Higher education is facing its fair share of challenges, from mounting financial pressure to an evolving digital landscape. AI offers a powerful lever for future-proofing institutional strategies. Rather than being a standalone solution, AI is the combination of strong data foundations and intentional digital transformation. It enables institutions to scale more efficiently, unlock hidden opportunities, and adapt to change with agility. This FAQ explores how AI is being used across advancement and development operations, not only by well-funded programs but also by lean teams seeking to do more with less. Whether it’s improving prospect identification, maximizing outreach, or cultivating long-term donor pipelines, AI is becoming an essential tool in building sustainable and resilient advancement models.

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Developing sustainable business models and digital transformation are among the top strategic issues in higher education. Can you make the case for AI from the perspective of future-proofing?

AI is the outcome of numerous other factors, like your data being well organized, and having the information for AI to start with. As an organization goes through this journey of finding a business case for AI there are two main options, and they are not mutually exclusive.

1. Organizations can invest in the technology of the day, and as that technology changes, they keep investing in those different technologies.
2. Organizations can invest in their future by having the fundamental data that will allow them to pivot more easily to changing markets and new technology, and ensure long-term sustainability and self-sufficiency.

There is a compounding cumulative effect gained by focusing on the fundamentals that both enable AI, and also protect from the downside of change.

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What is the business case for AI in a period when resources are short, and institutions may be confronting declines in tuition revenue?

AI allows organizations to scale. The traditional way that organizations scale is through investments, and additional human resources, which has its limits in terms of what makes economic sense. Whereas getting a return on AI is very quick relative to a return on a capital campaign.

Also, AI works all the way up through the pipeline, including the identification of diamonds in the rough, or prospects who aren’t on the radar, while also cultivating and planting the seeds for the next generation of alumni and donors.

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What ways are institutions using AI to make prospect identification more effective, efficient, and scalable?‍

The biggest thing to understand when it comes to prospecting, is that it's not a competition with traditional methods. Finding the diamonds in the rough after conventional approaches have been applied is useful, because that's additional revenue into the system.

AI can spot patterns very well, one simple pattern we see is that people who make a $2,500 and over gift become significantly more likely to make that jump to $50,000. Those people often start with a gift below or at the median gift amount.

That example illustrates how AI can highlight the characteristics of what makes up a major donor in a way that is very different from Persona building. With this information, AI can start planting the seeds with a wide variety of people, which will create a stronger pipeline downflow.

This is something that needs to be looked at in the context of the institution and built in a way that accounts for the nuances of how the organization operates. That will ensure the maximum benefit of an AI investment, as opposed to duplicating what is already known.

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How are some of the most well-resourced advancement programs using AI? And how can similar tools be accessible for shoestring operations? ‍

Broadly speaking, AI is an umbrella term. The opportunity at larger institutions is having the capacity to do something differently. While the opportunity at the smaller institutions is the capacity to do something they weren't able to.

AI at a large shop may be used to reprioritize people who would otherwise go unengaged, and AI at a small shop may use it to find those extra opportunities.

If an advancement shop has gift officers that work by phone, and each have a couple hundred people in their portfolio, making all those phone calls can be a daunting task. AI can be used to predict who is going to answer the phone.  We have had organizations get to 90% contact rate, that makes it much more efficient for a gift officer to get through their list and increase momentum.

What are some of the ways that AI is changing  how institutions identify prospective major donors and cultivate prospects?

The big way that AI is changing how institutions identify prospective major donors is through behavioral factors like time and attention. We live in an attention economy, and the TV commercial itself is not nearly as effective as it used to be. It's the consumer behavior and seeing others do things that has influence now.

We’ve seen firsthand what happens when you provide value in your content. We were doing a personalized video for an organization that was holding a marathon, we sent each constituent a personalized video with their finish line photo along with their race time. What we saw was people pausing the video, taking screenshots, and sharing them online. We were able to provide those constituents value in that moment, and when that behavior is recorded and fed into AI, it becomes very clear what's valuable and what's not.

When we look at how digital behavior has changed in the last ten or twenty years, we see that most organizations don't have the technology in place to capture it. You can go into CVS, Walgreens, Starbucks, or McDonald's, and they’re investing in this type of infrastructure to capture data about what people are interested in and reward them, expanding the market potential of their customers.

We’re not seeing these approaches in alumni associations where loyalty can be quite high. So, by making a fundamental investment in your data towards AI, you open these doors which also serve as shields for changing markets and changing conditions.

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