675. Shift 5 — Beyond the Prompt: AI Fluency is the New Digital Literacy for Nonprofits - Woodrow Rosenbaum, GivingTuesday + Elizabeth Kelly, Anthropic

Summary

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Podcast Summary

We Are For Good Podcast – Episode 675
Shift 5 — Beyond the Prompt: AI Fluency is the New Digital Literacy for Nonprofits
Guests: Woodrow Rosenbaum (Chief Data Officer, GivingTuesday), Elizabeth Kelly (Head of Beneficial Deployments, Anthropic)
Hosts: Jon McCoy, Becky Endicott
Release Date: January 19, 2026

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Episode Overview

This episode explores why AI fluency is emerging as the new digital literacy for nonprofit professionals. Instead of focusing on simply writing AI prompts, the conversation dives into what it truly means for organizations to develop confident, ethical, and effective AI practices—moving beyond basic usage to strategic adoption. The guests share their recent launch of “Claude for Nonprofits” and a free AI Fluency course, discuss the importance of trust and governance, and offer practical advice for nonprofits at every stage of AI adoption.

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Key Discussion Points & Insights

1. Defining AI Fluency for Nonprofits

[03:34 - 04:50]

• AI fluency is not about mastering prompts but about knowing when and how to use AI tools responsibly.
• Elizabeth Kelly: “AI fluency means understanding what these tools are good at—drafting, summarizing, pattern finding, processing data—and where human judgment remains essential.”
• There’s a spectrum: some avoid AI out of overwhelm; others dive in without guardrails. Fluency is the balanced “middle path”—experimenting responsibly and making informed decisions.

2. Building Solutions for (Not Just With) the Sector

[05:03 - 06:09]

• Woodrow Rosenbaum stresses that nonprofits need tools tailored to their unique challenges, not off-the-shelf tech: “If all we do is productivity, we’ll just get there [‘mediocrity’] faster. And that’s not what anybody wants.”
• True opportunity: Use AI to achieve better outcomes, not just quicker processes.

3. Sector-Wide Shifts and Democratizing Impact

[07:27 - 10:09]

• Shift from “Should we use AI?” to “How do we use it responsibly?”
• AI is helping smaller nonprofits “punch above their weight,” leveling the playing field in grant writing, data analysis, and client impact.
• Real-world examples:
  • iDInsight works “up to 10x faster” on some tasks.
  • Small teams surfacing $1.2B in benefits for 70,000 households.
  • Funders increasingly expect the nonprofits they support to leverage AI tools for greater efficiency.

4. Designing Claude for Nonprofits & the AI Fluency Course

[11:07 - 13:59]

• The Claude for Nonprofits program was developed through a year of sector listening and piloting with 60+ grantees.
• Offerings:
  • Discounted access (75% off).
  • Integrations with Blackbaud, Candid, Benevity, etc.
  • Dedicated support, reflecting a focus on impact, not revenue.
  • Example: AI math tutoring to 200,000 students in Africa; 24/7 support for epilepsy patients via Claude.
• Designed in partnership with sector experts (GivingTuesday) to ensure true alignment.

5. Responsible AI Use & Trust

[14:44 - 17:34]

• Trust is now “the work.” Responsible AI use centers on:
  • Privacy: “Data shared with Claude is kept private by default. We do not use it to train our models.” (Elizabeth Kelly, [15:34])
  • Compliance: SoC2 Type 2, ISO 27001, HIPAA compliance.
  • Transparency: AI can draft, summarize, but “doesn’t know your community”—human review is essential.
  • Ethical guardrails: “The organizations that are doing this well aren’t just adopting tools, they’re building governance around them.”
• Realistic guidance: Use AI to augment—not replace—human experience and judgment.

6. Practical Steps for AI Fluency & Getting Started

[21:32 - 23:20]

• Start small and specific: pick a pain point and run a two-week experiment with a couple of staff.
• Cultivate internal champions before trying wider rollouts.
• Governance is non-negotiable: Define what needs human review, what data can be shared, and who is accountable.
• Free AI Fluency Course covers practical workflows (grant writing, program evaluation, donor engagement); designed for all nonprofit staff, not just techies.

7. Addressing Fears, Building Momentum, and Peer Sharing

[23:20 - 26:00]

• Address fears by listening and transparently showing data and case studies.
• Peer sharing (“What’s one thing you’ve used AI for—interesting, useful, fun, funny?”) helps demystify and normalize adoption.
• AI as a tool to return precious staff time to mission-critical work.

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Notable Quotes and Memorable Moments

• On AI Fluency:

  “Just like digital literacy has meant learning to evaluate websites and spot misinformation, AI fluency means understanding what these tools are good at... and where human judgment remains essential.”
  — Elizabeth Kelly ([03:45])

• The Promise and the Peril:

  “If all we do is productivity, we’ll just get there faster. And that’s not what anybody wants. This is an opportunity for us to evaluate how do these tools actually shift our outcomes, not just our workflow.”
  — Woodrow Rosenbaum ([05:03])

• Real Example:

  “My friend Ben, a six-person team, has used AI to identify $1.2 billion in benefits for 70,000 households… That kind of scale wasn’t possible before.”
  — Elizabeth Kelly ([08:21])

• On Responsible Use:

  “Claude can draft a grant narrative, but it doesn’t know your community. Human review is absolutely critical.”
  — Elizabeth Kelly ([16:26])

• Starting Small:

  “Pick one recurring task that eats your time… try it with Claude or your tool of choice, see if it saves you 30 minutes. That’s how fluency starts—one workflow at a time.”
  — Elizabeth Kelly ([24:58])

• Fostering an Experimentation Culture:

  “Ask a coworker what’s one thing that you’ve used AI for that’s been interesting, useful, fun, or funny?… Just ask that question and see what people are doing.”
  — Woodrow Rosenbaum ([25:34])

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Timestamps for Key Segments

• [03:34] — Defining AI Fluency for Nonprofits
• [05:03] — Building with (not for) the sector
• [07:27] — Shifts in data use and democratization
• [11:07] — Claude for Nonprofits: Launch and features
• [14:44] — Responsible AI, Trust, Governance
• [21:32] — Practical playbook for getting started
• [24:58] — One Good Thing: Tiny steps for fluency
• [25:34] — Sharing AI wins and building culture

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Actionable Takeaways

• Start small— Identify and experiment with one workflow where AI could save your team time.
• Empower internal champions to spread fluency.
• Prioritize governance (privacy, review processes, accountability).
• Build trust by transparently communicating limitations, successes, and reviewing AI outputs.
• Leverage free sector-aligned resources (such as the AI Fluency Course).

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Resources & Where to Learn More

• Claude for Nonprofits: anthropic.com
• GivingTuesday Data Commons: givingtuesday.org/data
• AI Fluency Course for Nonprofits: [Link in show notes]

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Closing Thoughts

AI fluency is poised to power the next leap in nonprofit impact—but only if the tech is used responsibly and paired with strong governance, sector-specific alignment, and a commitment to trust. With cross-sector partnerships, transparent experimentation, and collective learning, nonprofits of any size can chart an ethical, effective path forward in the AI era.

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Transcript

[A]

Hey friends, we have exciting news. If you are looking to build capacity, clarity and momentum in the new year, we hope you'll join this community at our first ever We Are For Good Summit on February 12th.

[B]

It's a free one day virtual gathering for nonprofit leaders, fundraisers, marketers, and the everyday change maker who's looking to elevate Good.

[A]

Yeah. You can expect more than 20 speakers across three tracks, plus live workshops and working sessions and roundtable conversations on building trust, partnerships, people power, and what leadership really requires in 2026.

[B]

Save your free spot at weareforgood.com summit and let's learn together, then turn that learning into action.

[A]

After the summit, we're returning to local by activating in local impactup meetups so the ideas shared during the day turn into action together. If you want to host a meetup too, all the details are [e-mail] summit. Let's kickstart the year in Community.

[C]

Just like digital literacy has meant learning to evaluate websites and spot misinformation, AI fluency means understanding what these tools are good at, drafting, summarizing, pattern finding, processing data, and where human judgment remains essential.

[A]

Hi friends, welcome back to our 12 shifts in 2026 series. There's so much talk about AI, you know, and I think some people roll their back because they can't keep up with it and some are super excited about it. There's such a delta of how do we actually leverage this, especially in the nonprofit space. There's so much opportunity. And so, you know, we're leading into the year with the 12 shifts conversations. And these aren't just trends, these are shifts that we believe can lead to like, meaningful difference that we can all step into this year. So we knew we wanted to have a conversation about AI, but we were ill prepared for the type of conversation we get to bring to you today. Friends, we're titling this beyond the prompt AI fluency for nonprofits and we have got a powerhouse duo. We've got Woodrow Rosenbaum back in the house. He's the Chief data officer from GivingTuesday. Good to have you, Woodrow. We're also welcoming Elizabeth Kelly. She is the head of Beneficial Deployments at a little known company called Anthropic. You may have heard of them or maybe you're chatting with Claude as we speak here. But y', all, this is all about a conversation of moving beyond the prompt, how AI fluency is the new digital literacy for nonprofits. So these two have just come off this really incredible launch of Claude for Nonprofits it is unlocking a lot for our sector we're going to dive into. What does that really mean? How can we actually use that? But let me tell you a little bit about kind of the backstory of each of these individuals if they're new to you. Woodrow has a front row seat to how nonprofits are evolving. What's changing in fundraising? What's changing in data and decision making as AI becomes more mainstream? And Elizabeth is bringing this lens of helping to build tools and training that are designed specifically for nonprofits, using new AI fluency course that they've launched and accessing programs that make responsible AI adoption more possible. They're thinking about this in an ethical way, which is why we wanted to have this conversation, because I know so many of y' all listening are concerned about that aspect, and we want to lean headfirst into it. How can we do this in a way that's not just responsible, not eroding trust, but building trust? And we believe this is something that is a huge unlock and opportunity for nonprofit leaders. So, Woodrow, Elizabeth, it means the world to have y' all in the house today. Welcome to the podcast.

[D]

Pleasure to be back. Thank you.

[C]

Excited to be here. Thank you.

[A]

Yeah, you bet. Well, we want to jump in today and get some tone setting from both of y'.

[D]

All.

[A]

AI fluency. We're moving, like, beyond just like your typical prompt. What does that actually mean? And why is that becoming the new digital literacy? Elizabeth, I'll start with you, and then we can go to Woodrow.

[C]

Thanks so much. So AI fluency isn't just about becoming a prompt engineer, which I know sounds very daunting.

[A]

Was it on my bingo card?

[C]

Yeah, exactly. You know, it's about knowing when AI can help, when it can't, and how to verify what it produces. So just like digital literacy has meant learning to evaluate websites and spot misinformation, AI fluency means understanding what these tools are good at, drafting, summarizing, pattern finding, processing data, and where human judgment remains essential. We've seen organizations get stuck in two places. Either avoiding AI entirely because it feels overwhelming or diving in without guardrails. And fluency is the middle path. It's really building the organizational muscle to experiment responsibly, learn what works for your specific context, and make informed decisions about when to use these tools. That's why we partner with GivingTuesday on this. They've spent years building a grassroots movement that understands what nonprofits actually need, not what tech companies think they need.

[A]

Woodrow. I mean, what a tee up. You know, we're givingtuesday super fans over here. Love the movement that y' all built. Why was this. This, you know, kind of lead us into this, of the tone setting that you think about AA fluency and why you dove into this project?

[D]

I really appreciate particularly that last point that Elizabeth made, because we're. We're in this place where we might actually be getting a tech adoption phase right in the nonprofit sector. And there's still. I mean, there's lots of hurdles, but we are seeing an industry that is leaning in, even if some are doing it reluctantly. And that's really encouraging. But we need partners who are going to build tech solutions for the nonprofit sector from the ground up, because otherwise all we're doing is off label solutions or just doing productivity. And I think that this is one of the risks that we are hoping to mitigate, that we think that this work will help to mitigate is that nonprofits will just use these new technologies to do the same mediocre job faster. And we don't like a lot of the trends in our industry. And if all we do is productivity, we'll just get there faster. And that's not what anybody wants. And this is an opportunity for us to evaluate how do these tools actually shift our outcomes, not just our workflow.

[B]

Okay, I have to tell you, this is one of the first times I have felt truly excited to have an AI conversation, because I do think that Delta that you referenced, Elizabeth, is very, very wide. We see people in community dive all in and get entirely overwhelmed. And then you have someone on the other side who is not using it at all and overwhelmed. And so I think that middle ground is really, really important. And I think this mindset shift is such a smart first step. And I also want to commend you both, before I get into the next question, for building with community and not for it. I think that is a very big difference where you're actively listening, you're actively testing with nonprofits. Thank you, Anthropic, please. Doing that because I'm really curious about this data. So when I think about data for the sector, and yes, I'm from Oklahoma, so I say data and not data. Woodrow. I think about Giving Tuesday so much because. And I hope people know about the Giving Tuesday data Commons. And it is such a wealth of information for our sector that is consistently being analyzed in patterns and looking at shifts. And so I want to know, from your perspective, Woodrow, what is the big shift shift, what are you seeing across the sector as AI becomes more mainstream?

[D]

I think on the positive side, we're seeing real conversations about how we solve structurally as opposed to just upskilling. We need the systems in place in order to make sure that these tools are actually doing the job that we need them to do and that we're in a position, as Elizabeth already alluded to, to interrogate those outcomes for our organization. So I think that what we're seeing now is investments being made and leadership recognizing that we need policies and policies that aren't just here's a list of things you can't do right, but are rather thinking about. This is going to continue to evolve rapidly. Let's have policies in place that help us to evaluate what's working for us in a really intentional way and not just be about prohibitions.

[A]

I mean, yes, please, on all of that. I mean, did you want to say something, Elizabeth?

[C]

Yeah, I'd love to chime in. And I'm from New Orleans, so I say data too. But you know, we at Anthropic are a very data driven company. It's like very much in our DNA. We have things like the economic index or just reporting on, like how users are using our product so that we can build in community with them. And I think there's a couple of really cool things that we've already started to see. One is this shift from should we use AI to how do we do it responsibly? And that's in part because you're seeing so many nonprofits who are actually just getting really outside scans about AI adoption. I think about iDInsight, which is reporting that they're working up to 10x faster on certain tasks, or IRC, which is synthesizing evidence in minutes to scale integrated delivery in crisis context. Organizations that are building fluency are able to capture these gains while maintaining the trust their communities expect. And I think that's encouraging other organizations to join them. It's part of why we're seeing a democratization story where small organizations that couldn't afford a data analyst or a grant writer are now able to punch above their weight. My friend Ben is a six person team that has used AI to identify 1.2 billion in benefits for 70,000 households. And that kind of scale, it wasn't possible before. Right. That's a huge return. And so it's no surprise that funders are starting to expect that the nonprofits that they're investing in are using AI, so they're delivering more for each dollar. I'm a social worker's kid. I grew up the daughter of a nonprofit CEO and I remember all the hours spent going through fundraiser databases or writing thank you notes or synthesizing different state requirements for certain funding. There's so much that AI can unlock and it's really exciting to see more and more organizations doing that.

[B]

I also have a story along this line. I want to shout out Kyle DeGood who is in our community. He's incredible person that works at William and Marion corporations and foundations. And I remember him telling me that all the energy that they used to take like searching for these grants and all of the legwork and how do we populate our data into this? He said it went down to seconds. It went from months down to seconds. And so now we can focus on outcome, we can focus on building the relationship, we can focus on interpreting it and building a bigger story. So I just want to give another real world example how that's working on the corporations and foundations side because it's not a magic bullet. There is no magic bullet. But I think the responsibility of this and going slow and measured is the way and I'm really glad that you're we're giving these sorts of examples. So keep going. John.

[A]

Yeah, I'm living for these examples too. Because y' all built this product, I wanna give space to celebrate. Cloud for Nonprofits is out in the world, so really exciting. Alongside that, y' all released this amazing AI Fluency for Nonprofits course featuring our friend Kelsey Kramer. Gotta give her a shout out, but what I love is that it was teaching in workflows like Step by Step. This is something that kind of takes our hand and can help us actually move the needle on something. Tell us more like who did y' all build this for? What is like what are some of those resources and what are you hoping some of the outcomes from Yalls perspective will be in getting these resources in more nonprofit's hands.

[C]

I'm really excited to talk about our launch and our new product and even more thrilled we were able to do it in partnership with Giving Tuesday. I mean, we built this based on a year of listening. The consistent feedback from nonprofits was staff spend too much time switching between systems, pulling manual reports, answering routine questions. Small teams need new ways to move faster without adding headcount. And so before we even launched, we actually piloted with over 60 grantees across Robinhood, Tipping Point and Constellation Fund to learn what actually works. And so when we came to market, we were able to put out discounted access 75% off, which is market leading connectors to nonprofit specific tools like Blackbaud, Candid Benevity. So Claude works where nonprofit organizations already are and a free AI fluency course that we built with GivingTuesday because they know this sector deeply. And we wanted to make sure this was designed for nonprofits, not just marketed to them. We've also been collaborating with the bridgeband Group, Ideals Consulting, Barra Solutions, Slalom, all of these organizations that are providing tailored expertise to nonprofits adopting new technologies. And we're working to provide really dedicated support to nonprofits and helping with their overall strategy, impact measurement, organization wide implementation of AI. One of the things that we're really proud of is that we've built dedicated applied AI customer success teams who are working with nonprofits the same way they would work with our largest enterprise customers, based off the impact that we think they can have on the world with AI as opposed to the revenue they're generating for us. And we know this impact can be huge. We want nonprofits to be able to spend less time on administrative work and more time on the mission. And the scale is big. We've seen Rising Academy providing AI math tutoring to 200,000 students in Sub Saharan Africa via WhatsApp, the Epilepsy foundation offering 24. 7 support to 3.4 million Americans using Claude. These organizations are using AI to extend their reach in ways that weren't possible before. And we want to make that accessible to every nonprofit with Claude for nonprofits.

[D]

For us, the reason why this partnership works is because of that comprehensive approach that this isn't just here are some tools, you can adopt them. There's a discount. This is recognizing that nonprofits need help with their resourcing. They need to be able to capitalize on the productivity opportunity here to, as Elizabeth said, focus on the mission, focus on outcomes where we don't have a lot of excess resource in this sector, and also understand and have confidence that we know how to use these tools and that we're going to use them responsibly. And that package is how we're going to actually move forward as an industry. And we need to be doing it in that comprehensive way, which is why it's working so well for us and our network.

[B]

Yeah, I mean, I think when you value a line and you agree on the big things, it's so much easier to move more quickly. And this is something that we do want nonprofits to feel like they can move quickly through. But one of the things that is really bubbling up for us, in fact, it's our number one trend of 2026 this year, is trust is the work now, nonprofits run on trust. So let's get into that as it relates to AI. What is responsible AI use look like in practice? And I want to like focus on privacy and data and bias and how are we looking at transparency and human review? And I know you both have gone through this deeply as just something that we deeply care about as a sector. So Elizabeth, I want to pitch that question to you first and then, Woodrow, I'm going to come back to you.

[C]

Yeah, I couldn't agree more. And I think that trust, transparency, responsibility, this is built into who AI Anthropic is as a company. It's why we were founded with really this dual mission of making sure that AI is developed safely and responsibly, but also that it's deployed in a way that benefits all humanity and is doing so in a way that values trust, privacy, all of the things that are so core to the work that nonprofits are doing. So as with all of our teams at Enterprise Accounts, data shared with CLAUDE is kept private by default. We do not use it to train our models. Claude maintains SoC2 Type 2, ISO 27001, HIPAA compliance, all of the Alphabet soup that actually matters. When you are the guardians of incredibly important sensitive data. Whether you're working with inner city kids at a homeless shelter or you're providing mental health services like your clients need to know that you are going to be safeguarding the trust that they placed in you. And anytime we build a connector with candid benevity, the rest of them, we make sure that they don't have access to anything you haven't explicitly given them permission to do. In our view, responsible use also means being honest about limitations. CLAUDE can draft a grant narrative, but it doesn't know your community. Human review is absolutely critical. It can summarize program data, but it can make mistakes or miss context that a program officer could catch. So we tell organizations use AI to augment your experience, not replace your judgment. And that means building in checkpoints who reviews AI generated content before it goes out. How do you verify claims or statistics? What decisions should never be delegated to AI? The organizations that are doing this well aren't just adopting tools, they're building governance around them. And we love partnering with organizations to get this right because we all win when we do.

[A]

Hey friend. Taking a quick pause to share about some of our amazing partners. Meet GiveButter, RKD Group, Whiteboard, and so on. These aren't just amazing partners for we are for good. They're value aligned allies who are fueling and growing the impact uprising. And so of course, we want you to know them. So if you are looking for a new CRM or a fundraising or marketing partner, maybe an impact strategist or a creative team, we'd love to make a warm introduction for you to one of our trusted partners. They happen to be powered by amazing humans, too. You can check them [e-mail] Rex that's weareforgood.com RECS.

[B]

I mean, Woodrow, pick up that thread. How are you seeing trust evolve in this process?

[D]

So I think that, I mean, first of all, just worth reiterating, these technologies should not be replacements for humans. They should augment our human workforce. And that's really important. And I think to a degree, we have the benefit of we don't have a lot of excess headcount in the nonprofit sector. Nobody's replacing 6,000 human beings in their workflow overnight. And to suddenly discover, oops, that was a bad idea. Right? So great, we're not doing that. That's excellent. So what are we doing instead? I think that one of the ways that I think this whole program has been helpful is Anthropic's 4D framework is very straightforward, and it gives you a really clear understanding of how am I going to set up those checkpoints and what I need to be watching for, and how do I ensure that I'm learning how to use the tools that make them better and validating what they're doing for my organization so that I'm mitigating that risk. And I think that these tools, one of the reasons why there is so much experimentation and adoption compared to previous technological evolution in our sector is because they are by their nature, so accessible. The large language models are built to engage with us in natural language, and that means people are experimenting. And on the one hand, that mitigates the risk of people not doing anything with them. On the other hand, it does exacerbate the risk that Elizabeth mentioned earlier of jumping in with no guardrails. And there are some really simple ways of managing that. What we did at Giving Tuesday, for example, is we created an AI learning circle. And we're fortunate in that we have a highly skilled technical team of 40 data scientists and data engineers. Now, most organizations don't have that. But what we did was just create an environment where all of our personnel, regardless of whether they're technical staff, can experiment with these tools in a variety of ways that aren't on the program, aren't on the mission, but are just like trying stuff out and sharing with each other what they did and what they learned. And we're coupling that with some basic training that our technical staff provide that is available now through this anthropic program. And there's lots of other avenues where you can ensure someone can help with the technical details people need to learn. But this is a very simple way of giving, getting people an opportunity to see what kind of outputs these tools produce and understand how do I get the best result out of my use of those tools in a way that is really safe.

[A]

Yeah, I think that's super practical. And I, I love the idea sharing and the empowerment that comes of people finding tools that work for them and sharing what's working and sharing how it breaks through. I think that can be done with a simple stipend too, you know, to empower people to like, find ways to use AI in whatever they're facing in their workflow. So, Elizabeth, I want to kick it to you because a lot of nonprofits maybe listening are like, okay, AI Fluency is on my to do list this year across our organization. What's the playbook? Like, where does someone start?

[C]

So my first piece of advice is to start small and specific. Pick one workflow that everyone finds painful. Maybe it's summarizing board meeting notes, drafting donor thank you emails, or pulling data for a quarterly report and run a two week experiment with two to three staff members, measure the hours saved and then decide together whether to expand. And we do this too at Anthropic. I think about my team in a weekly update that we draft. And it was proving a pain point. And we spent a lot of time figuring out how could we codify the process, what was the prompt that we could all use. And it took what was something that people were annoyed about having to spend time on into a very straightforward, better output. And there's lots of examples like that for any organization. I think you also want to build internal champions before you roll out organization Wide Smart. Yeah, it makes a big difference when you've got one or two people who become fluent first and then teach their colleagues. And so there's these continuing returns. This is how the AI fluency course is designed. It's free and it covers grant writing, program evaluation, donor engagement, and it doesn't require any technical background. And when you have a couple of folks who try it start to see the dividends and then get their colleagues excited. That's the way the momentum builds. And most importantly for nonprofits, given the trust that is placed in them, you can't skip the governance conversation. Before you scale, you need to get alignment on what types of content need human review, what data can and cannot be shared with AI tools, who's accountable for AI generated outputs? And the organizations that are building this muscle early can avoid problems later.

[B]

Okay, those are so genius. I love them so much. I think it is such a good starting point. Can I add one more? And I would say address the fears. What is the fears that the group has about AI? I say this because I did this with my parents over the holidays. Can we talk about this? It took my dad, y', all, years to trust Venmo to get a Venmo account. He's a boomer. He's 74 years old. And I just think people have read things, seen things that create a bias. It truly does. And I think if you can understand the fears of your audience quickly, probably with AI, you can find data that could respond to those. And I do think that showing that data is helpful in the use of this AI and how it's moving the organization, coming back and sharing success stories is going to increase confidence. It's going to allow people to come along with it. Because I can tell you, just as as an adopter, I use Claude for myself personally, it has transformed the way that I work, the way that I think, the way that I prioritize, and I say that in a good way. So I want to get to the brass tacks of all of this because, Elizabeth, when we end our conversations, we end with a one good thing. And this is like a very tight distillation of whatever's bubbling up for you. What is one good thing listeners could do this week to build a high fluency? And I'm talking about something that would improve a real workflow. Maybe it builds trust. What would you say to that? Elizabeth, I'll start with you.

[C]

My advice is just to take one recurring task that eats your time. Maybe it's drafting a meeting agenda, summarizing notes, writing the first draft of an email to a funder. And try it with Claude or your tool of choice, see if it saves you 30 minutes. And that's how fluency starts. One workflow at a time. If you want to go deeper, you can take the AI fluency course for nonprofits. But really just starting with that initial step, I think you can see what a powerful unlock AI can be. And it just helps reduce the fear that many people have.

[B]

Woodrow, what's bubbling up for you?

[D]

So I would say, I mean, one of the things we want to do is help People get out of silos and feel comfortable. And I think a way to do that is ask a coworker what's one thing that you've used AI for that's been interesting, useful, fun, or funny? And just ask that question and see what people are doing.

[B]

That's a good one.

[C]

We did it coming back from Christmas break and it was just really fun to see the interesting ways.

[B]

Yeah. What do people say?

[C]

I mean, it was everything from trip planning for fun vacations, to present ideas for difficult aunts, to how do I get my 3 year old to eat the food that's being served at Christmas dinner? Like, there was a huge gamut, but it was a really fun exercise.

[A]

I had it rewrite a recipe based on the ingredients I had the other night, and it was very helpful. Such a good combo. I just want to call one thing out because I was excited when this announcement came out. And you know, we've had a big announcement too, of going deeper with partnerships. And I just want to put this on a pillar for a second to say, y', all, this is how it works. To lock arms for impact.

[B]

Exactly.

[A]

Find value aligned partners. You are going in the same direction and we can go so much further when we get in step together. And I love that y' all are modeling this for the sector in such an inclusive way, in such an empowering way for the sector. So just thank you both for seeing this through. I'm sure it was a huge lift to actually bring it to market. So just grateful for y' all both doing that. As we close out, people listening are going to want to connect with y'.

[D]

All.

[A]

What's the best place to learn more about the program? The cloud for nonprofits, maybe the program in general. And just like where to find y'.

[D]

All.

[A]

Where do y' all hang out online? What's the best place?

[D]

Well, I'm always available on LinkedIn and the data commons work [e-mail] data so you can find us there.

[A]

Awesome.

[C]

Visit [e-mail], you can find out all the details about cloud for nonprofits. And I like Woodrow. I'm also a very active LinkedIn user. Look forward to meeting folks there.

[A]

Awesome.

[B]

And if you want to go deeper into this conversation, please check out that AI fluency course. We're going to link to it in the show notes. I also think fundraising AI does a really good job of centralizing resources. I think the ethics are so strong there, so check them out and just keep learning about this. Friends, I think that's the thing. AI is something where not everybody is going to be an innovator or an earlier adopter, but the longer you take to come along, the longer the education is going to be. So address those fears and let's get on board, because we want to give you back some of your time, and we want to make your work as efficient as and. And as impactful as possible. Elizabeth, Woodrow, you guys are a treasure to the sector. Thank you for coming in. We deeply appreciate you both.

[A]

Thank you.

[D]

Yeah, thank you.