Using AI to Strengthen Donor Relationships in Higher Education

It’s important to define AI because it’s an umbrella term that can include things like natural language processing, robotics, fuzzy logic, and of course, machine learning.

But that’s very different than implementing a ready made solution like ChatGPT or Perplexity.

This is the story of an organization moving in from where they are today to a future ready state.

I’ve never worked at a organization that uses so many platforms, so many different systems.

We have at least 17 core systems that sit outside of our CRM that gather data, that interact with our donors and constituents.

That information is lost many of the time. We have so many different systems that are talking in different languages, and the datasets are different, and the integrations are different.

We struggle with one version of the truth.

Legacy things, like, a lot of nuances are so exception based.

We built a whole system out of a small percentage of people that wanted things a very specific way, and we built a whole band aid solution for it.

We were on a technology that was twenty years old, and we needed to come to a modern technology.

We were in an unprecedented time. Right? AI was not a fringe thing anymore in academic. It was actually being used everywhere.

Our object here is to use technology to help make everyone’s lives easier, to make us work smarter, not harder.

That we’re gonna be able to do things that have not been done yet within this industry.

And that and that is really, you know, using AI and machine learning to be able to drive greater efficiency in our daily operations.

It is the dawn of an AI era and that I think is being said.

Because if you do it now, the best time to plant a tree was twenty years ago.

The next best time is today. Today is that moment when you can start to capture data.

Because ultimately, the data is only as good as how far you can extend it in your organization.

It’s not my analytics team role to create analytics for analytics sake.

You need to start caring about what data is in your system.

Privacy and preference, which is a growing concern in our industry and around the world with people’s use of their data.

The future is really looking like it’s going to be based around ownership, not only for organizations to really own their dataset, but also for individuals.

And organizations will need to have an easy way to send that information upon request to a constituent, and they will also need that information themselves to maintain their own relevance.

This is going to future proof our organization and help insulate us from exterior headwinds, whether it be enrollment declines, staffing decline.

We see this as setting the foundation up for not just my term, but for the the people that follow us.

We know that data and information allowing institutions to own that information is sort of the first step in creating an environment that’s future proofed.

And that’s because you may not know what the future technology is going to be.

But you know that without the information, you’re going to be able to is going to be.

But you know that without the information and without it organized in a way that AI can consume it, you’re going to be behind.

Data for an organization is critical.

It is the lifeblood of your organization.

If your organization if the leaders of the organization are not investing in your data, you’re going to have a challenge going forward into the future.