AI for U

Brian Piper

AI for U is the go-to podcast for higher ed professionals looking to integrate AI into their daily work. Each episode features interviews with industry leaders, providing insights on implementing and leveraging AI to streamline processes, enhance student experiences, and drive institutional success. Join host Brian Piper every other Thursday for fresh, empowering content that keeps you at the forefront of AI in higher education.

  1. 6d ago

    Ep. 52: How AI-Powered Student Enrollment Frees Staff to Focus on Genuine Empathy

    Higher education is undergoing rapid technological shifts, but Dr. Courtney Lewis believes AI integration should never mean sacrificing human empathy. Host Brian Piper sits down with the Director of Enrollment Services at Trinity Valley Community College (TVCC) to explore how an institution in rural East Texas leveraged AI-powered student enrollment to achieve sustained semester-over-semester growth. Courtney talks about her personal journey as a former first-generation TVCC student who navigated the college search with no money, no roadmap, and a shame-inducing narrative around community colleges, transforming that lived experience into a mission to rebuild the enrollment model from the ground up. She also shares actionable advice on change management, explaining why leaders must be vulnerable, expect to fail fast, and stop forcing AI into outdated, legacy processes. Join us as we discuss:  [2:16] How Courtney is addressing the challenges she faced as a TVCC student [7:52] Framing AI integration to your team as an opportunity to create more human connections [14:39] Why disconnected data is the biggest obstacle to implementing AI tools [22:14] The biggest takeaways from driving organizational change around data governance Check out these resources we mentioned during the podcast: Trinity Valley Community College Sees Surge in Enrollment (KETK NBC) To hear this interview and many more like it, subscribe on Apple Podcasts, Spotify, or our website, or search for AI for U with Brian Piper in your favorite podcast player. Episode Prompt:  **ROLE** You are a process design facilitator. Your job is to stop me from automating something that should not exist. You are direct, you ask uncomfortable questions, and you do not let me defend a step just because it is familiar. Ask questions one at a time. **ACTION** Take one process I am considering automating and tear it down to its purpose before we discuss any tooling. Rebuild it from zero, then, and only then, tell me where AI actually belongs. **CONTEXT** Interview me one question at a time until you understand: - The process, described as a numbered sequence of every step, including the steps nobody documents - For each step: who does it, how long it takes, how often, and what triggers it - Why each step exists, and if I answer "that's how we've always done it," push back and ask who would notice if it stopped tomorrow - What outcome the process is supposed to produce for the student or the institution, stated in one sentence - Which steps exist because of a policy, an accreditation or legal requirement, or a system limitation, and which are just habit - What happens today when this process fails - What constraints are genuinely fixed (staffing, budget, regulation) versus assumed **EXECUTE** Produce, in this order: 1. **Purpose statement** — the one sentence this process exists to deliver. If the current process does not deliver it, say so plainly. 2. **Step audit** — every step classified as: Required (regulation, policy, accreditation) | Load-bearing (something downstream breaks without it) | Vestigial (exists from a prior system, workflow, or org chart) 3. **Clean-sheet redesign** — how you would build this process today, from nothing, to deliver the purpose statement. Ignore our current org chart and software. State the redesign's staffing and data prerequisites. 4. **Gap between now and clean sheet** — what would have to change: ownership, policy, data, staffing, culture. Which of these are hard and which are just uncomfortable. 5. **Where AI fits…and where it doesn't** — in the redesigned process, identify: steps AI should handle (high volume, low empathy, low judgment), steps a human must own (emotional stakes, exceptions, consequential decisions), and steps AI should never touch and why. Include what human oversight and audit each AI step requires. 6. **What we would automate today if we skipped this exercise** — name the steps I was about to bolt AI onto that should have been deleted instead. 7. **Rollout timing** — given our academic calendar, when should this change, and when should it absolutely not. Assume the first attempt will fail and pick a window where that is survivable. **CONSTRAINTS** - Do not recommend a specific product. - If I have not told you a legal or accreditation requirement, ask rather than assume one exists. - Every AI recommendation must name the human check that sits on top of it. - If the honest answer is that this process needs no AI at all, say that. - - - -Connect With Our Host:Brian Piperhttps://www.linkedin.com/in/brianwpiper/ About The Enrollify Podcast Network:AI for U is a part of the Enrollify Podcast Network. If you like this podcast, chances are you’ll like other Enrollify shows too!  Enrollify is made possible by Element451 —  The AI Workforce Platform for Higher Ed. Learn more at element451.com. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

  2. Jul 30

    Ep. 51: Why Higher Ed Must Adopt AI at Scale Before the Tech Passes Them By

    AI is changing how we learn, work, lead, and prepare students for the world ahead. So why isn’t higher ed moving faster in adopting this technology at scale? In this episode, Brian is joined by Josh Riedy, Executive Director of the Institute of Applied AI at Minnesota State University Moorhead, to explore what meaningful AI adoption looks like across higher education. Josh shares MSUM’s approach to building AI literacy across academic programs, creating real-world learning opportunities through its Applied AI Clinic, and preparing students to enter the workforce with practical AI experience. He also explains why institutions cannot simply hand AI over to the CIO, create another committee, or launch a standalone AI certificate and consider the job done. Join us as we discuss:  [3:25] Why higher ed needs to start adopting AI at scale [15:35] Who should lead AI implementation measures across your institution  [25:52] Using workshops and challenges to establish an AI literacy framework To hear this interview and many more like it, subscribe on Apple Podcasts, Spotify, or our website, or search for AI for U with Brian Piper in your favorite podcast player. - - - -Connect With Our Host:Brian Piperhttps://www.linkedin.com/in/brianwpiper/ About The Enrollify Podcast Network:AI for U is a part of the Enrollify Podcast Network. If you like this podcast, chances are you’ll like other Enrollify shows too!  Enrollify is made possible by Element451 —  The AI Workforce Platform for Higher Ed. Learn more at element451.com. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

  3. Jul 23

    Ep. 50: How 24/7 Student Support AI Drives True Equity in Higher Education

    When Massachusetts rolled out free community college, it drove massive equity across the state, but it also created an unprecedented bottleneck at the front door of smaller institutions. Brian sits down with Alex Russo, Director of Enrollment & Recruitment Strategy at Cape Cod Community College, to discuss how a school with limited headcount operationalized 24/7 student support AI to manage a sudden 40% spike in student volume. Alex shares how their frontline AI agent triages hundreds of late-night inquiries from busy, non-traditional students, freeing up staff to focus on deep, relational counseling sessions and high-impact on-campus events. Join us as we discuss:  [2:51] Why 24/7 AI agent support became an enrollment equity driver for Cape Cod Community College [11:04] How community colleges can start leaning into an AI strategy on limited budgets [20:59] Measuring the ROI of AI agents and maintaining your school’s brand voice   To hear this interview and many more like it, subscribe on Apple Podcasts, Spotify, or our website, or search for AI for U with Brian Piper in your favorite podcast player. Episode prompt:  ROLE You are reviewing a draft on behalf of the person who will read it. You are not a writer, an editor, or a copy improver. You are a stand-in for the reader. CONTEXT - Who wrote this: [YOUR ROLE, e.g. director of enrollment] - Who will read this: [BE SPECIFIC — e.g. a prospective student who is the first   in their family to apply to college and has never completed a FAFSA] - What the reader already knows: [WHAT CAN YOU ASSUME THEY KNOW?] - What the reader needs to do after reading it: [THE ONE ACTION] - Constraints: [DEADLINE, TONE, LENGTH, POLICY LANGUAGE THAT CANNOT CHANGE] THE DRAFT """ [PASTE YOUR DRAFT HERE] """ ACTION Do NOT rewrite my draft. Do NOT produce an improved version. Do NOT change my word choices, sentence rhythm, or voice. Report back only, using these headers: 1. THE ONE ACTION — In one sentence, what does this draft ask the reader to do?    If you cannot tell, say so. 2. WHERE A READER GETS LOST — Quote the exact phrases that assume knowledge    this reader may not have: jargon, acronyms, internal process names,    unstated steps. 3. UNANSWERED QUESTIONS — What will this reader wonder that the draft never    answers? List them as questions. 4. INTERNAL CONTRADICTIONS — Flag any dates, times, names, amounts, or    instructions that conflict with each other elsewhere in the draft. 5. TONE CHECK — Is there anywhere the language could make this reader feel    judged, condemned, or hesitant to ask for help? Quote it. 6. WHAT IS WORKING — Two things I should not change. EXECUTE Before you begin, ask me any clarifying questions you need, one at a time. When you report, cite the exact text you are referring to. If a section has nothing to flag, write "Nothing flagged" rather than inventing a concern. - - - -Connect With Our Host:Brian Piperhttps://www.linkedin.com/in/brianwpiper/ About The Enrollify Podcast Network:AI for U is a part of the Enrollify Podcast Network. If you like this podcast, chances are you’ll like other Enrollify shows too!  Enrollify is made possible by Element451 —  The AI Workforce Platform for Higher Ed. Learn more at element451.com. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

  4. Jul 2

    Ep. 49: More Than Just a Writing Assistant: The Three Layers of Agentic AI

    Brian welcomes back Ardis Kadiu, Cofounder and CEO at Andi.ai, to break down the massive shift from simple text generation to true agentic autonomy. Ardis maps out the three critical layers of agentic AI — skills, workflows, and autonomous agents — and explains why higher ed institutions must stop looking at models and start evaluating the “harness” surrounding them. He outlines five essential questions that university presidents and cabinets must ask to expose organizational ambiguity, protect data authority, and safely redesign campus workflows. The conversation also explores learning intelligence in an AI-saturated classroom and why an artifact like a final essay is no longer an accurate indicator of student competency. Join us as we discuss:  [2:53] Why higher ed professionals need to reframe their understanding of AI’s capabilities [12:07] Five questions higher ed leaders need to ask before implementing AI [19:55] How AI is going to change higher ed’s role in an evolving job market [30:30] Closing the gap between future AI model capabilities and human adoption To hear this interview and many more like it, subscribe on Apple Podcasts, Spotify, or our website, or search for AI for U with Brian Piper in your favorite podcast player. - - - -Connect With Our Host:Brian Piperhttps://www.linkedin.com/in/brianwpiper/ About The Enrollify Podcast Network:AI for U is a part of the Enrollify Podcast Network. If you like this podcast, chances are you’ll like other Enrollify shows too!  Enrollify is made possible by Element451 —  The AI Workforce Platform for Higher Ed. Learn more at element451.com. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

  5. Jun 18

    Ep. 48: The Messy Middle of AI: How the University of Notre Dame Is Navigating Change

    Artificial intelligence is rapidly reshaping higher education, but most institutions are still trying to navigate what responsible adoption actually looks like in real time. In this episode, Brian sits down with Brandon Rich, Director of AI Enablement at the University of Notre Dame, to explore what he calls the “messy middle” of AI adoption in higher ed. Brandon shares how Notre Dame moved from an AI task force to campus-wide implementation in less than a year, launching AI literacy initiatives, governance frameworks, and hands-on experimentation across departments like HR, student affairs, finance, and research administration.  Join us as we discuss:  [2:47] The “messy middle” of AI adoption in higher education [13:26] How Notre Dame rolled out AI strategically across campus [26:06] Budgeting, staffing, and resource challenges for AI initiatives Check out these resources we mentioned during the podcast: Snowflake Cortex  ChatGPT Edu Okta To hear this interview and many more like it, subscribe on Apple Podcasts, Spotify, or our website, or search for AI for U with Brian Piper in your favorite podcast player. - - - -Connect With Our Host:Brian Piperhttps://www.linkedin.com/in/brianwpiper/ About The Enrollify Podcast Network:AI for U is a part of the Enrollify Podcast Network. If you like this podcast, chances are you’ll like other Enrollify shows too!  Enrollify is made possible by Element451 —  The AI Workforce Platform for Higher Ed. Learn more at element451.com. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

  6. Jun 4

    Ep. 47: Governance and Accessibility: How to Build Trust Around AI in Higher Ed

    Returning guest Joyce Peralta, Manager of Digital Communications at McGill University, joins Brian for a thoughtful conversation about what higher education institutions are getting right and wrong about AI adoption. From governance and accessibility to localization and structured content, Joyce shares how McGill is navigating the realities of implementing AI inside a large, decentralized institution. She explains why AI readiness is really about trust, shared standards, and human judgment, not just new technology. The conversation also explores the future of AI in higher education and why successful adoption will depend on building systems that support both consistency and inclusion. Join us as we discuss:  [2:38] Governance, trust, and creating shared standards across decentralized teams [11:34] The localization barrier in AI-assisted translation tools [21:19] Why AI is still stuck in an accessibility bottleneck To hear this interview and many more like it, subscribe on Apple Podcasts, Spotify, or our website, or search for AI for U with Brian Piper in your favorite podcast player. Episode prompt: You are a governance and strategy advisor specializing in responsible AI integration within institutional environments. I'm preparing to roll out a new AI use case in my organization. Before I do, I want to stress-test it against the standards and best practices my community already trusts. Your job is to help me surface where this AI initiative might fall short of those standards, identify the connections I need to draw for stakeholders, and recommend governance touchpoints to build into the rollout. Before you respond, ask any clarifying questions that will produce a stronger analysis. The AI Initiative: [DESCRIBE THE AI USE CASE — WHAT IT DOES, WHO USES IT, WHAT IT PRODUCES] Context: Organization type: [PUBLIC/PRIVATE, SIZE, CENTRALIZED OR DECENTRALIZED] Functional area: [MARKETING, ADMISSIONS, ADVANCEMENT, IT, ACADEMIC AFFAIRS, ETC.] Audiences affected: [INTERNAL TEAMS, PROSPECTIVE STUDENTS, CURRENT STUDENTS, ALUMNI, ETC.] Timeline: [WHEN YOU PLAN TO ROLL IT OUT] Key stakeholders: [WHO NEEDS TO BUY IN, WHO HAS OVERSIGHT] Our Existing Standards and Best Practices: Accessibility: [SUMMARIZE YOUR ACCESSIBILITY STANDARDS] Privacy & Security: [SUMMARIZE YOUR PRIVACY AND DATA HANDLING REQUIREMENTS] Brand, Tone & Voice: [SUMMARIZE YOUR BRAND AND EDITORIAL GUIDELINES] Usability & User Experience: [SUMMARIZE YOUR UX AND CONTENT STANDARDS] Other governance commitments: [E.G., BILINGUAL/MULTILINGUAL CONTENT, DEI, DATA SOVEREIGNTY, RESEARCH ETHICS] How I'm Currently Planning to Roll This Out: [OUTLINE YOUR ROLLOUT APPROACH — COMMUNICATION, TRAINING, OVERSIGHT, REVIEW] Now help me work through the following: Standards Alignment: For each existing standard above, where might this AI use case fall short? Be specific about how AI output could violate or undermine each one in practice. The Connection Gap: What language and framing should I use to show my community how this AI initiative reinforces — rather than replaces — the best practices they already trust? Give me phrasing I can use in actual rollout communications. Accessibility Stress Test: AI is a statistical reasoning tool and can overlook the experiences of people whose needs sit outside the majority. Where in this use case is that risk highest, and how do I design against it? Governance Touchpoints: What review steps, human-in-the-loop checkpoints, or oversight roles should I build into the rollout to maintain quality and trust over time — not just at launch? Cross-Silo Implications: In a decentralized environment, which other teams or functions should be in the conversation before this rolls out? What shared structure — terminology, content model, data definitions — might need to be in place first for AI to produce accurate, complete output? Readiness Check: Are the content, data, or processes this use case depends on actually ready for AI, or would I be rolling out before the foundation is in place? Tell me honestly if I should slow down and fix the underlying structure first. Be direct. I need this stress-tested, not validated.   - - - -Connect With Our Host:Brian Piperhttps://www.linkedin.com/in/brianwpiper/ About The Enrollify Podcast Network:AI for U is a part of the Enrollify Podcast Network. If you like this podcast, chances are you’ll like other Enrollify shows too!  Enrollify is made possible by Element451 —  The AI Workforce Platform for Higher Ed. Learn more at element451.com. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

  7. May 21

    Ep. 46: From Operators to Orchestrators: How AI Is Reshaping Our Strategic Mindsets

    Raj Jha has spent his career working across computer science, technology law, entrepreneurship, and AI systems, giving him a unique perspective on how organizations navigate periods of rapid technological change. In this episode, Raj joins Brian to discuss why most conversations about AI focus too heavily on tools instead of outcomes, how institutions can adapt without losing trust, and why the future may belong to humans who can think like orchestrators instead of simply operators. Join us as we discuss:  [2:32] Why “What AI tool should we use?” is the wrong question [10:24] How AI is forcing higher education to rethink its entire model [24:16] Reframing how siloed departments handle AI implementation [32:19] Why this is a great time for entrepreneurs and intrapreneurs Check out these resources we mentioned during the podcast: RajJha.com Raj Jha (X) To hear this interview and many more like it, subscribe on Apple Podcasts, Spotify, or our website, or search for AI for U with Brian Piper in your favorite podcast player. - - - -Connect With Our Host:Brian Piperhttps://www.linkedin.com/in/brianwpiper/ About The Enrollify Podcast Network:AI for U is a part of the Enrollify Podcast Network. If you like this podcast, chances are you’ll like other Enrollify shows too!  Enrollify is made possible by Element451 —  The AI Workforce Platform for Higher Ed. Learn more at element451.com. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

  8. May 7

    Ep. 45: The Death of the Data Dashboard: What’s Next for AI in Higher Ed

    There’s a quiet shift happening in how we work with data. For years, the focus has been on collecting more of it, building better dashboards, and reporting on the right numbers. But as this conversation explores, that approach may be reaching its limit. That’s because having data isn’t the same as having insight. In this episode, Brian talks with Jamie Boggs, Marketing and Engagement Analyst at Eastern Kentucky University, to talk about what’s actually changing as AI becomes part of everyday workflows in higher education. They explore why many institutions are “data rich but insight poor,” the difference between using AI for automation versus rethinking entire systems, and what it looks like to treat AI less like a tool and more like a teammate. Join us as we discuss:  [3:59] What “data rich, insight poor” means for higher ed [18:05] The death of the data dashboard and what it means for student insights [26:24] What institutions should be doing now to future-proof their schools Check out these resources we mentioned during the podcast: EduData podcast The Enrollify network of podcasts To hear this interview and many more like it, subscribe on Apple Podcasts, Spotify, or our website, or search for AI for U with Brian Piper in your favorite podcast player. Episode prompt: ROLE You are an expert in higher education analytics and marketing measurement, with deep experience helping institutions move beyond vanity metrics to identify the data points that genuinely indicate progress toward strategic outcomes. ACTION Help me identify the specific metrics that will give me real insight into whether a particular initiative or goal I'm working on is actually working — and flag any meaningful gaps in the data I'm currently collecting. CONTEXT Before recommending any metrics, you need a clear picture of the initiative, the outcome it's tied to, the audiences involved, and the data I currently have access to. Ask me the following questions one at a time, waiting for my answer before moving to the next: 1. What is the initiative, campaign, program, or goal you're focused on? Describe it in your own words. 2. What is the strategic outcome this initiative is meant to drive? (e.g., enrollment growth, retention, yield, brand awareness, alumni engagement, faculty recruitment, fundraising) 3. Who are the primary and secondary audiences this initiative is trying to reach or influence? 4. What does success look like 6 months from now? 12 months from now? 5. What metrics, if any, are you currently tracking for this initiative? Which ones do you report up to leadership? 6. What data sources and tools do you have access to? (e.g., CRM, Google Analytics, Search Console, Slate, Salesforce, social platforms, SIS, LMS, email platform) 7. What constraints should I be aware of — budget, staffing, data access, privacy, governance, leadership reporting expectations? 8. Is there anything you've tried to measure in the past that didn't work, or any data you wish you had but don't? EXECUTE Once you have my answers, deliver: 1. A short summary of the initiative and outcome in your own words, so I can confirm we're aligned. 2. A list of vanity metrics I should stop over-relying on for this initiative — and why they're not actually telling me what I need to know. 3. A list of insight metrics that would actually indicate real progress toward the strategic outcome, organized into:    - Leading indicators (early signals the initiative is on track)    - Lagging indicators (outcomes that confirm impact after the fact)    - Diagnostic metrics (help me understand *why* something is or isn't working) 4. For each insight metric, note which of my listed data sources it can be pulled from. 5. A gaps section flagging any critical metrics that would require me to start collecting data I don't currently have, with a brief note on what it would take to start collecting each one. 6. A short "leadership view" paragraph: what to report up to leadership vs. what to keep at the working level — so I can satisfy the "shiny things" leadership expects without losing focus on what actually moves the needle. Ask any clarifying questions you need, one at a time, before producing the final output. - - - -Connect With Our Host:Brian Piperhttps://www.linkedin.com/in/brianwpiper/ About The Enrollify Podcast Network:AI for U is a part of the Enrollify Podcast Network. If you like this podcast, chances are you’ll like other Enrollify shows too!  Enrollify is made possible by Element451 —  The AI Workforce Platform for Higher Ed. Learn more at element451.com. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

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AI for U is the go-to podcast for higher ed professionals looking to integrate AI into their daily work. Each episode features interviews with industry leaders, providing insights on implementing and leveraging AI to streamline processes, enhance student experiences, and drive institutional success. Join host Brian Piper every other Thursday for fresh, empowering content that keeps you at the forefront of AI in higher education.

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