AI for U

Host Brian Piper speaks with Scott Clyde, Chief Growth Officer at enroll ml, about the evolving role of artificial intelligence in higher education admissions and enrollment strategy. Scott shares his first hand experiences navigating change management, testing AI tools, and learning from “fail fast” moments, including why 17-year-olds won't connect with AI phone callers. They also dive into the fine line of hyper personalization, the importance of retention, and why creating a sense of belonging requires an “all in” campus effort where recruitment and retention become everyone's responsibility.
Join us as we discuss:
[2:16] How to overcome the “spy vs. spy” distrust around AI with students
[12:19] Why you can't volume your way out of enrollment cliff realities
[21:23] “Recruit, Retain, Graduate”: Why admissions is everyone's job
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:
I'm introducing AI into a workflow and I need to know what I'm walking into.
THE CHANGE
What I'm proposing: [describe the actual change in plain terms]
What it replaces or alters: [what people do today]
Who it lands on: [roles, how many people, how long they've been doing this]
What I'm telling them the goal is: [your stated rationale]
What's actually driving it: [budget, capacity, leadership mandate, be honest here]
What I can't promise: [job security, timeline, that it will work]
GIVE ME
1. THE OBJECTION LIST
Every objection this group will raise, sorted into two columns: what they'll say in the meeting, and what they'll say to each other afterward. The second column
is the one I need. Include the objections people express as enthusiasm, as process questions, or as sudden concern for students.
2. WHAT'S UNDERNEATH EACH ONE
For each objection, name the real concern driving it. Fear of being replaced, fear of looking incompetent with a new tool, loss of craft or expertise they're proud of, more work with no relief, or a genuine problem with my plan.
3. WHICH ONES ARE RIGHT
Flag every objection that is legitimate and should change what I'm doing. Do not soften these. If my plan has a real hole, say so and tell me what to fix before
I announce anything.
4. THE HONEST RESPONSE
For each objection, give me two things:
- What an honest response sounds like, in plain speech, no corporate language
- What the defensive or evasive version sounds like, so I can recognize it if I start saying it
- Where the honest answer is "I don't know yet" or "some of this will change your job," write the version of that sentence I can actually say out loud.
5. THE PHRASES THAT WILL COST ME
List the specific words and framings that will destroy trust with this group, and what to say instead. Include anything that sounds like a promise I can't keep.
6. THE OPENING
Write the first three sentences of my announcement. They should say what is changing, name the concern in the room before anyone else does, and state what
I am asking for. Under a hundred words.

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Connect With Our Host:
Brian Piper
https://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.

Higher education is confronting a massive erosion of public confidence, and the emergence of artificial intelligence is about to accelerate that reckoning. Host Brian Piper sits down with Teege Mettille, author of College Is Broken (And What We Can All Do to Fix It), to unpack how the higher ed trust deficit is being broken wide open by AI-driven transparency. Teege argues that just as Kelley Blue Book stripped used-car dealers of their information monopoly, accessible AI tools now empower under-resourced families to interrogate opaque pricing models, debunk inflated medical school admit rates, and cut through manipulated post-grad employment statistics. Despite the systemic dysfunctions, Teege lays out an optimistic case for campus practitioners: because higher education built these broken structures, everyday enrollment and marketing leaders possess the power to dismantle them and rebuild genuine trust.
Join us as we discuss:
[2:09] AI’s role in the trust problem that pervades higher ed’s pricing model
[10:29] Addressing the mass destruction of traditional entry-level positions
[13:51] Why traditional presidential leadership is the biggest barrier to real change
[25:51] How the perception of college-student engagement is changing in real-time
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 auditing how visible and honest the cost information is on a college or university website, from the perspective of a prospective student and family with no insider knowledge and no counselor helping them.
INSTITUTION CONTEXT
Institution: [name, private or public, URL, size]
Primary audience for this audit: [first year, graduate, parents, etc.]
Cost landing page: [URL]
Published cost of attendance: [$]
Net price calculator (if available): [URL]
TASK
Inventory every place a prospective family could encounter cost information. For each item you find, record:
What it is (a number, a calculator, a scholarship page, a payment plan, an FAQ)
Exact URL
Clicks from the homepage, and the path a family would have to guess to get there
Whether it is findable by site search using the words a family would type ("how much does it cost", "tuition", "price", "can I afford")
The exact language used, quoted
Whether it states a single number, a range, or a conditional answer
Whether it covers one year or the full time to a degree
Whether fees, housing, food, books, travel, and program specific costs are included, excluded, or unmentioned
Whether the page says what happens in years two, three, and four, including tuition increases and whether scholarships renew
Reading level and whether financial aid jargon is defined on the page
Present this as a table. Do not summarize. I want every instance, including the ones that contradict each other. Flag contradictions explicitly.
Then, based on the growing challenges that higher ed is facing (from the demographic cliff to the perceived value of higher ed), create a list of opportunities for this institution to be more transparent and helpful with prospective students to build trust and to make it as easy as possible for them to get the information they need.

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Connect With Our Host:
Brian Piper
https://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.

Come find me at the MAICON event on October 15 for a live recording of AI for U — https://www.marketingaiinstitute.com/events/marketing-artificial-intelligence-conference
Traditional marketing personas are often locked away in static PDF documents or PowerPoint decks, collecting digital dust while teams rely on gut instinct rather than real audience insights. Host Brian Piper welcomes Matt Wilkinson, Founder of Strivenn and author of The Buyer in the Loop, to explore how interactive AI personas in higher ed and marketing are transforming audience research. Matt breaks down why static persona documents fail, forcing marketers to perform uncomfortable mental gymnastics, and how grounding synthetic customers in deep research and voice-of-customer data allows teams to actually put their personas to work.
Join us as we discuss:
[3:06] What sets interactive AI personas apart from traditional student personas
[15:30] Practical examples of “synthetic for directional and human for decisional”
[22:20] How AI personas can combat organizational gravity during the content creation cycle
[29:11] Combatting imperfect data sets and tracking your synthetic personas’ ROI
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 buyer persona researcher working inside a higher education institution. You know the enrollment funnel, the advancement cycle, and how a university marketing office actually operates.
You work the way Adele Revella's "Buyer Personas" and Matt Wilkinson's "The Buyer in the Loop"
instruct.
Your job is not to write a persona document. It is to build a grounded, queryable representation of a real audience that my team can interrogate for months, then hand me the text to deploy it.
# THE ASSIGNMENT
AUDIENCE: [one sentence describing them]
INSTITUTION: [name and main URL]
DEPARTMENT: [marketing / admissions / advancement]
THE DECISION: [what this person is deciding: apply, deposit, give, re-enroll, upgrade a gift]
THE OUTCOME: [the institutional goal this supports]
REFERENCE URLS: [about, strategic plan, the 2-4 program or giving pages that matter most, cost and aid, outcomes]
EVIDENCE: [list what you are attaching]
# OPERATING RULES
1. Tag every claim [E] evidenced or [I] inferred. Never leave one untagged, never quietly promote an [I] to an [E].
2. Never invent quotes or manufacture voice. Patterns from real evidence only, with the source shown.
3. Resist the average. If a claim would be true of almost anyone in this category, flag it as GENERIC and either ground it or cut it.
4. Do not flatter. A persona that likes everything I show it gives me false confidence and the bad idea still gets built.
5. Synthetic for directional, human for decisional. You generate and stress-test hypotheses. You do not decide aid strategy, pricing, a case statement, or a program launch.
6. Carry no identifying detail about real people out of my evidence. Abstract to the pattern.
7. Write in plain language. If they would call it the price, do not call it the investment.
# PHASE 0 - INTAKE
Ask me these in one numbered batch and wait for answers.

1. What evidence do you have and can you share it? Interviews, surveys (admitted student, non-matriculant, melt, alumni), CRM and SIS behavior, GA4, frontline notes (counselor, call center, chat, tour, gift officer), and unowned voice (Reddit, Niche, review sites, parent groups).
2. What do you already believe about this audience, and how confident are you? Put your assumptions on the record now so we can see later which ones the evidence contradicts.
3. What are they choosing between, including the alternatives that are not other schools? A job, community college first, staying put, giving nothing this year.
4. Is this one audience or several wearing the same label?
5. Who else is in the room when the decision gets made, and can each of them champion, veto, or only advise?
6. What internal constraints can this persona's needs run into? Governance, brand standards, counsel review, an aid model or CMS you cannot change.
7. What will this persona be used for first?
# PHASE 1 - EVIDENCE READ AND GAP REPORT
Read everything, then before building give me a short report:
a. The three to five findings the evidence clearly supports, with sources named.
b. Where the evidence contradicts my Phase 0 assumptions. Quote me, then show what the evidence says. Be direct. This is the highest-value output of the exercise.
c. The gaps, and the fastest way to fill each one.
d. A provenance score, 1 to 5, and what it means for how far I should trust what follows.
Wait for my reaction before continuing.
# PHASE 2 - BUILD THE PERSONA
Tag every line [E] or [I].
THE FIVE RINGS
1. Priority initiatives. The 5 to 10 things actually taking their time, money, and worry right now. For each, what triggered it. The trigger matters most: what changed that made this decision active now rather than six months ago.
2. Success factors. What would make them say the decision worked, split into tangible outcomes and intangible ones (belonging, pride, relief, a parent's approval, legacy). Higher ed decisions run on the intangible column while institutional messaging runs on the tangible one. Name that mismatch if you see it.
3. Perceived barriers. What keeps them from choosing us, including the barriers that are factually wrong but sincerely held. For each: true, partly true, or false about this institution, and whether the fix belongs to marketing or to the institution.
4. Decision criteria. Ranked by the weight they actually carry, sorted into screeners (fail one and we are out), differentiators, and tiebreakers. Then say which we win, which we lose, and which we satisfy but never mention.
5. Journey. Stage by stage, using stages that fit this audience rather than a generic funnel. Per stage: what they feel, the exact questions they ask in their own words, who they trust for answers, what content they consume and what they wish existed, who else enters the decision, and what causes them to stall or reverse.


WHAT MAKES IT QUERYABLE
6. Identity. Fictional name, age range, life stage, and the situation they are sitting in today.
7. Voice. How they actually talk, including the institutional words they would never use. This is what separates a persona you can talk to from a slide you can look at.
8. Emotional drivers and anxieties, including the fear they would not say to a counselor or a gift officer.
9. Objections and turn-offs. Specific words, claims, images, and design choices that make the disengage.
10. Information sources ranked by trust, including the ones we do not control and the AI assistants they now ask before they ever reach our site.
11. What would change their mind. If you give me one line from this whole persona, give me this one.
THE DECISION GROUP
Build the primary persona in full, then map the other roles in one line each: their separate criteria, their power, when they enter, and where their criteria conflict with the primary persona's. That conflict is usually where the decision stalls. Then tell me plainly whether the other roles warrant full personas of their own or whether the map is enough.

# PHASE 3 - THE DEPLOYABLE PACKAGE
Give me a copy-and-paste block for a Custom GPT, Gem, or Claude Project containing a fictional name,
a one-line public description, a vivid and specific headshot prompt (synthetic person, never a real
one, and no generic professional headshot), and a system prompt written in first person covering
what they care about, what worries them, how they decide, where they are in the process, who they
trust, and how they talk.
The system prompt must instruct the persona to react to anything shown to it by naming its first-three-seconds gut response, scoring 1 to 10 on whether it would move them to the next step, pointing at the exact word or image that landed or lost them, and saying what they would need in order to act. It stays in character, stays blunt, says "I would be guessing here" rather than
performing a reaction it has no basis for, and tells anyone about to make an expensive decision on
its say-so to go talk to real people.
Attach an evidence ledger: each ring, its [E] or [I] status, its sources, and a confidence level.
That ledger travels with the persona so a colleague six months from now knows how much weight it holds

# PHASE 4 - KEEPING THE BUYER IN THE LOOP
Wilkinson's point is that the buyer gets researched once and then fades, because the people with approval authority are the people furthest from that buyer. Every edit is reasonable. The message still ends up written for the institution.
Give me a short plan to prevent that:
1. The three or four moments in our real workflow where the persona gets queried, including after approval. Run the approved version back past the persona and ask whether it still sounds like it was written for them. A score that drops between draft and approval is a measurement of organizational gravity, and a number is the thing that survives a conversation with a provost.
2. The one question anyone here can ask it in under a minute, so using it requires no process.
3. What it may never decide, and the human research each of those needs instead.
4. Refresh triggers: a new survey, a competitor or policy change, a leadership change, a news cycle, or twelve months, whichever comes first. Put a review date on it.
# HOW TO WORK WITH ME
Ask Phase 0 and wait. Do Phase 1 and wait for my reaction. Then run Phases 2 through 4 in one pass.
If I try to skip the evidence step, build it anyway but label the whole thing SPECULATIVE, say in
one sentence what it can and cannot be used for, and give me the gap list regardless.
Be specific. A vague persona is worse than none, because a vague persona still gets approved.

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Connect With Our Host:
Brian Piper
https://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.

Artificial intelligence brings with it a fundamental shift in how educational institutions prepare students for careers that have not yet been invented. In this episode of AI for U, host Brian Piper sits down with Dr. Rachelle Keck, President at Grand View University, to explore what institutional AI leadership in higher ed looks like from the president's office. Dr. Keck breaks down how Grand View, a resourceful, adaptive institution of 2,000 students, uses AI to level the playing field against billion-dollar endowments by automating mundane operational tasks to free up time for meaningful, face-to-face human connections. She shares how she fosters a culture of innovation where direct reports are encouraged to experiment and fail fast, why revising core curricula cannot take four to six years in an AI-driven world, and her favorite daily prompting secret: the Iowa "What Else?" method.
Join us as we discuss:
[2:32] Preparing tomorrow’s workforce through a culture of experimentation
[8:35] How higher ed leaders can prepare their faculty and staff for an AI strategy
[17:21] Winning over skeptics and Grand View’s biggest institution-wide changes brought by AI
[25:10] Bridging siloed departments and gauging the temperature of higher ed’s urgency to adopt an AI strategy
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:
“What else?”
Follow-ups to push it further once "What else?" has opened the door:
What am I assuming here that might not be true?
Who would disagree with this, and what's their best argument?
What would make this fail?
What would the strongest version of the opposite approach look like?
What am I not asking you that I should be?
What would you need from me to give a better answer?
Ask "What else?" more than once. The second and third passes are usually where the non-obvious material shows up. Stop when the answers start repeating.

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Connect With Our Host:
Brian Piper
https://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.

As artificial intelligence makes basic knowledge transfer free and instant, higher education institutions must confront a fundamental question: what is the true value of a university degree? Host Brian Piper speaks with Michael Horn, Author of Job Moves and co-founder of the Clayton Christensen Institute for Disruptive Innovation, to explore how AI is fundamentally reshaping higher education. Michael explains why simple AI chatbots fail to drive long-term student engagement and why community-centric higher education AI is the true path forward for sustainable institutional growth. Michael also outlines the shifting expectations of the modern job market, where employers increasingly expect entry-level candidates to arrive with real-world experience because AI now handles low-level administrative tasks.

Join us as we discuss: 

[2:36] The necessary pivot from marketing institutional knowledge transfer to communities of learning

[14:10] Why schools need to steer away from the traditional mindset of higher ed’s value

[24:06] The biggest obstacles in institution-wide AI integration on the administrative side

[33:45] Using AI to leverage career centers and marketing student outcomes that justify ROI

Check out these resources we mentioned during the podcast:

The Future of Education Substack

Episode Prompt: 

Act as a skeptical, well-informed advisor reviewing the attached [document/plan/draft]. 

Don't summarize it back to me. Instead: 

(1) identify the three biggest gaps or unanswered questions a smart critic would raise, 

(2) tell me what a reasonable person who disagrees with this approach would argue, and why, 

(3) flag anything that's vague, unsupported, or likely to raise a red flag with [leadership/faculty/families/whoever the real audience is], and 

(4) suggest the three best outside sources I should check before I finalize this. 

Ask me clarifying questions one at a time if you need more context before responding, rather than guessing.

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 Piper
https://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.