The potential of artificial intelligence (AI) can’t be understated. Used ethically and effectively, AI provides colleges and universities like yours the opportunity to spend less time gathering data and more time personalizing the student experience. But, like all new technologies, institutions are still learning about AI and the best ways to get started.
Salesforce.org’s first-ever AI for Good Week offered institutions the opportunity to learn all about AI for Higher Ed - what it is, how it can be used across departments & throughout the student lifecycle, and how Trailblazers like Cal State East Bay, Taylor University, and Southern Methodist University are using this technology today.
Here are the 5 key learnings from AI for Good Week:
AI Can Have a Profound Impact on Transforming the Student Journey
From chat bot hackathons to a discussion on the ethical use of AI, we saw in the AI for Good Week kickoff broadcast how Einstein for Higher Education can be leveraged to improve the student experience at scale. You don't have to be a data scientist to use Einstein - everything is available at your fingertips to access intelligent insights that can make a profound difference in student outcomes.
AI offers a path to making dramatic progress toward your mission; the future is bright, and institutions are already learning best practices from each other. By leveraging Einstein for Higher Education, you can join a community of changemakers that are using AI to transform education for good.
Gain insight at each stage of the recruitment funnel
Using predictive analytics enables institutions to gain insight into prospective students' likelihood to move to the next stage of the recruitment funnel. In the Recruitment and Admissions AI Master Class, Nathan Baker, Director of Recruitment and Analytics, discussed how Taylor University accomplishes this by leveraging its data for information that will help admissions counselors focus on prospective students with the most potential to enroll.
But Baker is careful to note, "This does not dictate how we operate. It's just another point in our process where we can be efficient." Baker adds that history repeats itself with predictive analysis, because this analysis looks for the next opportunity based on something that happened in the past. "We have great potential to leverage this information," he says. "But we can't just let history repeat itself, because that doesn't benefit our institutions or society at large."
Start small with AI
As we heard Terry Teague, Corporate Programs and Systems Administrator at Southern Methodist University say, “The best advice I can give with AI is to start small. With Einstein Bots, you can start by thinking about common student FAQ's and then build out communication journeys from there. It's all very easy and flexible to do.”
In the AI Master Class focused on Student Success, we learned how Einstein can help institutions leverage AI at scale. Starting small can help spark new ideas on how AI can be leveraged across the entire student lifecycle–from seamless automation with Einstein Bots to intelligent student recommendations with Einstein Next Best Action.
AI is making philanthropy more predictive and intelligent
As we heard in this webinar on what AI means for fundraising, AI is playing a bigger role in Higher Ed Philanthropy, enabling frontline fundraisers and advancement teams to be more productive. For advancement services and operations, AI means increasing the impact of the work your staff is already doing. By generating new insights into donor opportunities and building greater transparency into the pipeline, AI drives more accurate and predictive forecasting.
AI also means more efficiency in day to day tasks for gift officers by helping to better prioritize their time with the biggest donation opportunities that have the best chance of closing or recommending the next action to take based on historical donation history.
Be aware of data bias
Choosing technology that enables trust and transparency is just one part of leveraging AI for Good. We learned from this digital magazine on Demystifying AI in Higher Ed, that eliminating data bias is also key. But how can you start to identify potential biases across the student lifecycle? It starts with asking yourself these questions:
- WHERE is your data being sourced from?
- WHEN is your data coming in (i.e., freshness)?
- WHO are you getting data from or about?
- WHAT categories are being collected and used?
These are all important questions to explore when getting started with AI at your institution. Being aware of data bias is a key step in starting your AI journey–having these open dialogues on campus can put you on the path to transform your student data into intelligent actions at every step of the student lifecycle.
Begin your AI journey
As stated in the article, Artificial Intelligence: It's a Journey, Not a Destination, it's important to take the "crawl-walk-run" approach if you're looking to get started today. You can start simple with free online learning platforms such as Trailhead, which has interactive tutorials on AI basics and Salesforce Einstein. Make sure to also check out the list of resources and articles from Salesforce.org's AI for Good Week.