Institutional strategy
What is the school trying to build?
Leadership needs a clear view of the capability that matters, the current level of implementation, and the sequence of work that deserves attention first.
RB
Dr. Ryan Baltrip
Clinical Assistant Professor of Marketing · Executive Director, Loyalty Science Lab · Founder, Navigate AI
Academic leaderDigital-learning executiveBusiness-school facultyAI researcher
About Navigate AI
An independent perspective shaped by both institutional leadership and the work of teaching.
Navigate AI was founded by Dr. Ryan Baltrip to help business schools answer a practical question: what AI capability has the school actually built, and what evidence can leadership use to support that claim? The work draws on a career that spans university-wide digital-learning strategy, academic administration, business-program leadership, faculty development, course design, teaching, assessment, and applied AI research.
Why the background matters
AI strategy becomes meaningful when it survives the trip from leadership priorities to student work.
Business-school AI decisions cross several levels at once. A dean may be deciding how AI fits the school's strategy. A curriculum committee has to translate that direction into program expectations. Faculty need course-level practices that make sense in their disciplines. Assessment leaders still have to determine whether the resulting student work provides credible evidence of learning.
Ryan's professional path has moved through each of those levels. He has led institution-level online and digital-learning strategy, served as a dean and business chair, designed faculty-development systems, worked directly on course and program design, and now teaches and conducts AI research inside a business-school context.
That combination shapes Navigate AI's approach. The work begins with institutional questions, then follows them far enough into curriculum, courses, assessment, and evidence to determine whether the pieces actually connect.
Leadership across the academic system
A career built around making strategy operational.
The through-line has been academic change: building programs, supporting faculty, improving digital learning, and creating structures that make new initiatives sustainable after the launch.
2023–present
Old Dominion University: business-school teaching, research, and applied AI work
Ryan serves as a Clinical Assistant Professor of Marketing and Executive Director of the Loyalty Science Lab in the Strome College of Business. His teaching has included AI in Business, Strategic AI Leadership, AI in Digital Marketing, Principles of Marketing, and Consumer Behavior. He has also served as an AI Teaching Fellow and received the Strome College of Business Outstanding Faculty Teaching Award in 2025.
His current research examines student AI readiness, verification, trust, privacy, disclosure, human oversight, and the design of evidence-rich learning in AI-enabled courses.
2021–2023
Carson-Newman University: dean, business chair, and program builder
As Dean of the College of Professional Studies, Chair of Business Administration, and a management and marketing faculty member, Ryan led academic strategy across programming, enrollment, student success, operations, and market development. He directed business programs including the MBA and BBA and led redesign work intended to strengthen academic quality, market differentiation, and online delivery.
The role provided the leadership perspective that now informs Navigate AI's institutional work: new ideas have to fit budgets, faculty capacity, program structures, student needs, and the decision processes of a university.
2018–2021
Miami University: university-wide digital-learning strategy
As Director of Digital Learning Initiatives, Ryan led online, hybrid, and innovative-learning efforts across the university. He authored a multi-year digital-learning strategy, worked across academic colleges and administrative units, expanded graduate and undergraduate offerings, and developed structures for faculty and program support.
The work required coordinating institutional priorities across business, engineering, health, education, graduate education, and other areas while building processes that could scale beyond a single enthusiastic program.
2018
University of Cincinnati, Lindner College of Business: faculty and online-MBA design
As a Senior Instructional Designer, Ryan helped the college strengthen faculty training and its online MBA while consulting on executive-education program planning. The role added direct experience with the operating realities of a large business school and the relationship between course quality, faculty support, and program strategy.
2016–2018
William & Mary: online-program strategy and expansion
As Director of Online Programming, Ryan led university-wide planning for online and distance education, supported graduate program development across schools, and helped expand online learning in business, law, education, and the undergraduate college. His team was recognized in consecutive years among leading eLearning organizations for operational effectiveness.
2012–2016
Southern Seminary: online-learning operations, faculty development, and growth
As Director of Online Learning, Ryan led a large online program, built faculty training, expanded blended and distance offerings, and strengthened the infrastructure supporting course design and delivery. Earlier instructional-design work at St. Petersburg College helped establish the course-level foundation for later leadership roles.
The perspective behind Navigate AI
Four parts of the work have to stay connected.
Navigate AI is designed around the places where institutional AI efforts can become disconnected. The methods keep leadership direction, teaching practice, assessment evidence, and continuous improvement in the same conversation.
Curriculum & teaching
Where does the capability become real?
Program maps, course expectations, faculty practices, and assignments determine whether an institutional goal becomes part of the student experience.
Assessment & evidence
What shows that students can actually do it?
Direct measures, process evidence, verification artifacts, and defensible scoring make the learning claim more credible when AI participates in the work.
Improvement
What changes after the evidence is reviewed?
A quality system becomes useful when findings lead to a decision, ownership, implementation, and a later opportunity to see whether the change worked.
Teaching and research now
The current work keeps Navigate AI grounded in the same questions clients are facing.
Ryan's teaching places him directly in the changing environment Navigate AI is designed to address. Students use increasingly capable tools for research, analysis, writing, ideation, and multi-step work. The challenge for faculty is deciding what students should still be able to explain, verify, defend, and do independently enough to support professional judgment.
His research program examines those transfer problems empirically. Recent work has studied the gap between belief in human review and supervision readiness, the translation of disclosure knowledge into actual practice, trust and privacy in AI adoption, confidence versus demonstrated proficiency, and the emerging challenge of human oversight in agentic workflows.
That research informs Navigate AI's emphasis on observable capability and evidence. It does not substitute for institutional validation of the products. Diagnostic validation, client outcomes, and external evidence are treated as separate questions and will be reported as those data develop.
A record of digital-learning leadership
The AI work builds on more than a decade of academic technology and faculty-development experience.
Before generative AI became a business-school priority, Ryan's work centered on many of the same implementation challenges: translating emerging technology into sustainable academic practice, supporting faculty through change, and preserving learning quality while programs evolve.
Institutional planningAuthored and led multi-year strategies for online and digital learning across university settings.
Program developmentHelped launch, redesign, and scale graduate, undergraduate, professional, online, hybrid, and alternative-credential programs.
Faculty capabilityBuilt faculty-development structures and supported instructors through course and program change.
Learning qualityWorked across instructional design, learning media, accessibility, student support, and academic leadership rather than treating technology as a stand-alone implementation.
Mission
Help business schools build AI capability they can see, assess, and improve.
Navigate AI supports schools as they define student capability, strengthen course and assessment practice, organize evidence, and make the next improvement decision with greater confidence.
Vision
Business graduates who can use AI productively and still stand behind the work.
The long-term goal is a form of Human+AI capability in which students can create value with advanced tools while retaining judgment, verification, transparency, responsibility, and professional accountability.
Independent by design
Navigate AI separates the evidence review from the organizations and institutions being referenced.
Navigate AI operates as an independent business. Ryan's university roles provide professional experience and inform the work, while those institutions do not endorse or sponsor Navigate AI unless a separate relationship is explicitly stated.
The same principle applies to AACSB. Navigate AI uses current standards as one quality context for business schools and can help organize evidence relevant to those expectations. Accreditation interpretation and decisions remain with AACSB, its accreditation managers, and peer review teams.
Independence is useful because the Diagnostic is intended to provide a neutral baseline of what the available evidence supports. The goal is to give leadership a clearer view before the findings become part of curriculum planning, board communication, quality review, or accreditation preparation.
A practical conversation
Bring the institutional question you are trying to answer.
A briefing can begin with student capability, assessment evidence, course quality, faculty support, or a broader institutional baseline. The first step is identifying where better evidence would improve the decision.