Addressing The Staff Morale Crisis In Admissions

When we look back on the last couple years in college admissions, the issue of staff morale will be one of the hallmarks of the post-pandemic era.  That's why I was excited to host this important conversation with Elizabeth Kirby about how - specifically - she was paying attention to this issue for her team.

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The full conversation is available on demand: https://www.crowdcast.io/c/morale

As admissions teams work through the challenges of identifying and engaging prospective students, the next step is figuring out how to approach each individual student. Many of the conversations around AI focus on its role in automating tasks, but one of its most exciting possibilities lies in helping human counselors make better, more informed decisions. Instead of scripting emails or pre-setting communication workflows, AI can act as a decision-support tool that guides counselors on the best way to reach each student.

The Human Touch Meets Data-Driven Insights

The key advantage of using AI in this context is its ability to blend data-driven insights with the counselor’s expertise and intuition. AI doesn’t replace human decision-making; it enhances it. For example, AI can analyze a student’s engagement data—such as how often they open emails, what content they interact with, and how quickly they respond to outreach—to provide counselors with insights on the student’s preferences, needs, and readiness to take the next step.

These insights give counselors a more complete understanding of each student’s profile, allowing them to make outreach more personalized and meaningful. Instead of guessing what message might resonate, counselors can be guided by the data, allowing them to focus on building authentic connections with students, which AI cannot replicate.

Personalizing Outreach for Maximum Impact

AI’s ability to help personalize outreach goes beyond generic recommendations like “send more emails” or “call at this time.” By analyzing behavioral patterns, AI can offer specific recommendations for each individual student, such as:

• Preferred Communication Channels: Some students might prefer email, while others are more likely to respond to text messages or phone calls. AI can analyze a student’s past interactions to suggest the most effective channel for outreach.
• Timing Recommendations: Based on a student’s activity history, AI can provide guidance on the best time to reach out. For example, if a student typically engages with your communications in the evening, AI can recommend sending a targeted message at that time for a higher likelihood of response.
• Tailored Messaging: AI can help counselors identify which topics are most likely to resonate with a particular student. If a student has shown significant interest in financial aid options or specific academic programs, the AI system can suggest focusing on those points in the next conversation.

Enhancing Counselor-Student Relationships

By acting as a decision-support tool, AI enables counselors to spend less time on administrative tasks and more time building relationships with students. Since AI handles the data analysis, counselors are freed up to focus on what they do best—listening to students, understanding their needs, and guiding them through the admissions process in a more personalized and empathetic way.

This approach also helps reduce the risk of “over-automation” in the admissions process. While automated emails and workflows can save time, they often lack the personal touch that students value in their interactions with an institution. With AI acting as a guide, counselors can strike the right balance between automation and human connection, ensuring that students feel seen, heard, and supported.

A Strategic Approach to Engagement

AI can also help admissions teams prioritize their efforts by identifying which students are most likely to benefit from personal outreach at a given time. For instance, if a student is showing signs of disengagement, AI can flag this and prompt a counselor to intervene with a more personalized message or offer additional support. On the flip side, students who are highly engaged and close to making a decision might benefit from a more direct conversation to help them finalize their plans.

AI as an Essential Partner for Admissions Counselors

AI’s role as a decision-support tool in admissions is one of its most powerful applications. Rather than replacing counselors or relying on generic automation, AI enhances the human touch by providing data-driven insights that lead to smarter, more effective outreach. By guiding counselors on how to communicate with students in a personalized and timely way, AI helps foster stronger connections and ultimately leads to better enrollment outcomes.

Next week, I’ll wrap up this series by looking ahead to how AI will continue to shape the future of admissions, combining human expertise with advanced technology for a truly transformative approach to student engagement.

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At NACAC, there was plenty of discussion around using AI to automate tasks, but few touched on AI's ability to track and predict where students are in their decision-making process. This is one of AI’s most powerful, yet underutilized, capabilities in admissions. Understanding what stage a student is at—whether they’re still exploring options, actively researching, or ready to apply—enables admissions teams to tailor their communications, making every interaction more meaningful.

The Challenge: Understanding Student Decision-Making

Admissions teams often rely on broad, linear models to track where students are in the funnel—prospect, inquiry, applicant, admit, and enrolled. While these categories are helpful, they don’t account for the complexity of individual student behavior. Some students may linger in the exploration phase for months, while others fast-track to applying after a single campus tour.

Knowing exactly where a student stands isn’t always clear with traditional methods. You might rely on surface-level cues—did they submit an inquiry form? Have they opened emails?—but these only provide part of the story. This is where AI can step in to give a clearer, more nuanced picture.

AI's Ability to Predict the Student Journey

AI excels at processing large amounts of data quickly and spotting patterns humans might miss. By analyzing behavior like how often a student visits your website, what pages they view, and when they open emails, AI can track subtle signals that indicate their progress through the decision-making process. AI models can even predict future behaviors, offering insights into where a student is headed and what kind of interaction they’ll need next.

Here are some ways AI can help map the student journey:

• Behavioral Analysis: AI looks at the frequency and nature of student interactions—such as visiting specific academic program pages or registering for events—to estimate how far along a student is in their journey.
• Predictive Staging: Based on past behaviors, AI can predict a student’s next steps. For example, if a student starts spending more time on financial aid or housing pages, AI might suggest they’re getting ready to make a decision, prompting your admissions team to send a personalized outreach.
• Engagement Milestones: AI helps track when students hit certain engagement milestones, like signing up for an info session or downloading an admissions brochure. These milestones help admissions teams know when it’s time to switch from general engagement to more specific, personalized communication.

Why Predicting Decision Stages Matters

Understanding where a student is in their journey allows admissions teams to deliver the right message at the right time. A student still exploring their options might need a broad overview of campus life, while a student deep into the decision phase might appreciate personalized insights into scholarships or financial aid opportunities.

Instead of bombarding every student with the same set of emails or phone calls, AI enables admissions teams to focus their efforts more strategically. This targeted approach can make the student experience feel more personal and relevant, which in turn increases the chances of them moving forward in the process.

A More Tailored Approach to Engagement

AI doesn't just help predict where students are—it also helps you communicate with them more effectively. A student in the early stages of exploration likely won’t respond well to an email asking them to apply now, but they might engage with content highlighting the academic programs or campus life they’re interested in. Conversely, a student nearing the end of their decision-making process will likely appreciate direct guidance on deadlines, financial aid, or next steps for enrollment.

By meeting students where they are, you’re not just improving your chances of conversion—you’re improving their experience with your institution. A more tailored, relevant approach to engagement shows students that you understand their needs and are there to support them throughout their journey.

AI and the Power of Predicting Student Behavior

AI’s ability to map and predict the student decision journey is a game-changer for admissions teams. By analyzing behavior patterns and engagement milestones, AI provides invaluable insights into how students are progressing through the funnel. This allows for more personalized and strategic communication, ultimately improving the chances of turning prospects into enrolled students.

Next week, I’ll explore how AI can help admissions teams craft the perfect approach for each individual student, providing guidance on the best way to engage based on their unique profile and preferences.

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