For-Purpose AI

The Path #29

One of our biggest motivations for launching Pathfindr was that we wanted to be able to bring the power of AI innovation to underserved sectors. We saw that Big Consulting and other players in the tech sector were hyper-focused on making inroads with Fortune 500 clients, all of whom have deep pockets. Many (if not most) had already established robust AI innovation capabilities in-house. Despite this, the number of well-publicized production implementations of generative AI solutions is much smaller than one would think, given how much time has passed (~20 months) since ChatGPT took the tech world by storm. This week’s press release from JP Morgan touting the release of LLM Suite, an internal research assistant, begs the question - how long had they been working on it before they felt confident to release it? How much did they have to invest to get a workable generative AI solution?

Now put yourself in the shoes of a leader in a non-profit (or “for purpose”) organization. Perhaps you have cost overruns that you need to control or efficiency gains you need to make. Maybe you are struggling to attract or retain volunteers, or to capture more funding from donors or governments. You’ve heard that AI can help you address these needs, but you’re not sure where to start, or how to afford it even if you did. What can you do?

We love good news here at Pathfindr, and the good news in this case is….you can do a lot.

Let’s start with something that is top-of-mind for most NFP leaders: cost. Generative AI that can transform how your staff or volunteers operate is not that expensive. A ChatGPT Teams subscription - which would allow your staff to create their own GPTs to do a wide range of tasks including research, data analysis, image generation and more - would cost you less than $5000 per year for a team of ten. That’s 5% of one person’s annual salary for something that can make ten people 10% more productive (at a minimum). If you use Microsoft, you can add an Azure Open AI capability for less than that. If you build multiple use cases on top of it, your annual cost will likely go up, but so will your productivity. The math checks out.

OK, so the money’s not an issue. What about risk? We’ve talked a lot about risk in other editions, and the same guidelines that apply to enterprise apply to the for-purpose sector. If you’re using ChatGPT Teams or Microsoft Azure, and have opted out of having your inputs and data used to train external models, you’re sufficiently protected for internal use. However, It’s still a good idea to put policies in place that prevent your staff or volunteers from entering personal data or other sensitive content.

Adoption can be another challenge…but this is an area where NFPs have an advantage over their industry counterparts. At times, implementing AI to help someone with their job can make them feel nervous or fearful; they worry about getting replaced. Because volunteers aren’t relying on a salary from their role, the more that you can help them amplify their impact while maintaining or reducing the number of hours required of them, the more they’ll appreciate it.

Now that we’ve put some concerns to rest, the next question is - what can a for-purpose organisation do with AI? The answer is “pretty much everything a for-profit can” in terms of productivity, efficiency, and cost reduction but there are a few unique use cases that NFP leaders might not have considered.

1. Fundraising - both analytical and generative AI can be huge assets to those responsible for raising funds for their organization. Your pool of potential donors is essentially your list of sales prospects and should be treated accordingly. You can use analytical AI to segment them by demographic, location, interest, previous activity or different levels of expected spend. Based on their prior donations and known areas of interest, AI can make recommendations to contact specific people at specific times, when they are most likely to write a check (or make a transfer, in this day and age). Generative AI can help you create targeted outreach messages at scale, greatly increasing the reach of your team.
2. Advocacy - putting your organization’s activities and cause directly in front of government decision-makers is often at the top of the to-do list for many NFP leaders. In addition to the custom outreach approach used for donors, AI can scrape news outlets and other websites to compile relevant information to inform your advocacy efforts. It’s the most efficient way to stay updated with the latest developments in areas that matter most to you and your organization.
3. Volunteer Experience - your volunteers give their time because they support your organization and are passionate about what they do. The more you can enable them to spend their time doing what they love, the more effective your team will be. That’s why it’s important to remove as much manual and repetitive work as possible from their plates. AI is great at reducing the time it takes to write reports, summarize emails or calls, follow up on action items, or any other mundane parts of a volunteer’s daily responsibilities.

AI is an incredibly powerful tool that can transform the way your for-purpose organization operates and make it easier for you to focus on what’s most important (and automate the rest). If you’d like to learn more, register for our workshop on August 7th - we’ll cover some practical ways to use AI to change the game on how you and your team operate every day.

Until next week!