5 AI Features to Support Your Campus Better in the New Semester

Why New AI Features Matter Today (This New Semester)

Every new academic year brings pressure: enrollment targets, faculty workloads, student onboarding, and retention goals. For many institutions, AI has shifted from experimental pilots to mission-critical infrastructure.

Many AI tools used by students today are outside of the institutional environment, making it difficult for students to access accurate information, high chances of AI hallucinations, and privacy and safety concerns. At this pivotal point, the question isn’t “should we adopt AI?” anymore. It’s “how do we deploy it responsibly and quickly enough to make an impact this semester?”

Luckily, today's AI solutions are not generic copilots bolted onto workflows. They’re LMS-native, role-aware, and institution-governed. That means they slot into existing teaching and support systems while respecting the guardrails of academic integrity, privacy, and equity.

1. Multilingual AI Support Assistants: Equity at Scale

Imagine being a first-year student with urgent questions about housing, timetables, or ID cards. For many, support bottlenecks in the first weeks of term mean long waits, unanswered emails, and mounting stress. International and commuter students often feel this most acutely, since small barriers can quickly snowball into disengagement.

The University of Gloucestershire tackled this challenge by introducing an AI-powered support assistant across its student services. The system provided instant, accurate responses to high-volume questions, available 24/7 and deeply integrated with institutional knowledge bases. Within the first term, support services saw significant reductions in Tier-1 inquiries and freed staff capacity to focus on complex, high-touch student needs.

For students, the difference was palpable: faster answers, less confusion, and more equitable access to support. For staff, it wasn’t about replacing the human connection: it was about reclaiming time and bandwidth to engage where empathy and nuance mattered most.

2. Streamlined Induction and Onboarding with AI

Every September, universities brace for the wave of questions that come with new student induction. From “Where do I pick up my ID card?” to “What’s the deadline for registering for financial aid?” The first two weeks can overwhelm both support teams and students. International students in particular often face multiple hurdles, from navigating enrollment, induction registration, and settling into a new culture, all at once.

One way to tackle this challenge is deploying AI-powered support at the start of term. Features such as flows allow AI assistants to design precise pathways for common questions, ensuring students receive the right type of support without long delays. Routine questions about induction weeks are answered instantly, while financial aid queries can trigger a tailored step-by-step flow to guide students through forms and deadlines. More complex cases are seamlessly escalated to student services staff.

The result: students feel supported at every turn, and staff can focus their energy on the situations where human empathy and expertise matter most. For international students, this translates into faster clarity during a stressful transition (see how we support international students). For first-years, it meant a seamless induction experience with fewer missed deadlines or gaps in information. And for administrators, it simplifies one of the thorniest challenges in higher ed, navigating financial aid with accuracy and confidence.

3. AI-Powered Analytics Dashboards: From Data to Action

Every support request, LMS query, and feedback cycle generates data. But with fragmented sources, conflicting information, or gaps in data, the path to clarity is difficult - leaving stakeholders with unanswered questions. AI-powered analytics transform assistant interactions with students, faculty, and staff into insights that directly improve the experience.

LearnWise AI analytics report on a wide range of insights: support analytics for helpdesks such as ticket volume, resolution rates, response times, escalation trends, common support topics, tutor analytics for faculty such as student engagement metrics, topic-specific struggle identification, usage patterns, content effectiveness, and institutional metrics such as feedback trends, assessment analytics, student satisfaction, systemic support and learning insights.

Institutions use AI-powered analytics to uncover friction points across the full student lifecycle:

• Onboarding: Highlighting where new students get stuck during orientation, with reading materials, or meeting registration deadlines.
• Course Setup & Delivery: Spotting gaps in gradebook setup, compliance workflows, or assignment instructions before they escalate.
• Course Content: Course content query patterns, helping educators see conversations, trends, and feedback to make ongoing improvements, refining course delivery, and strengthening engagement.
• Engagement & Retention: Detecting at-risk students early by tracking patterns of disengagement and surfacing which content drives participation.
• Campus Life & Administration: Streamlining high-volume tasks like financial aid queries, housing requests, and timetable changes by showing where students most often hit barriers.

4. AI Student Tutor: Context-Aware Learning Support

Generic AI chatbots may help with general knowledge, but higher education requires course-aware tutors. These AI tools ingest syllabi, lecture materials, and approved institutional content, then generate practice quizzes, explanations, and study guides aligned to the curriculum - all within an institution’s LMS, with no additional workflows or credentials. 

At the beginning of the school year, syllabus information can feel overwhelming for students, who take multiple classes at the same time. Keeping track of each class requirement and making the right study plans is key for a smooth start to their learning journeys, and ensuring a low barrier to information is essential. AI tools like LearnWise are placed where learners are studying and interacting with existing course material - and teachers are evaluating assignments and other submissions - ensuring ease in adoption.

At the University of Westminster, the AI Student Tutor inside Blackboard not only answered student questions but also generated quizzes that improved study habits, integrating fully with open-source content tools like H5P. Used for creating interactive content such as presentations, videos, quizzes and surveys, educational games and branching scenarios for personalized learning, H5P integrations make AI tools like Student Tutor much easier to adopt. Upon usage of, faculty discovered unexpected insights into how students were engaging with course material, shaping better instructional strategies. 

For students, the difference is confidence: no more floundering alone on problem sets or turning to unreliable internet sources. The tutor sits inside their LMS/VLE, available 24/7, with faculty oversight ensuring quality.

5. Connecting the dots: Understanding the student journey with AI

One of the biggest challenges for students isn’t mastering a single class, but managing the complexity of all their courses at once. Deadlines overlap, policies differ, and concepts often connect in ways that aren’t obvious at first glance. AI can help students cut through that noise by serving as an organizer, coach, and connector across their entire learning journey. A student might ask the assistant to build a weekly plan that balances due dates across Calculus, Physics, and English, or to flag when multiple assignments bunch together. They could compare late-submission policies across courses to avoid penalties, or get guided advice on which courses to take next semester to stay on track for graduation. 

Beyond logistics, AI can bridge knowledge across disciplines, like linking the chain rule from Calculus to kinematics in Physics, or suggest which readings to revisit before tackling a new unit. It can even synthesize resources, eliminate duplicate materials, and map assignments into career-ready portfolios. By weaving together the strands of a student’s full workload, AI transforms fragmented course experiences into a coherent path, helping learners stay organized, deepen their understanding, and progress with confidence.

Here’s a few other cases where cross-course support can help student engagement:

• Navigate policies and exceptions by comparing grading or late-submission rules across different courses, saving time and reducing confusion.
• Make smarter enrollment choices by mapping current progress to future degree requirements, ensuring the next semester’s courses keep them on track.
• Build stronger study plans with interleaved practice that pulls from multiple courses, targeting weak spots with exercises that reinforce ideas in different contexts.
• Simplify campus life by synthesizing overlapping resources (e.g., multiple citation guides), centralizing navigation (like Zoom links across courses), and even curating assignment portfolios for career development.

Governance That Keeps AI Applications Responsible

Speed and scale matter, but governance still defines success. Each of these features comes with built-in controls: system prompt editing, role-based behavior, approved content sources only, and full audit logs. Students and faculty trust AI when they know who controls it, what data it uses, and how it can be corrected.

From Features to Impact

These five features aren’t futuristic add-ons: they’re available now, and institutions are proving their value in the first term of deployment. Together, they free staff from repetitive tasks, give students confidence in their learning, and help leadership teams steer with better data.

Want to see them in action?

Read the full guide: AI Readiness for Fall 2025

Book a 30-minute consult with our team