governance on how you want to use AI as AI matures and as your organization's use of AI matures.
[20:29] Mimi Yeh: And then who are the people responsible for helping to create that AI evolution in your organization over time?
[20:39] Mimi Yeh: It's also from a change management perspective, it's the point where AI stops being somebody else's project or someone else's pet effort.
[20:51] Mimi Yeh: And it really starts becoming part of the organizational DNA.
[20:56] Mimi Yeh: So interestingly, this is also the place back to what George mentioned in the label and title of our webinar here, AR starts becoming a little boring.
[21:09] Mimi Yeh: And we see that in behaviors like people stop announcing that they're using this cool new AI tool because now it's just part of how people are getting their work done.
[21:21] Mimi Yeh: It's another tool alongside the other ones that George mentioned that help people do their jobs more effectively.
[21:30] Mimi Yeh: George had this great analogy when we were preparing for this call that this is the stage when you stop casually dating AI and you just straight up commit to it.
[21:42] Mimi Yeh: And there's another great analogy that he's got that he's going to share in just a bit.
[21:47] Mimi Yeh: But I would say that one of the big points here is that being boring is actually a good sign because it means that you've moved beyond curiosity and experimenting.
[21:59] Mimi Yeh: Now you're starting that journey into sustainable adoption.
[22:05] Mimi Yeh: But it's also a point where we want to be mindful that it doesn't sit in the background so much so that people stop sharing their lessons and they stop um talking with each other and collaborating and co creating.
[22:19] Mimi Yeh: So
[22:21] Mimi Yeh: The other thing I do want to mention is that organizations don't reach a systemic stage just by buying better technology or better AI tools.
[22:31] Mimi Yeh: You get there intentionally by building these new habits, these new skills, and these new ways of working together.
[22:39] Mimi Yeh: So, you know, that's why we consider systemic systematic, not systemic, to be the pivot point.
[22:46] Mimi Yeh: Because that's where AI shifts from being a technology initiative to being an organizational capability.
[22:53] Carolyn Woodard: We have a quick question here that I think this might be a good time to ask is someone asks, can you give an example of having a specific objective versus it being part of the regular workflow?
[23:05] Carolyn Woodard: Do you have a quick example of that sort of thing?
[23:09] George Danilovics: I would say, you know, an example of a specific objective would be one use case for AI.
[23:14] George Danilovics: So, you know, someone may have an objective that says, you know, I want to learn prompts to write emails better with AI.
[23:22] George Danilovics: And you know, you can you can test that and you can see people sharing prompt ideas.
[23:27] George Danilovics: When AI use with email becomes systemic, it becomes second nature.
[23:36] George Danilovics: It becomes the button you push before you click send just to proof your email to make sure you know the language is the right tone.
[23:45] George Danilovics: Um, it becomes second nature without you thinking about it.
[23:49] George Danilovics: That's systemic.
[23:51] Carolyn Woodard: Yeah.
[23:51] Carolyn Woodard: And there's another question in there, which I'm gonna save for the end because it's kind of a bigger conversation.
[23:57] Carolyn Woodard: So uh Greg, h ang on.
[23:59] Carolyn Woodard: That's easy.
[24:00] Carolyn Woodard: All right, next slide.
[24:03] George Danilovics: So so this slide is is actually what you know the whole webinar grew out of.
[24:09] George Danilovics: Um
[24:10] George Danilovics: Nobody in your organization has, you know, you don't have an email strategy committee, an internal email strategy committee.
[24:18] George Danilovics: There isn't a Microsoft Office champion.
[24:21] George Danilovics: There's no pilot program of are we going to use Outlook?
[24:25] George Danilovics: Who's gonna use Outlook?
[24:26] George Danilovics: There's no lunch and learns on how do you attach files to emails.
[24:31] George Danilovics: Yet email is completely mission critical.
[24:35] George Danilovics: If if email went down from a day, your organization would grind to a halt.
[24:40] George Danilovics: Email's quiet, it's boring, it's everywhere, it's essential.
[24:46] George Danilovics: But here's the thing: some of us remember that it always wasn't that way.
[24:51] George Danilovics: Uh, I remember Outlook, it used to be a standalone CD that you would buy at Micro Center or Best Buy, and you would install Microsoft Outlook as an application.
[25:01] George Danilovics: And this was the first time that you could go from plain text emails to composing emails with color and adding attachments.
[25:12] George Danilovics: This was a novelty.
[25:13] George Danilovics: You had one spot that had your contacts, your calendar, and your email, and you can share data between those three different systems.
[25:23] George Danilovics: There was a time when email was new and organizations had to send memos around about what you should or should not say in email.
[25:33] George Danilovics: Um, and
[25:34] George Danilovics: All that infrastructure and novelty, it existed at a point in time, but it eventually went away because Outlook and email just became the part of how work is done.
[25:44] George Danilovics: You know, look at job postings today.
[25:47] George Danilovics: None of them say email proficiency.
[25:50] George Danilovics: Um, because that'd be kind of strange.
[25:52] George Danilovics: It's kind of assumed that everybody knows how to use email and send attachments.
[25:58] George Danilovics: So
[25:59] George Danilovics: AI, it's on that same trajectory, and maybe it's going to be moving a little faster.
[26:04] George Danilovics: So here's here's a question for you, and I'd like you to think about this.
[26:08] George Danilovics: You know, what would your organization look like if AI was as unremarkable as email?
[26:15] George Danilovics: Who would need to know what would they what would people be able to stop doing?
[26:22] George Danilovics: What would they be able to start doing?
[26:25] George Danilovics: Because that picture that you're thinking about, whatever it looks like for you and your organization, that's the destination that you're working towards.
[26:35] Mimi Yeh: All right.
[26:35] Mimi Yeh: So just as a recap, we've gone through the ad hoc stage, the experimental stage, and the systematic stage.
[26:44] Mimi Yeh: Here we are at strategic and pioneering.
[26:46] Mimi Yeh: And this is when AI starts changing the organization, not simply by the way that it works.
[26:53] Mimi Yeh: It starts showing up in how leadership makes plans for the future and how budgets get built and how the organization thinks.
[27:02] Mimi Yeh: And notice that there are some people markers on this slide.
[27:06] Mimi Yeh: And these are the ones that matter to me.
[27:08] Mimi Yeh: So leaders begin making different decisions, um, maybe more informed, maybe more holistic and reflective of not just internal operations within the organization, but things that you can collect and um consider as external forces that make a difference.
[27:27] Mimi Yeh: Hopefully, teams are working differently together and maybe being a bit more um selective in how they use their time together and moving away from those big old status meetings where we are regurgitating content to each other.
[27:45] Mimi Yeh: And then managers are hopefully thinking a little bit differently about roles and responsibilities.
[27:51] Mimi Yeh: Um,
[27:51] Mimi Yeh: I think about the way that a lot of people spend their time at work, and strategy is usually the one that just gets the short end of the stick and the least amount of time.
[28:03] Mimi Yeh: Hopefully, AI is going to stop being a tool question and it's going to become an organizational design question, and it becomes something that enables people to make better use of the available time that they have to really tackle those big needy problems that are out there.
[28:22] Mimi Yeh: So, in that strategic stage, there's also some governance markers.
[28:26] Mimi Yeh: Uh,
[28:27] Mimi Yeh: There are conversations around ethical frameworks, there's participation in industry conversations about AI, and it shifts from what tool should we use to how should we organize ourselves to get the most value out of this tool.
[28:46] Mimi Yeh: And that last stage, that pioneering stage, that is definitely rarer, and that is also reflected in the poll that we had at the beginning of our conversation.
[28:56] Mimi Yeh: So this is when AI is leading the industry, it's helping to shape standards, it's helping to create new services and member value that might not have existed before.
[29:09] Mimi Yeh: A lot of organizations might never reach that pioneering stage, and most don't need to.
[29:15] Mimi Yeh: This is not a scenario where the goal is for everybody to be at the end stage of that maturity model.
[29:23] Mimi Yeh: The goal is to be at the stage that works best for your organization.
[29:31] Community IT Intro: Thank you for joining Community IT for this podcast, part one.
[29:35] Community IT Intro: Subscribe wherever you listen to podcasts and leave us a rating to help others find this leadership resource for nonprofits.
[29:42] Community IT Intro: Listen for part two in your podcast feed.

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