During the spring session of our Higher Education Summit, the Alliant Group discussed the significant shift in how institutions approach AI over the past 12 months, moving from wanting to learn about it to actively implementing solutions. They noted that institutions are now prioritizing specific AI applications rather than just studying the technology theoretically.
Two major advancements stand out in the current AI landscape:
- Enhanced reasoning capabilities: AI can now demonstrate its thinking process, showing its work and explaining how it arrived at answers. This has greatly improved trust in AI systems as they've evolved from "black boxes" into more transparent tools that cite sources and show their reasoning paths.
- Multimodal functionality: AI has become much more versatile, working with:
- Text and written content
- Numerical data and analytics
- Images and visual information
- Voice commands and audio processing
This increases AI's applicability across diverse educational settings from classrooms to administrative offices.
They're also witnessing an AI arms race among software companies, which is driving down costs and making more solutions affordable and accessible to educational institutions. Chris compared this to how Uber and Lyft's competition created a "race to value" that benefits universities by making previously expensive AI applications much more attainable.
Where Institutions Are Starting
Alliant Group's survey revealed that approximately half of the institutions have taken steps on their AI journey in the past year. The adoption is happening in several key areas:
- In the Classroom Experience
- Implementing AI tutors that complement professor instruction
- Creating guardrails for ethical AI use by students
- Designing AI assistants that guide learning rather than simply providing answers
- Using AI to process different content types (books, videos, notes) into unified learning resources
- Improving Campus Experience
- Developing chatbots that combine information from multiple university systems
- Connecting students to campus resources (like writing centers) more effectively
- Creating 24/7 information access for common student questions
- Streamlining navigation of complex university information systems
- Back Office Automation
- Scanning and reviewing applications more efficiently
- Enhancing finance functions through process automation
- Reducing administrative burden on staff to allow more focus on high-value activities
- Handling repeatable, transactional tasks to free up human resources
- Recruiting and Fundraising
- Using generative AI to write personalized communications based on recipient profiles
- Creating trigger-based outreach tied to events that matter to specific audiences
- Developing year-round campaign approaches rather than one-time mass mailings
- Customizing the experience for prospective students and donors based on their interests
Most Popular AI Application: The AI Tutor
The most consistently adopted solution has been the AI tutor, which allows professors to upload course materials (notes, books, videos) to create a 24/7 learning resource for students. Unlike public AI tools, these tutors don't just provide answers - they work through problems with students using the Socratic method.
Implementation is remarkably quick:
- 2-3 weeks for a pilot with individual professors
- 2-3 months for a scaled solution across multiple classes
- Once systems are connected, expansion can happen rapidly to any class that opts in
This specific approach differs from generic AI as it:
- Protects data and intellectual property: Course materials remain secure within the university's systems
- Uses only curated content: Only professor-approved materials are included
- Employs the Socratic method: Instead of giving answers, it asks questions to guide understanding
- Shows sources from course materials: Links back to specific pages or resources
- Can be customized by individual professors: Allowing different approaches for different subjects
These tutors also provide analytics to professors, showing:
- Which topics students are asking about most frequently
- Common areas of confusion or interest
- Patterns in student engagement with course materials
This allows instructors to adjust classroom time accordingly, focusing on areas where students need the most help.
Department Adoption Patterns
Their polling showed that adoption varies by department:
Academic Departments (Fastest Adopters)
- Professors want to ensure students use AI responsibly
- Faculty recognize students will use AI regardless, so they want to guide that use
- The Socratic approach ensures AI enhances learning rather than shortcuts it
- Early data shows students using these systems have improved test scores
Admissions (Second Wave)
- Using AI to answer prospective student questions
- Automating parts of the application review process
- Creating personalized communications for different prospective student segments
- Leveraging AI as a recruiting advantage to demonstrate technological advancement
Administrative Departments (Third Wave)
- Implementing automation for repetitive processes
- Using AI to improve efficiency in financial operations
- Enhancing document processing and management
- Supporting operational functions with limited staffing
Fundraising (Emerging Area)
- Creating personalized donor communications based on interests and giving history
- Timing outreach to coincide with events donors care about
- Developing more sophisticated, year-round engagement strategies
- Analyzing giving patterns to optimize fundraising approaches
Future Directions
Looking ahead, Chris expects to see 75-80% of institutions implement some form of AI within the next 12 months. Most solutions will involve generative AI, with automation following as the second most common application.
He also thinks we're likely to see the emergence of "agentic AI" - systems that not only provide information but can take actions based on that information. For example:
- A recruiting agent could automatically send tailored materials to prospective students based on their specific interests
- A student support agent could not just answer questions about the writing center but schedule appointments
- A fundraising agent could generate personalized communications and send them at optimal times
- A campus service agent could help students navigate multiple university systems more seamlessly
The distinction is significant - chatbots provide information, while agents can execute tasks based on that information. This represents the next evolution in AI functionality for higher education.
Recommendations for Institutions
If you're considering implementing AI at your institution:
- Start Somewhere
- Pick one idea and try it, even if small
- Begin with a pilot in an area where there's already faculty or staff interest
- Don't wait for perfect solutions - today's technology is already viable
- Learn by doing rather than theorizing
- Listen to Your Students
- They're already using AI and will need these skills in their careers
- Meet them where they are with responsible AI solutions
- Use AI to enhance their learning experience, not just restrict it
- Prepare them for a workplace where AI literacy will be essential
- Don't Limit Ideas to One Department
- Allow experimentation across the institution
- Share successes between departments
- Recognize that cross-university solutions will ultimately be most powerful
- Plant seeds throughout the organization to foster innovation everywhere
Notable Success Story
Bryant University, which implemented one of the first AI tutors, was recently named a CIO 100 winner - a significant technology award recognizing substantial industry change. This places them alongside major corporations like Microsoft and Accenture, validating that AI is making a meaningful impact in higher education.
This recognition demonstrates that:
- Higher education can be at the forefront of AI innovation
- Scaling AI solutions across an institution is now possible
- Student-focused AI applications are gaining industry recognition
- The technology has matured from experimental to production-ready
The rapid evolution of AI in higher education presents both challenges and opportunities. By starting with purposeful implementations that enhance rather than replace human teaching, institutions can improve student outcomes while preparing them for a workforce where AI literacy will be essential.