Student Retention: Using AI to Spot Disengagement Before Dropout

At Manhattan University, the case for the liberal arts is being made with outcomes, not nostalgia. Its graduates rank in the top 2% nationally for mid-career salaries, and The Wall Street Journal ranked the university 73rd in the country for graduate salaries, social mobility, and cost-effectiveness. The more useful story for institutional leaders sits underneath those numbers: a set of deliberate decisions about program design, technology preparation, faculty adoption, hiring, and alumni engagement. In this episode of the Changing Higher Ed® podcast, Dr. Drumm McNaughton speaks with Dr. Fred Bonato, President of Manhattan University, about how the institution pairs a liberal arts core with universal technology preparation, on the premise that transferable skills hold even greater value when combined with technical fluency. Bonato explains how Manhattan houses its interdisciplinary programs in AI, cybersecurity, and data science outside any single college under the new ARCH Innovation Exchange; requires every first-year student to earn an IBM SkillsBuild digital badge in AI; funds faculty adoption through an institutional ChatGPT license, workshops, and peer champions rather than mandates; screens faculty and staff hires for comfort with AI as a tool; and treats the university's alumni network as employment infrastructure, including the James Patterson-funded leadership development honors program. This conversation is especially relevant for presidents, provosts, and board members weighing humanities cuts, planning AI integration, or looking for adoption strategies that work within shared governance rather than around it. Topics Covered •       Why Bonato defines the liberal arts by their transferable skills: problem-solving, creative thinking, and persuasive writing and speaking •       Housing interdisciplinary programs in AI, cybersecurity, and data science outside any single college to reduce the likelihood of ownership disputes •       The ARCH Innovation Exchange (analytics, research, creativity, humanity) and its speaker series open to the surrounding community •       The required IBM SkillsBuild AI course and digital badge for first-year students •       Driving faculty adoption through demonstrated value, resources, and peer champions instead of presidential mandates •       How hiring questions have shifted from comfort with online teaching to comfort with AI, for faculty and staff alike •       Experiential learning, intern-to-hire pipelines, and the alumni network's role in supplying opportunities Real-World Examples Discussed •       ARCH's inaugural speaker, a cardiologist and Manhattan engineering alumnus who leads AI at his hospital, framing AI as decision support with a human in the loop •       An institutional ChatGPT license and training workshops so faculty and staff can adopt AI at no personal cost •       The James Patterson Honors Program, a leadership development program seeded by the best-selling alumnus, which launched with more than 160 students •       Board chair and American Express CEO Steve Squeri speaking directly with students about building a career Three Key Takeaways for Higher Education Leaders 1.     Keep the liberal arts in every program, including technical ones; graduates without them are less prepared and less well-rounded for the working world 2.     Build the capacity to pivot; the world is changing quickly, and "this is how we've always done it" will no longer hold 3.     Presidents need a deliberate way to disengage and recharge, even if only through adequate sleep; the job can consume its holder This episode offers a practical look at how one institution operationalizes the pairing of liberal arts and workforce readiness through governance, partnerships, hiring, and culture, without waiting for the technology or the sector to stabilize. Read the transcript: https://changinghighered.com/manhattan-university-liberal-arts-workforce-readiness/   #LiberalArts #WorkforceReadiness #HigherEducation #HigherEducationPodcast

Most retention systems flag struggling students through grades and attendance. By the time those indicators fire, many students are already halfway out the door. Elvee's survey of 1,050 U.S. college students shows why: 86% start college highly motivated, 42% come close to dropping out at some point, and only 17% of those who struggle ever request help. In this episode of the Changing Higher Ed® podcast, Dr. Drumm McNaughton speaks with Raz Dar, CEO of Elvee, whose work with U.S. colleges centers on reading behavioral data for early signals of student disengagement. Drawing on his background in commercial technology, Dar explains how patterns in study time, login frequency, and forum participation reveal disengagement before exam period and before failure reaches the gradebook. He and McNaughton examine why motivated students still leave, why institutions that wait for students to ask for help miss most of the students who need it, and why intervention without follow-up monitoring routinely fails. This conversation is especially relevant for presidents, provosts, student success executives, enrollment executives, and board members looking to move retention from reactive support to proactive, early intervention. Topics Covered Why grades and attendance are lagging indicators that flag students too late What disengagement looks like in behavioral data, and why a single dip can be benign The help-seeking gap: 17% ask for help, 52% try to solve it alone first, 30% never reach out The top dropout drivers: balancing work and school (72%) and mental health or stress (71%) How the most successful institutions build a personalized bond from day one Scaling a dozen advisors across thousands of students through prioritization and automation Real-World Examples Discussed A freshman who skipped two exams under acute stress and recovered because the institution initiated contact Institutions that call students at term start to confirm they have books, Wi-Fi, and a computer Cambridge's bridge week for first-generation students and Yale's required freshman life-skills course The corporate benchmark: turnover above 10% triggers alarm in business, while higher ed absorbs far worse Three Key Takeaways for Leadership Build trust with students before they struggle; outreach in crisis only lands if a relationship already exists. Move from reactive to proactive; only 17% of struggling students will ask for help, so use behavioral signals to know when to reach out and monitor afterward to confirm the intervention worked. Make retention a strategic, measurable KPI from the top, and resource it with a real team. This episode offers a practical look at what becomes possible when institutions stop waiting for students to raise their hands and start reading the signals students are already sending. Read the transcript: https://changinghighered.com/using-ai-behavioral-signals-student-retention/ #StudentSuccess #StudentRetention #HigherEducation #HigherEducationPodcast #AIforStudentRetention

Half of college presidents worried about public trust are answering with a public relations campaign. According to the AAC&U report at the center of this episode, that is a reasonable instinct but the wrong one. Public confidence in colleges and universities has slid for more than a decade, and messaging alone will not turn it around. In this episode of the Changing Higher Ed® podcast, Dr. Drumm McNaughton speaks with Dr. Jeremy Young, lead author of The Trust Agenda: A Framework for Advancing Public Trust in Higher Education and he co-directs AAC&U's Advancing Public Trust in Higher Education initiative, about why trust has eroded and what campus leaders can actually do about it. Their conversation moves past naming the crisis, which presidents and boards already feel, into the specifics: why the most prestigious institutions are the least trusted while community colleges and regional publics are the most, why distrust took root long before today's politics, and how the report's five recommendations translate into work a campus can start now. This conversation is especially relevant for presidents, provosts, board members, and cabinet leaders weighing how to respond to declining confidence without defaulting to a PR campaign. Topics Covered Why public trust has fallen unevenly, and what the institution-type gap means for strategy The deeper roots of distrust, including the sense of distance between campuses and their communities Community engagement as the core of trust, and why it cannot live in a single office Inclusive excellence as a student success strategy, including the position of conservative students Defending academic freedom and university autonomy against government overreach Telling a clearer story that connects to shared values, and why PR alone falls short Accelerating internal innovation, from shared governance to AI literacy Three Key Takeaways for Leadership Connection is the thread through every recommendation: within a campus, across campuses, and with the community, society, and students. Reform, defense, and communication are not an either/or; institutions have to pursue all three at once. Higher education is a community asset, and it earns trust by being trustworthy and doing the work, not by asking for trust. The most durable change, Young argues, will not come from convening the sector's leaders to design a single fix. It will bubble up from individual campuses that innovate, with others adopting what works. Read the transcript: https://changinghighered.com/the-trust-agenda-advancing-public-trust-in-higher-education/ #HigherEducation #PublicTrust #HigherEducationLeadership #ChangingHigherEdPodcast

When the federal government freezes research funding, leaders tend to treat it as a budget problem: a number that was cut and might later be restored. The harder truth in this conversation is that much of the damage cannot be undone. Halted studies, shuttered labs, and departed early-career researchers do not simply resume when the money comes back. Research funding cuts are a strategic risk, not a line item. In this episode of the Changing Higher Ed® podcast, Dr. Drumm McNaughton speaks with Dr. Nick Dirks, President and CEO of the New York Academy of Sciences and former chancellor of UC Berkeley. Dirks first joined the show in 2018, as the podcast's third guest, reflecting on the protests that had put Berkeley at the center of national attention over controversial speakers on campus. He returns to discuss what the current research funding cuts are doing to American science, where AI fits in higher education, and the choices facing presidents and boards. This conversation is especially relevant for presidents, provosts, and board members weighing how federal funding volatility, the loss of early-career research talent, and the rapid arrival of AI in the classroom should shape institutional strategy and risk planning. Topics Covered •       Why frozen research funding cannot simply be switched back on, and what that means for biomedical studies, drug trials, and animal research •       The damage to the early-career research pipeline, and why postdocs and graduate students are the most exposed •       What current data shows about US scientists weighing whether to leave the country or the field •       How the president's role has shifted from pleasing every constituency to making hard, unpopular choices •       Why bringing higher education's costs down depends on faculty and administrators rebuilding trust Real-World Examples Discussed •       Drug trials at Columbia that had to stop outright, ending years of work toward a potential cancer treatment that could not be restarted once funding returned •       Animal research populations that universities could no longer afford to maintain, forcing some labs to shut down entirely •       The mRNA vaccine effort spanning the University of Pennsylvania, Germany's BioNTech, and scientists originally from Turkey •       A National Postdoctoral Association survey Dirks worked on, and a January 2026 AAU brief quantifying how far the talent loss has progressed •       The calculator's arrival in the 1970s as a precedent for absorbing a disruptive new tool without banning it Three Key Takeaways for Leadership 1.     Research funding cuts are a strategic risk, not a budget event. The damage to studies and to the people who run them often cannot be reversed once the money returns. 2.     The early-career pipeline is where the loss compounds. Protecting graduate students, postdocs, and research associates is protecting the institution's long-term research capacity. 3.     Hard institutional decisions require trust. Cost discipline and AI adoption both depend on boards, presidents, and faculty working together rather than against each other. This episode offers presidents and boards a clear-eyed look at how funding shocks, talent loss, and AI are reshaping higher education, and why the institutions that plan for these pressures will weather them better than those that wait. Read the transcript: https://changinghighered.com/research-funding-cuts-are-a-strategic-risk-not-a-budget-problem/ #ResearchFunding #HigherEducation #HigherEdLeadership  #HigherEducationPodcast

Most AI conversations in higher education focus on the academic side. The administrative side gets less attention and is producing the bigger near-term financial wins for institutions willing to govern the rollout. In this episode of the Changing Higher Ed® podcast, Dr. Drumm McNaughton speaks with Justin Beck, CEO of Gravyty, about how AI is being applied across enrollment and advancement at institutions including Empire State University, Florida Southwestern State College, and Boise State University. Drawing on his career across Blackboard, Instructure, Kaltura, and now Gravyty, Beck walks through the specific case studies behind administrative AI adoption: a reported 4% year-over-year retention gain at Empire State, 90% first-contact resolution of admissions inquiries at Florida Southwestern, and an 87% increase in donor volume at Boise State. He also explains where institutions go wrong, including bots that loop the way call-center bots loop and set-it-and-forget-it deployments that drift out of alignment within weeks. This conversation is especially relevant for presidents, boards, and enrollment and advancement leaders building the business case for administrative AI and the governance to back it. Topics Covered Why administrative AI is producing measurable financial gains while most institutions still treat AI as an academic policy question The retention math: how a 4% lift can translate into multi-million-dollar revenue protection at a mid-size institution How AI sorts and triages carries admissions volume that hiring cannot keep up with Why a poorly designed enrollment chatbot is worse than no chatbot at all How AI surfaces structural fragmentation across student-facing offices Advancement AI's real value: donor prioritization, not email generation What good governance and human-review cadence actually look like in practice Real-World Examples Discussed Empire State University: a 25% engagement lift and a 4% year-over-year retention gain after deploying AI virtual assistants across roughly eight departments Florida SouthWestern State College: 90% first-contact resolution of admissions inquiries and time to class registration cut in half Boise State University: an 87% increase in donor volume, a 50% increase in donor interaction and response, and $635,679 raised through an AI-assisted advancement channel A Missouri institution where an AI web crawler surfaced three different admissions deposit dates published on three active web pages A New York institution where more than 40% of questions coming into the financial aid office had nothing to do with financial aid Three Key Takeaways for Higher Education Leadership Move quickly, with an acceptable use policy on the books and defined institutional outcomes the AI work is supposed to drive Control what you can control while pulling stakeholders in, including the faculty committee model Iterate often on a recurring governance cadence, because the technology is changing month by month Institutions that do not use AI to improve administrative efficiency are incurring opportunity costs in every cycle. Read the transcript: https://changinghighered.com/administrative-ai-in-higher-ed-finding-revenue-friction/ #AdministrativeAI #HigherEducation #HigherEducationPodcast

AI implementation in higher education is often framed as a technology question. California State University treated it as change management with technology as the catalyst, rolling out ChatGPT Edu to 22 universities in 18 months while running the largest AI survey ever conducted at a single university system. In this episode of the Changing Higher Ed® podcast, Dr. Drumm McNaughton speaks with Dr. Leslie Kennedy, Assistant Vice Chancellor for Academic Technology Services at the California State University Office of the Chancellor, about how the system designed and executed its generative AI implementation and what the Ahead of the Curve survey of 94,060 respondents reveals about AI adoption, faculty engagement, and student behavior. Drawing on her work co-leading the academic side of CSU's GenAI initiative, Kennedy explains the governance structure that made the rollout possible, the campus-level training infrastructure that scaled adoption across 22 universities, and the survey findings that pushed back on common assumptions about cheating, faculty resistance, and AI access gaps. This conversation is especially relevant for presidents, provosts, boards, and CIOs evaluating how to move from AI policy discussions to systemwide implementation. Topics Covered: The sequencing model behind CSU's 18-month AI rollout Findings from the largest AI survey ever conducted at a single university system Why faculty are the only group reporting both positive and negative AI impact How CSU funded faculty-led innovation through the AI Educational Innovations Challenge The communication challenges of running AI implementation across 22 independent campuses What CSU plans next: hackathons, embedded credentials, and domain-specific tools Real-World Examples Discussed: The AI Educational Innovations Challenge received 417 faculty applications against an expected 50, with 63 funded at $3M ChatGPT Edu deployment across all 22 CSU campuses, now at 225,000 active accounts Student hackathons run with IBM Watson, AWS, NVIDIA, and Cal Poly partners across multiple disciplines Faculty-led podcasts (My Robot Teacher from Cal Maritime and Unfixed from Chico State) that built peer-to-peer training resources Three Key Takeaways for Leadership: Sequencing matters more than budget or technology. Faculty resolution first, governance second, enterprise tool third, training and funded experimentation in parallel. Faculty carry more complexity than staff or students in AI implementation, and need different support, training cadence, and communication than other groups. Communication is a continuous operating discipline, not a launch campaign. The technology changes faster than any single training cycle. This episode offers a practical view of what large-scale AI implementation actually looks like in higher education, and why the institutions getting it right are treating it as change management work supported by technology rather than a technology rollout in search of governance. Read the transcript: https://changinghighered.com/https://changinghighered.com/csu-chatgpt-edu-rollout-lessons-higher-ed-leaders/ #GenerativeAI #HigherEducation #HigherEducationPodcast

At sixteen, with straight A's in math and science, Dr. Karen Panetta's school career assessment told her to sell makeup or be a cook. A male friend with lower scores got engineer or politician. No AI was involved. Just a rules-based system applying gender and biographical filters to two teenagers. That same logic now sits inside AI tools landing in admissions offices and HR systems across higher ed, with one critical difference: AI does not eliminate human bias, it removes the human accountability that used to make bias correctable. In this episode of the Changing Higher Ed® podcast, Dr. Drumm McNaughton speaks with Dr. Karen Panetta, Dean of Graduate Education for the School of Engineering at Tufts University and an IEEE Fellow. Panetta lays out a procurement framework presidents and boards can use to evaluate AI tools before signing a contract. She and McNaughton work through the four questions most vendors cannot answer, why IRB principles already give higher ed a working framework for AI, and what happens to graduate research when students ask AI for a unique contribution and accept whatever comes back. This conversation is especially relevant for institutional leaders making decisions about AI procurement, classroom adoption, and data governance who want a clear set of questions to ask before they buy and a clear standard for keeping humans accountable for the decisions AI tools are increasingly being asked to make. Topics Covered: The four procurement questions every higher ed leader should ask before signing an AI contract Why expert disagreement on ground truth limits what any AI tool trained on that judgment can do How IRB principles apply to AI deployments, and why every kind use of technology has a misuse case sitting next to it The risk of AI's interpretation of truth aging with the consensus Why faculty in English, history, and the arts are essential to AI policy What IEEE's 500,000 technical professionals are doing on AI standards that no single corporate vendor will do Real-World Examples Discussed: The career assessments that pointed a top math student toward cooking and a Navy veteran toward forest ranger work A cancer detection project where six doctors agreed on whether something was cancer but disagreed on every grade beyond that A conservation project where the same tracking data that helps park rangers could help poachers if security is weak Graduate admissions committees where different faculty weight credentials, projects, and volunteer work differently, and what gets lost when only one set of weights is encoded into an AI screen Three Key Takeaways for Leadership: AI does not create bias. It scales whatever bias is already in the institution's decision systems, at the speed and volume the institution chose to deploy. Every consequential decision needs a human in the loop who can explain the call out loud. Without that, the institution cannot defend the decisions it is making. The sticker price on the AI tool is not the story. The data behind it is, and most vendors cannot tell you what it is. This episode gives presidents, provosts, and boards a practical framework for AI procurement and governance, along with a clear answer to the trustee asking why the institution has not bought what everyone else is buying. Read the transcript: https://changinghighered.com/ai-bias-procurement-framework-higher-education/ #HigherEducation #AIinHigherEd #HigherEducationPodcast #AIGovernance #AIBias #HigherEducationLeadership

Most business schools are still forming committees to figure out what to do about AI. Kogod School of Business at American University formed a committee, but far from the typical higher ed standards. Leadership gave it six weeks and a five-page limit, and used the recommendation to integrate AI into every department, major, and minor. Three years later, undergraduate enrollment is up 40%, applications are up 50%, and more than 90% of faculty are using AI in the classroom. In this episode of the Changing Higher Ed® podcast, Dr. Drumm McNaughton speaks with returning guests David Marchick, Dean of the Kogod School of Business at American University, and Angela Virtu, Professor of IT and Analytics and Associate Director of Kogod's AI Institute, about how the school moved from a dean's instinct that AI would be big to a fully embedded, faculty-driven transformation that has redefined how business education is taught, assessed, and experienced by students. Marchick and Virtu walk through how they navigated shared governance at speed, leaned into 14 core course coordinators to spread adoption like wildfire, and built a culture where faculty are making stuff up, trying things, and pivoting when something doesn't work. Virtu explains how courses are being rebuilt from the ground up, with professors shifting from lecturers to coaches and students building real software for real clients. Marchick shares the enrollment and media results, including being named the first AI-first business school by Bloomberg Businessweek. This conversation is especially relevant for institutional leaders trying to figure out how to move on AI without blowing up their governance structures or losing faculty trust. Kogod's playbook worked within existing academic processes, and the results are measurable. Topics Covered: •       How a conversation with a Google executive sparked the AI initiative before ChatGPT went mainstream •       Why Marchick gave the faculty committee six weeks and a five-page limit instead of a two-year study •       The top-down and bottom-up strategy that moved faculty adoption from a handful of volunteers to over 90% •       How 14 core course coordinators became the tactical lever for culture change across the school •       The shift from professors as lecturers to professors as coaches •       How non-quantitative students are programming and building functioning apps using AI •       Kogod's scaffolded four-year curriculum: AI literacy in year one, domain-specific applications in year two, deep dives in years three and four, and a capstone that combines all three pillars •       Why the school teaches what's wrong with AI before teaching what's right •       The AI assessment problem no institution has solved yet •       What's next: domain-specific AI apps, student portfolios, and an AI minor for non-business students Real-World Examples Discussed: •       Tommy White's course with no readings and no textbook, where students use AI prompts to find their own materials and come to class with different sources on the same topic •       Kelly Frias's advertising class where students built a social media content tool and owner dashboard for a real college-apparel business with brand ambassadors at 75 campuses •       Brad Smith, president of Microsoft, telling Marchick that the specific AI tool matters less than teaching students to feel comfortable experimenting and trying new things •       A distinguished Kogod scholar describing AI as like having a PhD student for research productivity Three Key Takeaways for Leadership: 1.    Culture first, training second, technology third. Faculty adoption spreads when leadership creates permission to experiment and fail, not when it purchases a platform. 2.    Teach what's wrong with AI before teaching what's right. A human has to be in the loop at the beginning and at the end. AI can be a collaborator, a partner, an assistant, but it cannot be a substitute. 3.    Don't wait for the technology to stabilize. AI capabilities are changing in weeks. If you tried it two years ago and weren't impressed, try it again. The updates in just the last few weeks represent really big strides. This episode offers a practical, replicable look at what happens when a business school treats AI integration as a culture change initiative and moves fast enough to stay ahead of the technology. Kogod's transformation is relevant to any institution trying to figure out how to act on AI without waiting for a perfect plan. Read the transcript: https://changinghighered.com/kogod-ai-first-business-school-enrollment-growth/ #AIinHigherEd #BusinessEducation #HigherEducation #HigherEducationPodcast #ChangingHigherEdPodcast

AI adoption in higher education is moving faster than institutional change models were built to handle. Students are already using AI at high rates, while many institutions are still trying to decide where AI belongs, who should lead it, and how much change is required. In this episode of the Changing Higher Ed® podcast, Dr. Drumm McNaughton speaks with Nikki Barua, serial entrepreneur and founder of FlipWork, about why higher education's traditional change management playbook will not work in the AI age. Drawing on her work with Fortune 500 companies and AI implementation, Barua explains why AI should be treated as institutional infrastructure, not an IT project. She discusses the growing gap between technology adoption and human readiness, why many AI pilots fail, and how institutions can move from slow, episodic transformation to shorter, people-centered reinvention cycles. This conversation is especially relevant for presidents, boards, provosts, CIOs, and senior leadership teams trying to prepare students, faculty, staff, and institutional systems for an AI-driven future. Topics Covered Why incremental change management cannot keep pace with AI How AI differs from previous technology disruptions like the internet and mobile Why AI should be treated as infrastructure across the institution What the AI readiness gap means for higher education leaders Why many AI pilots fail when organizations focus on tools instead of people How AI may reshape entry-level jobs and the graduate talent pipeline Why skills-based hiring is changing what students need from higher education How faculty roles may shift from content delivery to mentorship, ethics, and judgment Why liberal arts and human skills may become more valuable in the AI age How human-in-the-loop design can improve AI use in enrollment, advising, and student support Why AI literacy must become a core institutional capability Real-World Examples Discussed AI adoption among students far outpacing institutional readiness Corporate AI pilots failing because organizations did not prepare people to use the tools effectively Entry-level jobs shrinking or changing as AI takes over early-career tasks Employers moving toward skills-based hiring and project-specific teams AI tutors, teaching assistants, adaptive learning tools, and student support applications Enrollment chatbots that create frustration when they replace rather than support human interaction Human-in-the-loop workflows that know when to hand a student or prospect to a person Ethics in AI as a foundation for preparing graduates to use powerful tools responsibly Three Key Takeaways for Higher Education Leadership AI is an opportunity for reinvention, not an IT project. Institutions should treat AI as a strategic leadership issue that affects competitive position, culture, academic delivery, student support, and institutional agility. Students are already ahead of many institutions. Without governance, ethical guidelines, and structured leadership, AI use can become unmanaged shadow AI across the institution. The cost of waiting grows exponentially. AI is advancing week by week, and institutions that delay action will face a widening readiness gap that becomes harder and more expensive to close. This episode offers a direct look at why higher education cannot rely on its traditional pace of change in the AI age, and why institutional leaders must rethink what they offer that AI cannot replicate. Read the transcript: https://changinghighered.com/closing-higher-educations-ai-readiness-gap/ #AIinHigherEducation #HigherEducation #HigherEducationPodcast #WorkforceReadinessGap

Scaling higher education is no longer a theoretical strategy. As the sector moves deeper into consolidation, institutional leaders need to confront whether their operating models, credential structures, partnerships, and delivery systems are built for the market ahead. In this episode of the Changing Higher Ed® podcast, Dr. Drumm McNaughton speaks with Dr. Stephen Spinelli, President of Babson College, about how an entrepreneurial mindset can help higher education respond to consolidation, AI disruption, and changing learner expectations. Drawing from his experience as co-founder of Jiffy Lube International and president of one of the nation's leading entrepreneurship institutions, Spinelli explains why higher education's anti-scale culture has become a strategic problem. He argues that demand for learning is growing, but the sector's delivery model has not kept pace with what students, employers, and adult learners now need. The conversation covers how AI is changing the economics of small-unit, high-quality education, why credentials are likely to become more modular and measurable, and how partnerships with other institutions and industry will shape the next era of higher education. Spinelli also outlines why strategy must be tied to action, accountability, and institutional values that do not shift with every market signal. This episode is especially relevant for presidents, boards, and senior leaders working through questions of scale, consolidation, strategic partnerships, AI-enabled learning, and long-term institutional relevance. Topics Covered Why higher education is showing classic signs of market consolidation How anti-scale thinking limits institutional durability and adaptability Why demand for learning is growing while delivery models lag behind How agentic AI changes the economics of small-unit education Why credentials may become smaller, more measurable, and more industry-aligned How strategic partnerships may extend beyond institutions into corporate and industry networks Why lifelong learner relationships may become a new revenue and relevance model How quarterly board-level strategic execution reviews keep institutions accountable Why liberal arts capabilities matter more in an AI-enabled environment Real-World Examples Discussed Jiffy Lube's early growth model and what it taught Spinelli about scale Babson's shift from entrepreneurship to entrepreneurial leadership Babson's network of 45 or 46 partner schools building entrepreneurial leadership capacity A group of seven New England institutions exploring partnership models to save resources AI-supported teaching models that could allow one expert to reach far more learners The doctor, lawyer, educator relationship model for lifelong learning Three Key Takeaways for Higher Education Leadership Institutions need a crisp and understandable value proposition that clearly explains why they exist and what they believe. Mission and values must drive strategy so institutions can adapt their actions without abandoning their core purpose. Strategic plans must be actionable, measurable, and reviewed regularly by the board so they inform decisions instead of sitting unused. This episode offers a direct look at what higher education leaders need to confront as consolidation, AI, modular learning, and partnership-driven delivery reshape the sector. Read the transcript: https://changinghighered.com/scaling-higher-education-entrepreneurial-approach/ #HigherEducation #HigherEducationLeadership #HigherEducationPodcast