Excellence in Student Success: 6 Key Lessons from Our Summer Webinar Series & 3 Years of Research

Students experience college as one connected journey.

Institutions, however, often support that journey through separate offices, systems, processes, and priorities.

A student may begin with a question about dual credit enrollment, move through admissions, select a major, meet with an advisor, explore career pathways, and prepare for the workforce. To the student, these moments are connected. However, the teams responsible for supporting students are frequently asked to operate with limited support.

Despite carrying most of the responsibility for student success, enrollment professionals, advisors, career services teams, retention specialists, and student support staff are often among the most under-resourced functions on campus. They are expected to deliver personalized support at scale while navigating fragmented data, manual processes, and technology ecosystems that were not designed to support today's learners and rising institutional expectations.

That challenge has informed our research since 2023 and served as the foundation for our Excellence in Student Success Webinar Series, held from April 23 through June 25, 2026.

Across nine sessions this summer, more than 700 higher education professionals representing over 100 colleges and universities joined conversations on enrollment, advising, career services, workforce readiness, and responsible AI. While the topics varied, a common reality emerged: most institutions do not suffer from a lack of effort to support student success. They struggle with the infrastructure and coordination required to deliver that support consistently at scale.

As Advisor AI Founder & CEO, Arjun Arora, shared during the series:

"Delivering a high-quality solution for student success requires alignment across three core areas: empowering people, defining clear implementation processes, and designing simple, usable tools. We cannot build strategies around technology alone or treat it as a magic wand. Real progress comes from an iterative approach that continually integrates people, process, and technology."

That observation reflects more than three years of field research, institutional partnerships, and implementation work with colleges nationwide. The institutions making the greatest progress are not necessarily those with the largest budgets or the most tools. They are the institutions finding ways to better support the people already doing great work.

Moreover, the webinar series reinforced a consistent finding: student success challenges are often less about student motivation and more about resource complexity. Students frequently encounter fragmented information, disconnected resources, unclear pathways, and support structures that can be difficult to navigate. At the same time, staff members often lack the visibility, time, and tools needed to proactively support students at scale.

The six insights that emerged from this series reflect what leading institutions are implementing across the nation as they work to address rising accountability standards and institutional mandates. Together, they offer a practical perspective on how colleges can strengthen student success infrastructure, empower frontline teams, and create more connected experiences from exploration and enrollment through graduation and career success.

1. Early Exploration Reduces Friction Across the Student Journey

Across the research, one finding surfaced repeatedly: institutions are achieving stronger student engagement and decision-making when exploration begins earlier in the student journey.

Too often, career exploration is introduced only after students have already made several important decisions. By that point, students may have selected dual enrollment courses, applied to institutions, declared a major, or completed significant coursework without fully understanding how those decisions connect to long-term goals.

Leaders participating in the series described a common challenge. Students frequently arrive in advising, career services, or first-year programs looking for answers to questions they were never given an opportunity to explore earlier. As a result, teams often find themselves helping students reconsider decisions that might have benefited from earlier guidance and context.

This theme emerged consistently across sessions focused on dual enrollment, direct admissions, and first-year persistence. Institutions are increasingly recognizing that helping students build clarity before enrollment is often more effective than trying to restore confidence after uncertainty has already developed.

During the dual enrollment conversation, student success expert Dr. Jeff Doyle and Advisor AI Founder Arjun Arora discussed the significant variation in student access to exploration and guidance across the country. While some students benefit from strong advising relationships, clear pathway information, and coordinated support, others receive limited exposure to available programs, career opportunities, or the implications of their academic choices.

Institutional leaders also highlighted an important reality: offering access is not the same as providing clarity. Students and families need support understanding how courses connect to credentials, how credentials connect to programs, and how programs connect to future opportunities.

The direct admissions discussion reinforced a similar lesson. An admission offer communicates that a student is eligible to attend an institution. It does not automatically help them understand why a particular pathway may be a good fit, what opportunities are available, or how their interests align with future academic and career possibilities.

The institutions making progress in this area are connecting exploration throughout the student lifecycle, from recruitment through onboarding, advising, and career services. Rather than treating exploration as a one-time activity, they are embedding it into the broader student experience.

The lesson from the field is clear: students make stronger decisions when they can see the connection between interests, programs, skills, and careers before critical choices are made.

2. Technology Creates More Value When It Strengthens Human Advising

.Another consistent finding across the series was the importance of understanding the true nature of advising work.

Discussions about automation frequently focus on tasks that are visible and measurable: course selection, policy questions, referrals, graduation requirements, appointment scheduling, and information retrieval. Yet all advisors know that the real work extends far beyond those transactions.

Across multiple sessions, advising leaders emphasized that many student challenges reveal themselves only through conversation. What begins as a question about a class schedule may uncover financial stress, uncertainty about a major, family obligations, a lack of belonging, or concerns about future career opportunities.

This distinction shaped many of the discussions around responsible AI implementation.

Enrollment expert Michael Griffin and Arjun Arora highlighted a principle that appeared repeatedly throughout the research: technology can streamline transactional work, but people remain responsible for transformational work.

Institutions are already finding practical ways for AI to support advising teams. Teams are implementing AI technology to help students access information outside office hours, prepare for appointments, identify relevant resources, understand institutional processes, and receive guidance between meetings. And advising teams are benefiting from richer context, summarized student activity, and improved visibility into engagement patterns over time.

At Central New Mexico Community College (CNM), Executive Director of Student Persistence and Completion Brian Sailer described the institution's approach:

"We're using this as more of an exploratory tool, pointing the student in the direction they would like to go, and then we step in with the human side of things."

That philosophy reflects what many institutions are learning through implementation. The goal is not to replace advising relationships. The goal is to reduce administrative friction, improve access to information, and create more capacity for meaningful student interactions.

The right questions is: "How can technology help advisors spend more time doing the transformational work?"

3. Connected Support Makes Existing Resources More Effective

A third insight from the series was that most institutions already have many of the resources students need.

They have advising offices, career centers, tutoring programs, financial aid teams, academic departments, transfer services, success coaching, wellness support, employer relationships, and workforce programming. The opportunity is not always to create more resources. In many cases, the opportunity is to help students find the right resource at the right time, and to help teams coordinate around what the student has already explored, completed, or expressed.

This theme surfaced strongly in the conversations on career ecosystems and case management sessions.

From the student perspective, institutional support is most useful when it feels connected. A student exploring business, marketing, and entrepreneurship careers may need academic advising, career guidance, internship support, financial planning, and encouragement from more than one office. If each team has a clearer view of where the student is in that journey, the support can become more timely and more relevant.

From the staff perspective, connected support can reduce the amount of time spent reconstructing context. Advisors and career professionals often begin conversations by trying to understand what the student has already done, what information they have received, what they are considering, and what still feels unclear. Better visibility helps those conversations begin in a more useful place.

In the career ecosystem conversation, Arjun Arora and career services expert Kim Sprought discussed several conditions that support a stronger experience: secure and governed systems, connections between student interests and programs, personalized next steps, coordinated visibility across teams, and earlier insight into student progress.

Each condition becomes more valuable when it is connected to the others.

• A career assessment is more useful when it informs an advising conversation.

• Labor market information is more meaningful when a student has support interpreting it.

• A referral is more effective when the next professional has enough context to continue the conversation.

• A resource recommendation is stronger when it connects to what the student is actually trying to decide.

Case management offers a similar lesson. The value is not only in tracking activity. The value is in helping teams understand the student’s movement across the institution, so support can be better coordinated over time.

For students, that can mean fewer moments of starting over. For advisors and career professionals, it can mean more focused conversations. For leaders, it can mean better visibility into patterns that are difficult to see when information remains separated across systems and offices.

As Kim Sprought shared during the series: “Our leaders are being asked not to just help students find jobs anymore. We’re being asked to help our institution create a much broader story about student success, workforce relevance, and the value of having a college degree.”

That broader story becomes easier to support when students experience the institution as a connected pathway rather than a collection of separate services.

4. Earlier Signals Help Support Students While Decisions Are Still Unfolding

Most institutional effectiveness outcomes get measured only after they occur: Retention, completion, graduation, transfer, employment, and enrollment. They help institutions understand progress and communicate impact.

However, the research also highlights the need for seeing student movement earlier, while there is still time to adapt. This does not mean reducing students to data points. It means giving staff better visibility into where students may be gaining momentum, where they may be pausing, and where a timely conversation could be useful earlier on.

• Has the student begun exploring academic or career options?
• Did they complete the next recommended pathway activity?
• Did they receive a referral and connect with the office in the last 90 days?
• Are they engaging in one area but missing another resource that could support their next step?

These signals are not substitutes for professional judgment. They help professionals apply judgment sooner.

A student who explores several career pathways but does not take a next step may not need an intervention in the traditional sense. They may need a better question. An advisor might begin by asking, “What did you notice as you looked through those options?” or “Which pathway felt most connected to what you want next?” That kind of context can change the quality of a conversation and the student's next step.

Brian Sailer described the practical value of better context: “It’s going to provide for richer discussions. We’re going to have a better idea of what the student wants, and we can better direct them along a meaningful path.”

This is especially important for teams managing large caseloads and have limited time. When staff have earlier insight into student interests, activity, and next steps, they can focus their attention more intentionally. Outreach can become more specific. Appointments can become more prepared. And referrals can become more relevant and timely.

Good use is not simply logging into a platform. Good use means the work becomes more timely and connected.

5. Responsible AI Requires Purpose, Trust, and Clear Ownership

The responsible AI sessions moved the conversation beyond what a system should do and towards implementing it.

The team from Central New Mexico Community College and Ivy Tech Community College provided a practical example of an institution approaching AI with purpose. Brian Sailer summarized the responsibility this way: “The question isn’t whether to adopt technology. It’s how to do so responsibly, transparently, and in service of students.” The five-stage model discussed in the session included exploration, governance, pilot, evaluation, and iteration.

The main lesson: A strong process begins with the institutional need first. Where are students encountering friction? Which decisions require human involvement? What information will the system use? Who is accountable for the student experience? How will staff understand the tool? How will students know what the tool does and does not do?

And a focused pilot gives institutions space to learn before expanding. It also protects staff capacity by allowing teams to identify where AI creates practical value before asking people to absorb a broad change management initiative.

Emery Peck from Ivy Tech also shared that the institution gained traction only after narrowing its focus: “By casting a wider net, we didn’t really have a clear focus. We had to narrow the scope down ... and once we did, momentum began.”

Thus, the goal is not to prove that AI can be used in every part of the student journey. The goal is to identify where it can improve a meaningful part of that journey and expand responsibly from there onwards.

6. Build-or-Buy Decisions Are Really Capacity and Sustainability Decisions

The final session addressed a question many institutions are beginning to ask:

Should we build an internal AI system, adapt a general-purpose tool, or partner with a specialized external platform?

It is easy to begin that conversation with cost, features, and speed. Those questions matter. But for student success work, they are not the only questions. Institutions also have to consider capacity, governance, workflow adoption, student trust, integration, maintenance, and long-term program sustainability.

Moreover, the question is not only whether an institution can build something. It is whether the institution can sustain the context, training, documentation, governance, and ongoing improvement required after launch. An internally developed solution may offer customization and control, especially for institutions with strong technical capacity. A general-purpose tool may offer flexibility and broad access. A specialized external platform may offer domain-specific structure, implementation support, and a model designed around student success workflows. Each path has value.

But for student success work, the quality of the partnership matters more. Institutions need technology that understands the complexity of advising, career development, enrollment, responsible AI, and frontline staff capacity. They also need partners who are clear about both what the technology can do and what should remain human-led.

Emery Peck contrasted Advisor AI’s approach with vendors that promise their platform can solve every problem: “That’s not the approach we have here. We know what it will do, and we know what it won’t do. That’s the big difference.”

That kind of clarity matters more than a long feature list. A tool that supports student success must be trusted by leaders, understood by staff, useful to students, and sustainable beyond the initial launch.

Technology must fit the work of teams and institutions, not the other way around.

What institutions can carry forward

The summer webinar series and implementation case studies did not point to one single solution, structure, or timeline. It revealed a consistent set of priorities for institutions working to strengthen and transform student success.

• Students make stronger decisions when exploration begins earlier.
• Advisors and student support professionals can do more meaningful work when technology improves context, reduces friction, and protects the human relationship.
• Existing resources become more effective when they are connected across the student journey.
• Earlier signals can help teams support students while decisions are still unfolding.
• Responsible AI requires clear purpose, transparent implementation, and institutional ownership.
• Build-or-buy decisions require leaders to consider not only what a system can do, but whether the institution can sustain the trust, capacity, and partnership required over time.

Taken together, these lessons point toward a more connected model of student success.

Additional Resources:

• Four Insights Redefining Student Advising Across Campuses Nationwide
• From Strategy to Implementation: Five Requirements for a High-Quality Tech-Enabled Career Ecosystem
• The Benefits of a Case Management Approach to Improving Completion and Workforce Readiness
• A Five-Step Model for Implementing Responsible AI in Higher Education