December 16, 2025 • 31 mins
What if AI actually made college more human—more supportive, more accessible, and more affordable? We sat down with Arizona State University CIO Lev Gonick to unpack how agentic AI, low-code tools, and faculty communities are transforming the student journey from recruitment to graduation.
Lev takes us inside “Agentic AI and the Student Experience,” a standing-room-only event that drew 650+ attendees from 25 countries. The focus wasn’t jargon; it was outcomes. We talk about “Experience AI” as a design principle that keeps value visible: faster curriculum design with human-in-the-loop checks, assessment aligned to skills and competencies, and agents that scout resources, research, and opportunities while faculty sleep. You’ll hear how ASU empowers staff and instructors through CreateAI, a low-code platform that moves innovation closer to the work, and why the university is replacing data silos with “data rivers” that support learners end to end.
We also dive deep on trust. Privacy, IP protection, and security aren’t footnotes; they’re the foundation. Lev explains how ASU differentiates its environment from consumer platforms, educates students and faculty on how AI engines operate, and uses principled innovation to set ethical guardrails. The result is a culture that scales experimentation without abandoning accountability. On the access front, we explore how agentic, multimodal recruiting tools help first-gen and low-income students discover pathways, compare programs, and get timely guidance that used to be out of reach.
If you care about student success, equity, or the future of learning, this conversation offers a clear, usable playbook: build communities of practice, define your trust posture, pilot targeted use cases, and scale what proves value. Enjoy the episode, share it with a colleague, and if it resonates, subscribe and leave a review so more educators and leaders can find it.
https://ai.asu.edu/
eloy@4leggedmedia.com
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Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
SPEAKER_00 (00:10):
Hi, this is the lawyer T S Oakley, and welcome
back to the Rand Podcast, thepodcast where we pull back the
curtain and break down thepeople, the policies, and the
politics of our higher educationsystem.
In this episode, I sit down withLev Gonick, the Chief
Information Officer at ArizonaState University.
(00:32):
Lev leads the technologyportfolio for the massively
innovative university, ArizonaState University.
Lev makes all of Michaeltechnology dreams come true.
And that is a tall order.
My conversation with Lev willtouch on the latest event at
(00:53):
Arizona State University calledAgentic AI and the Student
Experience.
Lev will talk about the eventand the overwhelming response he
got to the event from all acrossthe world.
Agentic AI, AI in general, andtechnology innovation are at the
center of the insatiableappetite for innovation at
(01:16):
Arizona State University.
So I'm looking forward tojumping into the conversation
with Lev and talking about howhe and his team handle that
enormous appetite for innovationat ASU and how he keeps up with
the changes in technology today.
But before we get into that, Iwant to take a moment as we
approach the end of the year tothank all of our listeners, all
(01:39):
of our subscribers, all thefolks who watch us here on
YouTube, thank you forcontinuing to follow the Rant
podcast.
I hope the content has beenvaluable.
I hope my conversations withleaders in the higher education
marketplace gives you a bit ofan insight into what's happening
today and what are some of theissues that we're going to have
(02:01):
to pay attention going forward.
Certainly, technology andespecially AI have been a big
part of the conversations we hadthis year, but also the enormous
changes that have been broughton by the Trump administration
in the higher educationmarketplace, as well as the rise
in the lack of confidence thatAmericans feel about higher
(02:22):
education and the drive to showmore value, more economic
mobility for learners who enterprograms of study.
We've had some great guests thisyear from Lev Gonic to Phil
Hill, to many others who havehelped us understand what's
shaping the higher educationmarketplace today.
(02:45):
And all this would not bepossible without our sponsors.
So I have to take a moment tothank our amazing sponsors who
make the Ramp Podcast possible.
I want to thank, of course,Arizona State University for
continuing to support the RampPodcast as we shine a spotlight
on innovation throughout thehigher education marketplace.
(03:06):
I also want to thank AllianceInternational University that's
making professional graduateprograms affordable and
available to Americansthroughout the country.
I also want to thank OpenClassrooms.
Open Classrooms had an amazingmilestone this year.
They received theiraccreditation from WASC.
They moved here from France,opened up shop in the US about
(03:28):
three years ago, and are nowaccredited in creating multiple
apprenticeship programs andprograms of study that lead to
good paying jobs.
Also, a big thank you toRisePoint.
I recently interviewed FernandoBlake Schmarr, and that episode
will be published in the nextfew weeks.
(03:51):
We talk about ROI and onlineprograms and how RisePoint
supports institutions trying togrow their footprint in the
online education marketplace.
A big thanks to REAP as well.
REAP Education is helpinglearners who either had a poor
(04:12):
experience in higher educationor who never went to get
reconnected to higher educationin their adult working life and
get the skills that they need inorder to compete in today's
economy.
A big thank you also to Ilusian.
Illusion continues to evolve andsupport higher education
institutions, big and small,throughout the country by
(04:32):
leveraging their enterpriseresource planning platforms and
providing data solutions tocolleges and universities across
the country.
I also want to thank EESG,Education Strategy Group.
Education Strategy Group ishelping states and institutions
throughout the country to comeup with strategies and
(04:53):
understand how to thrive in thisever-changing education
marketplace.
Also, a big thank you to CollegeFutures.
College Futures is also my dayjob.
They've been very supportive ofthe RAN podcast, helping to
spread the word about the workthat we're doing on the RAN
podcast and helping us findgreat guests like Michael
(05:15):
Iskowitz from the HEA Group totalk about how we are creating
more and better economicmobility for learners and how
we're going to measure thatgoing forward.
I also want to thank Branded andBrandon Bastide, the CEO.
Brand Ed was a sponsor at thebeginning of the year, and we
really appreciate the supportthat they gave us to help the
(05:36):
Rand Podcast continue to grow.
Without this support, the RandPodcast would not have been able
to see the tremendous growththat we experienced in 2025.
Our growth on YouTube has beentremendous.
We have now reached over 210,000views, well over 8,000 hours of
(05:59):
watch time, and we continue toadd more and more subscribers.
Last I checked, we were at morethan 4,500 subscribers.
We also continue to see steadygrowth in our audio platforms as
well.
So thanks to all of you forwatching us, for listening to
us, and continues to give usgreat feedback.
(06:20):
So with that backdrop, I hopeeverybody has a great end to
2025.
I'm looking forward tocontinuing the conversation in
2026.
And with that, please enjoy myconversation with Lev Gonig, CIO
of Arizona State University.
Lev, welcome to the RantPodcast.
(06:40):
Great to be with you.
It's good to have you, Lev, andthanks for taking time out of
your busy schedule.
I know there's always a lotgoing on at Arizona State
University, but thanks fortaking some time.
So as we launch into thispodcast interview, I know we've
got a lot to talk about, a lotgoing on at ASU and the AI
world.
(07:00):
But before we jump into allthat, let's level set a little
bit for our listeners.
Tell us about your role at ASUand how you and your boss and
partner, Michael Crow, has havecreated a culture of innovation
there at ASU over the last fewdecades.
SPEAKER_01 (07:17):
Great.
Thanks again for having me.
What I'd say is that my role asthe enterprise CIO, working for
Michael and the executive teamhere at ASU, is a combination of
stewardship of all of theutility functions that go into
running a huge enterpriseinstitution.
And at the same time, as apartner in co-designing and
(07:40):
thought leadership and strategicwork together to advance this
seemingly insatiable orientationtowards innovation that you uh
intimated.
And I think at ASU, it really isan unrelenting commitment to our
charter that focuses infundamentally on being
(08:01):
democratic in the sense ofmaking teaching and learning,
especially learning and studentsuccess, an essential of the
institution and mobilizing allof the technology tools that are
possible to advance studentsuccess, reduce the cost and the
burden of education, andfundamentally to prepare
(08:22):
students to have the opportunityto gain the skills that they'll
need for the workplace of thefuture today while they're at
the university.
SPEAKER_00 (08:30):
I appreciate using the term insatiable.
The university does have thisinsatiable drive toward
innovation, toward improving,toward democratizing access to a
great post-secondary experiencethat seems to be very
intentional.
Those of us who have had theopportunity to visit the various
functions that ASU see iteverywhere we go.
(08:53):
How do you keep up with it?
As you said, you're the guybehind the scenes.
You and your team are alwayshaving to go out there and
problem solve and try to figureout which technology will help
meet the goals that theuniversity is after.
And so many CIOs or CTOs are inthe no business.
How do you put you and your teamin the yes we can business?
SPEAKER_01 (09:16):
Yeah, it's a bit really important.
I guess I would say I'mgenetically predisposed to the
yes we can, and maybe that'swhat attracts a certain kind of
talent around Michael Crow,because there is a growth
mindset that is core to the sortof philosophical orientation to
all of the complexity of beingpart of an enterprise like ASU
(09:37):
or any other large complexorganization with a mission.
I think in terms of the tacticaland the operational issues, I
have always found that the bestway to actually learn something
is to teach it.
And so I've been writing andspeaking almost for 30 years
because I find that is the way Iactually get prepped to actually
(09:57):
get up to speed on what is goingon.
And I'm constantly asking peoplearound me, not only here at ASU,
but in my broader network that Ihave out there, for insights and
for what are you working on interms of experimental?
And are you trying thisparticular set of orientations
to the teaching and learningenvironment?
Or what are you doing in the HRarea along the way?
And so that that is a case ofunderstanding again, one of the
(10:20):
things that there is a littlebit of NIMBY stuff that happens
in especially in the technologyworld.
Well, that it's not inventedhere, it's not worth doing, not
at ASU, and certainly not forme, because if we've learned
anything in the last 20 years,we have found a way to partner
in a way that is not aboutsimply the transaction of a
(10:40):
vendor to a buyer relationship,to try to create more value to
actually help shape the way acommercial player can emerge
into the marketplace, but moregenerally to shape the
marketplace.
SPEAKER_00 (10:52):
I'm really glad you brought up that example.
You really do partner with allsorts of different entities to
bring to fruition thetechnology, the ideas, the
innovations that either acommercial or nonprofit partner
may be able to bring to bear andto help uh ASU complete its
mission.
Now, you just had one of yoursignature AI events recently
(11:14):
happened.
It was, I think it's titledGentic AI and the student
experience.
I think that's a perfect namefor an event today because we've
gone from just talking about therelease of Chat GPT and the
growth of LLMs throughout thecountry to now really talking
about a GENTIC AI.
First, tell us about the eventand what are some of the
(11:35):
interesting things that you cameacross there.
SPEAKER_01 (11:38):
It was a spectacular event in the following way.
Our expectations were that if weactually focused the
conversation on the studentoutcome, again, totally
appropriate for all of us, butcertainly for ASU, that we would
probably get maybe a couplehundred people from around the
country to come share what theywere doing and to get out of
this as only nerd speak, onlytechno babble, and to actually
(12:01):
start talking about earlyexperiments.
And what do we actually knowabout how students are thinking
about and making use of?
And as things happen in the ASUworld, I was traveling and
speaking, and we were invitingpeople individually to come to
campus to start sharing.
And all of a sudden, like itbecame clear that this could
really be a combustible moment,not just a couple of the usual
suspects getting together,telling war stories about how
(12:24):
hard it is to work with theacademics and so forth.
No, it became just a literallywe blew the roof off the actual
program with well over 650people participating from 25
countries around the worldcoming to again, not just to
listen, because we were veryintentional in design of this,
not to make this about sellingASU, because again, we have some
things to share, and we thinkwhat we're doing is actually
(12:46):
very much at the leading edge,but this was really about
sharing.
And we literally had over ahundred speakers of the 650
people there involved in oneway, shape, form, or another.
We solicited through paperproposals and poster sessions
and keynotes and the like, andreally it was a here's the best
evidence of why this was such aspecial event.
(13:07):
Friday at 11 o'clock on the lastday in the last session of the
event, standing room only.
Wow.
Now that's crazy.
Those of us who've been aroundthe academic event space know
that you can almost never planfor the last day because no
one's ever there.
But my point there is that therewas, there is, we tapped into a
moment in which there's thisincredible excitement and
(13:30):
interest around the applicationof the ability to translate the
nerd speak into English and haveit applied to how it gets used
in the learning environment.
And not like the very lastsession was actually a musician
talking about music and thecreative experience for classes.
So it wasn't just about how do Iuse this for computer science.
In fact, very little of it wasthe traditional computer
(13:52):
science.
A lot of it was the intersectionof what we've come to, what we
describe here at ASU aboutexperience AI, which is which
people can understand.
People want to experience AI.
They don't care whether or notit's generative AI or gentic AI,
right, or multimodal AI.
That's all nerd speak.
What people want is AI that theycan experience, experience for
(14:14):
purposes here of their learning.
And that what we were able tocapture was this extraordinary
breadth of interest, includingassessment, early assessments
from Australia, from Canada,from across the US, of people
actually studying the earlypieces.
So we now have a sense of wherethe baseline is as we continue
our collective journeys.
SPEAKER_00 (14:35):
So before we dive into some of the questions I
have around some of the usecases that you see emerging for
AI, and you're right, there'slots of nerds speak around this.
Some of it is probably still inthe realm of machine learning,
some of it is truly AI, and nowagentic AI, where we can turn
these agents loose to do somework on our behalf.
(14:56):
But before we go down that road,I work with a lot of colleges,
universities, and both inCalifornia and across the
country, where the college mayview ASU or uh Southern New
Hampshire or WGU and see some ofthe aspects of the deployment of
AI happening.
(15:16):
And they want to rush to thoseexamples, rush to those use
cases, but they have so muchwork to do on the back end to
actually be prepared to leverageAI.
What is some of the advice thatyou have for college and
university leaders to actuallybecome AI ready so that you're
not just buying products off theshelf, you're actually
(15:37):
identifying a problem to solve?
SPEAKER_01 (15:41):
To be sure, and again, what I would say here,
Eloy, is what we need to do isactually understand how to walk
on both sides of the fence.
The best way you know to predictthe future is to invent it.
The best way to invent thefuture is the start.
And so that that's on one leg.
And at the other side, you'reabsolutely 100% correct that you
(16:01):
actually have to set theconditions and the context for
why the faculty or the staff orthe student body should be
actually understanding why theinstitution is interested in
preparing students for the 21stcentury workforce, or why
students should be prepared tograpple with the ethics of AI,
(16:21):
or why students need tounderstand how, in fact, the
ability to do research anddiscover new science is going to
be radically transformed.
There is absolutely a stepbefore all of that, and that is
essentially creating communitiesof practice.
ASU began this journey now justabout three years ago, where we
understood that the first orderof business, while we had early
(16:42):
experimentations underway, wasto actually engage the faculty
community in a series ofconversations.
We knew coming out of thepandemic that the faculty under
through the pandemic understoodthat technology could be an ally
in a very disruptive moment, notbecause it was perfect, not
because we didn't have all kindsof challenges through the
(17:04):
pandemic with the technologiesthat we provided.
And we thought again, there'd bea couple hundred faculty at ASU
that would very quickly engagein conversation and early
experimentation.
And we were we've been blownaway.
Again, we have almost 6,000faculty uh teaching at ASU in
one way, shape, form, oranother.
And over 3,000 have gone througha program of essentially
structured learning that we,along with our colleagues at Ed
(17:28):
Plus, I know it's Phil work withhim, along with our provost
office, Nancy Gonzalez and herteam, created a curriculum
content that we've madeavailable.
And alongside of the sort ofself-paced learning that the
eight module learning that wecreated, we also began to create
community broad communities ofpractice with thousands of
faculty engaged, which now,three almost three years later,
(17:49):
is essentially inappropriatelylargely discipline-specific.
How are you and in your own,whether it's in the humanities,
looking at philosophy orEnglish, at this point, the
community practice needs to becontext really contextual?
Or if you're working inside abiomedical engineering lab,
those are all at this point allaround context-specific efforts.
And so we maintain thosecommunities of practice.
(18:12):
We engage intentionally.
We've created a faculty ethicscommittee where I'm constantly
asking for feedback because thisis not like one and done.
We understand there are allkinds of complexities associated
with the AI journey that we areon.
And we, certainly in central IT,we don't want to be presumptuous
to understand essentially whereall the biases and ethical
considerations need to be takeninto consideration.
(18:33):
And we have a research communitythat is constantly and in many
ways driving the technicalcutting edge, while at the same
time, we've got significant, Iwould say, commitments at ASU
back to our charter that focuseson equity and equitable access
to these tools a lot of the way.
So that's the juggling act thatis essentially much of it
(18:53):
critically important in additionto all the sort of leading edge
demonstrations of the art of thepossible.
And all I would say, whichagain, I think I know you will
very much resonate with this,but also to your listeners and
viewers, and that is that theseare still early days.
And again, we're privileged andlucky here at ASU to be working
on both sides, both the facultyengagement, the student
(19:15):
engagement, the staffengagement.
And one of the things that we'velearned, Eloy, in that regard,
is that we need to change, wehave to have a different kind of
mindset.
This is not about managingapplications like IT has done
forever.
This is a complete rethink ofthe ways in which we can use
technology to actually helpstudents instead of looking at
(19:36):
this as kind of data silos, it'sthe way most applications have
been developed over the last 30years, to think about this as
data rivers that can literallysupport students along their
entire journey and not onlystudents, but unlock the
opportunities to let subjectmatter experts in HR create AI
apps that work for HRprofessionals.
(19:56):
And the same thing for labprofessionals, rather than
saying, Oh, we have to wait.
For our technology people.
So we've developed the low-code,no-code platform technology,
which we call CreateAI.
And our job is to make sure thatthe campus community understands
its use and understands thatit's being guided by an ethical
consideration.
We call that principledinnovation here at ASU and get
(20:18):
feedback.
This last weekend, I was hangingout in the in our foot at the
football game, and a group ofstudent leaders were talking to
me exactly about this kind ofwork.
It's not the CIO writes a note,and all of a sudden, AI is
birthed all.
This is a series ofconversations, including the
ones that happen at a footballgame.
SPEAKER_00 (20:35):
Yeah, no, I would love to grab either uh Division
I football coach or athleticdirector to find out how they're
deploying AI, although theyprobably wouldn't want to tell
me because probably secret sauceat this point.
Based on what you're seeingright now, what are some really
interesting use cases foragentic AI in the student
experience?
Are there one or two that eitheryou're seeing at ASU emerge or
(20:58):
that through the this latestevent you had that you you found
really interesting?
SPEAKER_01 (21:03):
Yeah, I'd like to give you one of both just as an
example.
Again, this is not exhaustive,but just one of both.
So again, let's just level setthat the idea of an agentic AI
is that all of us have one whouse any AI at all have had one
relationship at least with oneagent.
Let's call that your favoritetool, whether that is taking a
look at Chat GPT or you're usingClaude or whatever tool that
(21:26):
you're using.
That's you and the agent.
But in the agentic age, theseare really an opportunity for
agents to actually be workingwith you and with each other,
agents being machine agents, toactually streamline workflows,
to create opportunities foraccelerating activities and for
discovery in ways that might notbe apparent to you if all you
(21:49):
were doing was having yourindividual either work in a
pre-AI era or even with a singleagent, your interactions.
Just two quick examples that youknow that I'd share with you.
One is that's easy tounderstand, I think, is the
process of actually creatingcurriculum.
And you could sure, you couldask ChatGPT, I'm about to teach
(22:10):
a course in microbiology, andI'd like you to give me a course
outline with all of the details.
Prompt, send.
All right.
But the truth is you've notreally described actually any of
the objectives, any of thecritical resources that need to
be uh engaged with, any of theways in which you want to assess
learning, what skills andcompetencies are actually going
(22:32):
to be will students actuallyreceive if they actually take
the journey on this microbiologycourse with you?
What uh opportunities are therefor study and or for work
afterwards?
At ESU, what we've done isactually set up an agentic
workflow that allows faculty toframe, again, in this low-code,
no-code fashion, everything thatstarts from learning objectives
(22:53):
to course outline, toassignments, to assessment.
Again, both in the form of shortassignments, short different
ways of leaning into thedifferent research that helps
you understand kind of wherestudents have historically found
challenges in a particular areaof the academic program, through
to what skills and assessmentsthat we know students will be
(23:16):
able to demonstrate coming outof it, what skills and
competencies they'll have, andthen actually help them
understand their journey goingforward.
Now, all of that is actuallywhere humans can be in the loop
as much as the designer, theinstructor or the instructional
designer wants to afford them.
But that what that does isenormous, not only does it
remove the administrivia of alot of the way in which course
(23:38):
design happens, it also is agreat way to understand uh the
opportunities to allow the agentto do the research on the back
end, whether it's new readingmaterials or new discoveries or
new opportunities for studentsto be able to participate in
things like hackathons or postersessions that again, the agent,
while you're sleeping, can goout and research essentially all
(24:01):
of these and bring them backtogether as what happens.
And on the commercial side,there's just so many interesting
agentic stories that arebeginning to unfold at ASU.
We're always interested in thetop of the funnel, which is to
say, student recruiting studentsinto the ASU environment.
There are terrific companiesthat are out there.
Again, I've just mentioned onethat we're particular we're
using at ASU now called CollegeVine, which again is an agentic
(24:24):
workflow that allows students tobe sharing their interests and
aspirations as they entercollege, colleges to be able to
actually work with the exchangeinfrastructure of the agentic
platform technology, it's to beable to indicate to students
that the level of our interestin having conversations with
them, and then using multimodalAI, that is, say, voice, text,
(24:45):
speech, and the like, to be ableto have to help students on
their journeys to a decision.
Those are just two simpleexamples of the ways in which
agentic AI is happening in realtime.
We see it all the way out to thealumni experience here at ASU,
right?
And we see it obviously all theway in on the other side to the
admissions journey.
SPEAKER_00 (25:03):
I think that last example is a great example.
The more and better informationwe can give to learners who are
thinking about going to college,particularly learners,
low-income learners or learnersthat don't have a very wide
social net, maybe, or the firstin their family to go to
college, just opening their eyesto the various possibilities of
various majors, what that majormeans to their career
(25:26):
aspirations, how to be prepared.
So there's so many use casesthat people complain all the
time there's not enough highschool guidance counts.
AI is certainly a way to getmore and better real-time
information to learners whenthey need it, wherever they can
get it.
So I think that's a great usecase.
Now, how do you think aboutprivacy?
I know you wrote recently aboutprivacy and data.
(25:50):
AI is all about getting more andmore data.
And a lot of people are growingconcerned about data privacy,
whether or not information thatthey're sharing as part of their
experience is being used totrain an AI model somewhere
else.
How do you think about privacyfrom the university enterprise
(26:11):
point of view?
SPEAKER_01 (26:14):
The central orientation is that in this age,
our biggest challenge andopportunity is to rethink trust.
How do you actually remainrelevant in a world in which
there is this massive diffusionof sharing, the sharing economy
that is underway that actuallyerodes a lot of the trust that
(26:38):
again we in higher educationhave taken for uh essentially
taken for granted that we alwayshave the impramater around we
are the trusted institution.
And because uh data privacy issuch a central issue in this
age, for the exact reasons thatyou indicate, our objective here
is to use the opportunity toeducate the campus community
(27:01):
into the importance ofunderstanding how the engine of
AI works and to indicate whatthe institution, again from the
enterprise, is doing to protectprivacy, security, personal
health information, but personalinformation in general,
intellectual property, and allthe things that actually, if you
(27:22):
didn't understand it, you mightthink somehow that all of those
are just being protected in yourconsumer commercial experience,
which they're not at all.
One of the things that we needto work on here is to understand
that this is not about the CIOor the council, uh the legal
council, the institutiondelivering it.
This is w about the framing ofhow we will actually deliver the
(27:47):
coin of the realm of this AIera, which is around building
trust.
We have to find a way toactually indicate and
differentiate the role of uhcoming to a university for
discovery or for the journey oflearning and understand that
it's a safe place around whichyou can have trust that it will
(28:08):
not be used for nefariouspurposes, or just incidentally
helping to tune a language modelwith the information that came
out of a lab where you thoughtyou were just doing what the
professor asked you to do.
SPEAKER_00 (28:22):
No, that's a great that's a great point.
And I think something for allcolleges and university leaders
to consider because it isultimately building the trust of
your learners, the trust of thecommunity, the trust of
employers, that the data you'reusing is protected and it is
accurate and is verifiable.
So good points to consider.
(28:42):
Now, let me ask you one lastquestion as we begin to wrap up.
Given the pace of change, thepace of transformation, and ASU
has been sitting right in themiddle of all this over the last
decade or so.
Where do you see this leadingASU over the next five years?
So if you're we're sitting heretalking five years from now,
(29:05):
what do you think thatconversation is going to be like
as we describe the impact of AIon the learning enterprise?
SPEAKER_01 (29:12):
I think I'll end where I started, which is here
at ASU, we genuinely have aNorth Star, which is unrelenting
focus on the mission.
And that won't change.
That won't change for now or forthe next five years.
We will be focused in on theways in which we can harness the
tools as they continue to matureand evolve in a fashion that
(29:35):
assures us that we're providingevery opportunity for students
to succeed.
And I have no doubt that even inthe next year or 18 months,
we're going to have a completelydifferent conversation about the
ways in which AI, as it evolves,continues to unlock that
possibility to advance a growthmindset.
And at the same time, to besure, there'll be all kinds of
ethical and important questionsthat we think about as we go
(29:58):
down the path together.
And I think the last word wouldbe we want to co-design this
effort with our faculty and withour students in a way that has
them owning their own destinies.
SPEAKER_00 (30:11):
All right.
On that note, Lev, thank you forjoining us here on the Rant
Podcast.
Thanks so much.
Great to see you.
Great to see you too.
Thanks for joining us,everybody.
You've been listening to myconversation with Lev Gonick,
CIO at Arizona State University.
We've been talking about agenticAI and the great innovations
happening at ASU and throughoutthe Learning Enterprise.
(30:32):
If you're watching us onYouTube, please hit subscribe,
continue to follow us.
And if you're listening to us onyour favorite audio podcast
platform, download our episodesand continue to follow us.
Thanks for joining us,everybody, and we'll see you all
soon.
Hi, this is the lawyer T S Oakley, and welcome
back to the Rand Podcast, thepodcast where we pull back the
curtain and break down thepeople, the policies, and the
politics of our higher educationsystem.
In this episode, I sit down withLev Gonick, the Chief
Information Officer at ArizonaState University.
(00:32):
Lev leads the technologyportfolio for the massively
innovative university, ArizonaState University.
Lev makes all of Michaeltechnology dreams come true.
And that is a tall order.
My conversation with Lev willtouch on the latest event at
(00:53):
Arizona State University calledAgentic AI and the Student
Experience.
Lev will talk about the eventand the overwhelming response he
got to the event from all acrossthe world.
Agentic AI, AI in general, andtechnology innovation are at the
center of the insatiableappetite for innovation at
(01:16):
Arizona State University.
So I'm looking forward tojumping into the conversation
with Lev and talking about howhe and his team handle that
enormous appetite for innovationat ASU and how he keeps up with
the changes in technology today.
But before we get into that, Iwant to take a moment as we
approach the end of the year tothank all of our listeners, all
(01:39):
of our subscribers, all thefolks who watch us here on
YouTube, thank you forcontinuing to follow the Rant
podcast.
I hope the content has beenvaluable.
I hope my conversations withleaders in the higher education
marketplace gives you a bit ofan insight into what's happening
today and what are some of theissues that we're going to have
(02:01):
to pay attention going forward.
Certainly, technology andespecially AI have been a big
part of the conversations we hadthis year, but also the enormous
changes that have been broughton by the Trump administration
in the higher educationmarketplace, as well as the rise
in the lack of confidence thatAmericans feel about higher
(02:22):
education and the drive to showmore value, more economic
mobility for learners who enterprograms of study.
We've had some great guests thisyear from Lev Gonic to Phil
Hill, to many others who havehelped us understand what's
shaping the higher educationmarketplace today.
(02:45):
And all this would not bepossible without our sponsors.
So I have to take a moment tothank our amazing sponsors who
make the Ramp Podcast possible.
I want to thank, of course,Arizona State University for
continuing to support the RampPodcast as we shine a spotlight
on innovation throughout thehigher education marketplace.
(03:06):
I also want to thank AllianceInternational University that's
making professional graduateprograms affordable and
available to Americansthroughout the country.
I also want to thank OpenClassrooms.
Open Classrooms had an amazingmilestone this year.
They received theiraccreditation from WASC.
They moved here from France,opened up shop in the US about
(03:28):
three years ago, and are nowaccredited in creating multiple
apprenticeship programs andprograms of study that lead to
good paying jobs.
Also, a big thank you toRisePoint.
I recently interviewed FernandoBlake Schmarr, and that episode
will be published in the nextfew weeks.
(03:51):
We talk about ROI and onlineprograms and how RisePoint
supports institutions trying togrow their footprint in the
online education marketplace.
A big thanks to REAP as well.
REAP Education is helpinglearners who either had a poor
(04:12):
experience in higher educationor who never went to get
reconnected to higher educationin their adult working life and
get the skills that they need inorder to compete in today's
economy.
A big thank you also to Ilusian.
Illusion continues to evolve andsupport higher education
institutions, big and small,throughout the country by
(04:32):
leveraging their enterpriseresource planning platforms and
providing data solutions tocolleges and universities across
the country.
I also want to thank EESG,Education Strategy Group.
Education Strategy Group ishelping states and institutions
throughout the country to comeup with strategies and
(04:53):
understand how to thrive in thisever-changing education
marketplace.
Also, a big thank you to CollegeFutures.
College Futures is also my dayjob.
They've been very supportive ofthe RAN podcast, helping to
spread the word about the workthat we're doing on the RAN
podcast and helping us findgreat guests like Michael
(05:15):
Iskowitz from the HEA Group totalk about how we are creating
more and better economicmobility for learners and how
we're going to measure thatgoing forward.
I also want to thank Branded andBrandon Bastide, the CEO.
Brand Ed was a sponsor at thebeginning of the year, and we
really appreciate the supportthat they gave us to help the
(05:36):
Rand Podcast continue to grow.
Without this support, the RandPodcast would not have been able
to see the tremendous growththat we experienced in 2025.
Our growth on YouTube has beentremendous.
We have now reached over 210,000views, well over 8,000 hours of
(05:59):
watch time, and we continue toadd more and more subscribers.
Last I checked, we were at morethan 4,500 subscribers.
We also continue to see steadygrowth in our audio platforms as
well.
So thanks to all of you forwatching us, for listening to
us, and continues to give usgreat feedback.
(06:20):
So with that backdrop, I hopeeverybody has a great end to
2025.
I'm looking forward tocontinuing the conversation in
2026.
And with that, please enjoy myconversation with Lev Gonig, CIO
of Arizona State University.
Lev, welcome to the RantPodcast.
(06:40):
Great to be with you.
It's good to have you, Lev, andthanks for taking time out of
your busy schedule.
I know there's always a lotgoing on at Arizona State
University, but thanks fortaking some time.
So as we launch into thispodcast interview, I know we've
got a lot to talk about, a lotgoing on at ASU and the AI
world.
(07:00):
But before we jump into allthat, let's level set a little
bit for our listeners.
Tell us about your role at ASUand how you and your boss and
partner, Michael Crow, has havecreated a culture of innovation
there at ASU over the last fewdecades.
SPEAKER_01 (07:17):
Great.
Thanks again for having me.
What I'd say is that my role asthe enterprise CIO, working for
Michael and the executive teamhere at ASU, is a combination of
stewardship of all of theutility functions that go into
running a huge enterpriseinstitution.
And at the same time, as apartner in co-designing and
(07:40):
thought leadership and strategicwork together to advance this
seemingly insatiable orientationtowards innovation that you uh
intimated.
And I think at ASU, it really isan unrelenting commitment to our
charter that focuses infundamentally on being
(08:01):
democratic in the sense ofmaking teaching and learning,
especially learning and studentsuccess, an essential of the
institution and mobilizing allof the technology tools that are
possible to advance studentsuccess, reduce the cost and the
burden of education, andfundamentally to prepare
(08:22):
students to have the opportunityto gain the skills that they'll
need for the workplace of thefuture today while they're at
the university.
SPEAKER_00 (08:30):
I appreciate using the term insatiable.
The university does have thisinsatiable drive toward
innovation, toward improving,toward democratizing access to a
great post-secondary experiencethat seems to be very
intentional.
Those of us who have had theopportunity to visit the various
functions that ASU see iteverywhere we go.
(08:53):
How do you keep up with it?
As you said, you're the guybehind the scenes.
You and your team are alwayshaving to go out there and
problem solve and try to figureout which technology will help
meet the goals that theuniversity is after.
And so many CIOs or CTOs are inthe no business.
How do you put you and your teamin the yes we can business?
SPEAKER_01 (09:16):
Yeah, it's a bit really important.
I guess I would say I'mgenetically predisposed to the
yes we can, and maybe that'swhat attracts a certain kind of
talent around Michael Crow,because there is a growth
mindset that is core to the sortof philosophical orientation to
all of the complexity of beingpart of an enterprise like ASU
(09:37):
or any other large complexorganization with a mission.
I think in terms of the tacticaland the operational issues, I
have always found that the bestway to actually learn something
is to teach it.
And so I've been writing andspeaking almost for 30 years
because I find that is the way Iactually get prepped to actually
(09:57):
get up to speed on what is goingon.
And I'm constantly asking peoplearound me, not only here at ASU,
but in my broader network that Ihave out there, for insights and
for what are you working on interms of experimental?
And are you trying thisparticular set of orientations
to the teaching and learningenvironment?
Or what are you doing in the HRarea along the way?
And so that that is a case ofunderstanding again, one of the
(10:20):
things that there is a littlebit of NIMBY stuff that happens
in especially in the technologyworld.
Well, that it's not inventedhere, it's not worth doing, not
at ASU, and certainly not forme, because if we've learned
anything in the last 20 years,we have found a way to partner
in a way that is not aboutsimply the transaction of a
(10:40):
vendor to a buyer relationship,to try to create more value to
actually help shape the way acommercial player can emerge
into the marketplace, but moregenerally to shape the
marketplace.
SPEAKER_00 (10:52):
I'm really glad you brought up that example.
You really do partner with allsorts of different entities to
bring to fruition thetechnology, the ideas, the
innovations that either acommercial or nonprofit partner
may be able to bring to bear andto help uh ASU complete its
mission.
Now, you just had one of yoursignature AI events recently
(11:14):
happened.
It was, I think it's titledGentic AI and the student
experience.
I think that's a perfect namefor an event today because we've
gone from just talking about therelease of Chat GPT and the
growth of LLMs throughout thecountry to now really talking
about a GENTIC AI.
First, tell us about the eventand what are some of the
(11:35):
interesting things that you cameacross there.
SPEAKER_01 (11:38):
It was a spectacular event in the following way.
Our expectations were that if weactually focused the
conversation on the studentoutcome, again, totally
appropriate for all of us, butcertainly for ASU, that we would
probably get maybe a couplehundred people from around the
country to come share what theywere doing and to get out of
this as only nerd speak, onlytechno babble, and to actually
(12:01):
start talking about earlyexperiments.
And what do we actually knowabout how students are thinking
about and making use of?
And as things happen in the ASUworld, I was traveling and
speaking, and we were invitingpeople individually to come to
campus to start sharing.
And all of a sudden, like itbecame clear that this could
really be a combustible moment,not just a couple of the usual
suspects getting together,telling war stories about how
(12:24):
hard it is to work with theacademics and so forth.
No, it became just a literallywe blew the roof off the actual
program with well over 650people participating from 25
countries around the worldcoming to again, not just to
listen, because we were veryintentional in design of this,
not to make this about sellingASU, because again, we have some
things to share, and we thinkwhat we're doing is actually
(12:46):
very much at the leading edge,but this was really about
sharing.
And we literally had over ahundred speakers of the 650
people there involved in oneway, shape, form, or another.
We solicited through paperproposals and poster sessions
and keynotes and the like, andreally it was a here's the best
evidence of why this was such aspecial event.
(13:07):
Friday at 11 o'clock on the lastday in the last session of the
event, standing room only.
Wow.
Now that's crazy.
Those of us who've been aroundthe academic event space know
that you can almost never planfor the last day because no
one's ever there.
But my point there is that therewas, there is, we tapped into a
moment in which there's thisincredible excitement and
(13:30):
interest around the applicationof the ability to translate the
nerd speak into English and haveit applied to how it gets used
in the learning environment.
And not like the very lastsession was actually a musician
talking about music and thecreative experience for classes.
So it wasn't just about how do Iuse this for computer science.
In fact, very little of it wasthe traditional computer
(13:52):
science.
A lot of it was the intersectionof what we've come to, what we
describe here at ASU aboutexperience AI, which is which
people can understand.
People want to experience AI.
They don't care whether or notit's generative AI or gentic AI,
right, or multimodal AI.
That's all nerd speak.
What people want is AI that theycan experience, experience for
(14:14):
purposes here of their learning.
And that what we were able tocapture was this extraordinary
breadth of interest, includingassessment, early assessments
from Australia, from Canada,from across the US, of people
actually studying the earlypieces.
So we now have a sense of wherethe baseline is as we continue
our collective journeys.
SPEAKER_00 (14:35):
So before we dive into some of the questions I
have around some of the usecases that you see emerging for
AI, and you're right, there'slots of nerds speak around this.
Some of it is probably still inthe realm of machine learning,
some of it is truly AI, and nowagentic AI, where we can turn
these agents loose to do somework on our behalf.
(14:56):
But before we go down that road,I work with a lot of colleges,
universities, and both inCalifornia and across the
country, where the college mayview ASU or uh Southern New
Hampshire or WGU and see some ofthe aspects of the deployment of
AI happening.
(15:16):
And they want to rush to thoseexamples, rush to those use
cases, but they have so muchwork to do on the back end to
actually be prepared to leverageAI.
What is some of the advice thatyou have for college and
university leaders to actuallybecome AI ready so that you're
not just buying products off theshelf, you're actually
(15:37):
identifying a problem to solve?
SPEAKER_01 (15:41):
To be sure, and again, what I would say here,
Eloy, is what we need to do isactually understand how to walk
on both sides of the fence.
The best way you know to predictthe future is to invent it.
The best way to invent thefuture is the start.
And so that that's on one leg.
And at the other side, you'reabsolutely 100% correct that you
(16:01):
actually have to set theconditions and the context for
why the faculty or the staff orthe student body should be
actually understanding why theinstitution is interested in
preparing students for the 21stcentury workforce, or why
students should be prepared tograpple with the ethics of AI,
(16:21):
or why students need tounderstand how, in fact, the
ability to do research anddiscover new science is going to
be radically transformed.
There is absolutely a stepbefore all of that, and that is
essentially creating communitiesof practice.
ASU began this journey now justabout three years ago, where we
understood that the first orderof business, while we had early
(16:42):
experimentations underway, wasto actually engage the faculty
community in a series ofconversations.
We knew coming out of thepandemic that the faculty under
through the pandemic understoodthat technology could be an ally
in a very disruptive moment, notbecause it was perfect, not
because we didn't have all kindsof challenges through the
(17:04):
pandemic with the technologiesthat we provided.
And we thought again, there'd bea couple hundred faculty at ASU
that would very quickly engagein conversation and early
experimentation.
And we were we've been blownaway.
Again, we have almost 6,000faculty uh teaching at ASU in
one way, shape, form, oranother.
And over 3,000 have gone througha program of essentially
structured learning that we,along with our colleagues at Ed
(17:28):
Plus, I know it's Phil work withhim, along with our provost
office, Nancy Gonzalez and herteam, created a curriculum
content that we've madeavailable.
And alongside of the sort ofself-paced learning that the
eight module learning that wecreated, we also began to create
community broad communities ofpractice with thousands of
faculty engaged, which now,three almost three years later,
(17:49):
is essentially inappropriatelylargely discipline-specific.
How are you and in your own,whether it's in the humanities,
looking at philosophy orEnglish, at this point, the
community practice needs to becontext really contextual?
Or if you're working inside abiomedical engineering lab,
those are all at this point allaround context-specific efforts.
And so we maintain thosecommunities of practice.
(18:12):
We engage intentionally.
We've created a faculty ethicscommittee where I'm constantly
asking for feedback because thisis not like one and done.
We understand there are allkinds of complexities associated
with the AI journey that we areon.
And we, certainly in central IT,we don't want to be presumptuous
to understand essentially whereall the biases and ethical
considerations need to be takeninto consideration.
(18:33):
And we have a research communitythat is constantly and in many
ways driving the technicalcutting edge, while at the same
time, we've got significant, Iwould say, commitments at ASU
back to our charter that focuseson equity and equitable access
to these tools a lot of the way.
So that's the juggling act thatis essentially much of it
(18:53):
critically important in additionto all the sort of leading edge
demonstrations of the art of thepossible.
And all I would say, whichagain, I think I know you will
very much resonate with this,but also to your listeners and
viewers, and that is that theseare still early days.
And again, we're privileged andlucky here at ASU to be working
on both sides, both the facultyengagement, the student
(19:15):
engagement, the staffengagement.
And one of the things that we'velearned, Eloy, in that regard,
is that we need to change, wehave to have a different kind of
mindset.
This is not about managingapplications like IT has done
forever.
This is a complete rethink ofthe ways in which we can use
technology to actually helpstudents instead of looking at
(19:36):
this as kind of data silos, it'sthe way most applications have
been developed over the last 30years, to think about this as
data rivers that can literallysupport students along their
entire journey and not onlystudents, but unlock the
opportunities to let subjectmatter experts in HR create AI
apps that work for HRprofessionals.
(19:56):
And the same thing for labprofessionals, rather than
saying, Oh, we have to wait.
For our technology people.
So we've developed the low-code,no-code platform technology,
which we call CreateAI.
And our job is to make sure thatthe campus community understands
its use and understands thatit's being guided by an ethical
consideration.
We call that principledinnovation here at ASU and get
(20:18):
feedback.
This last weekend, I was hangingout in the in our foot at the
football game, and a group ofstudent leaders were talking to
me exactly about this kind ofwork.
It's not the CIO writes a note,and all of a sudden, AI is
birthed all.
This is a series ofconversations, including the
ones that happen at a footballgame.
SPEAKER_00 (20:35):
Yeah, no, I would love to grab either uh Division
I football coach or athleticdirector to find out how they're
deploying AI, although theyprobably wouldn't want to tell
me because probably secret sauceat this point.
Based on what you're seeingright now, what are some really
interesting use cases foragentic AI in the student
experience?
Are there one or two that eitheryou're seeing at ASU emerge or
(20:58):
that through the this latestevent you had that you you found
really interesting?
SPEAKER_01 (21:03):
Yeah, I'd like to give you one of both just as an
example.
Again, this is not exhaustive,but just one of both.
So again, let's just level setthat the idea of an agentic AI
is that all of us have one whouse any AI at all have had one
relationship at least with oneagent.
Let's call that your favoritetool, whether that is taking a
look at Chat GPT or you're usingClaude or whatever tool that
(21:26):
you're using.
That's you and the agent.
But in the agentic age, theseare really an opportunity for
agents to actually be workingwith you and with each other,
agents being machine agents, toactually streamline workflows,
to create opportunities foraccelerating activities and for
discovery in ways that might notbe apparent to you if all you
(21:49):
were doing was having yourindividual either work in a
pre-AI era or even with a singleagent, your interactions.
Just two quick examples that youknow that I'd share with you.
One is that's easy tounderstand, I think, is the
process of actually creatingcurriculum.
And you could sure, you couldask ChatGPT, I'm about to teach
(22:10):
a course in microbiology, andI'd like you to give me a course
outline with all of the details.
Prompt, send.
All right.
But the truth is you've notreally described actually any of
the objectives, any of thecritical resources that need to
be uh engaged with, any of theways in which you want to assess
learning, what skills andcompetencies are actually going
(22:32):
to be will students actuallyreceive if they actually take
the journey on this microbiologycourse with you?
What uh opportunities are therefor study and or for work
afterwards?
At ESU, what we've done isactually set up an agentic
workflow that allows faculty toframe, again, in this low-code,
no-code fashion, everything thatstarts from learning objectives
(22:53):
to course outline, toassignments, to assessment.
Again, both in the form of shortassignments, short different
ways of leaning into thedifferent research that helps
you understand kind of wherestudents have historically found
challenges in a particular areaof the academic program, through
to what skills and assessmentsthat we know students will be
(23:16):
able to demonstrate coming outof it, what skills and
competencies they'll have, andthen actually help them
understand their journey goingforward.
Now, all of that is actuallywhere humans can be in the loop
as much as the designer, theinstructor or the instructional
designer wants to afford them.
But that what that does isenormous, not only does it
remove the administrivia of alot of the way in which course
(23:38):
design happens, it also is agreat way to understand uh the
opportunities to allow the agentto do the research on the back
end, whether it's new readingmaterials or new discoveries or
new opportunities for studentsto be able to participate in
things like hackathons or postersessions that again, the agent,
while you're sleeping, can goout and research essentially all
(24:01):
of these and bring them backtogether as what happens.
And on the commercial side,there's just so many interesting
agentic stories that arebeginning to unfold at ASU.
We're always interested in thetop of the funnel, which is to
say, student recruiting studentsinto the ASU environment.
There are terrific companiesthat are out there.
Again, I've just mentioned onethat we're particular we're
using at ASU now called CollegeVine, which again is an agentic
(24:24):
workflow that allows students tobe sharing their interests and
aspirations as they entercollege, colleges to be able to
actually work with the exchangeinfrastructure of the agentic
platform technology, it's to beable to indicate to students
that the level of our interestin having conversations with
them, and then using multimodalAI, that is, say, voice, text,
(24:45):
speech, and the like, to be ableto have to help students on
their journeys to a decision.
Those are just two simpleexamples of the ways in which
agentic AI is happening in realtime.
We see it all the way out to thealumni experience here at ASU,
right?
And we see it obviously all theway in on the other side to the
admissions journey.
SPEAKER_00 (25:03):
I think that last example is a great example.
The more and better informationwe can give to learners who are
thinking about going to college,particularly learners,
low-income learners or learnersthat don't have a very wide
social net, maybe, or the firstin their family to go to
college, just opening their eyesto the various possibilities of
various majors, what that majormeans to their career
(25:26):
aspirations, how to be prepared.
So there's so many use casesthat people complain all the
time there's not enough highschool guidance counts.
AI is certainly a way to getmore and better real-time
information to learners whenthey need it, wherever they can
get it.
So I think that's a great usecase.
Now, how do you think aboutprivacy?
I know you wrote recently aboutprivacy and data.
(25:50):
AI is all about getting more andmore data.
And a lot of people are growingconcerned about data privacy,
whether or not information thatthey're sharing as part of their
experience is being used totrain an AI model somewhere
else.
How do you think about privacyfrom the university enterprise
(26:11):
point of view?
SPEAKER_01 (26:14):
The central orientation is that in this age,
our biggest challenge andopportunity is to rethink trust.
How do you actually remainrelevant in a world in which
there is this massive diffusionof sharing, the sharing economy
that is underway that actuallyerodes a lot of the trust that
(26:38):
again we in higher educationhave taken for uh essentially
taken for granted that we alwayshave the impramater around we
are the trusted institution.
And because uh data privacy issuch a central issue in this
age, for the exact reasons thatyou indicate, our objective here
is to use the opportunity toeducate the campus community
(27:01):
into the importance ofunderstanding how the engine of
AI works and to indicate whatthe institution, again from the
enterprise, is doing to protectprivacy, security, personal
health information, but personalinformation in general,
intellectual property, and allthe things that actually, if you
(27:22):
didn't understand it, you mightthink somehow that all of those
are just being protected in yourconsumer commercial experience,
which they're not at all.
One of the things that we needto work on here is to understand
that this is not about the CIOor the council, uh the legal
council, the institutiondelivering it.
This is w about the framing ofhow we will actually deliver the
(27:47):
coin of the realm of this AIera, which is around building
trust.
We have to find a way toactually indicate and
differentiate the role of uhcoming to a university for
discovery or for the journey oflearning and understand that
it's a safe place around whichyou can have trust that it will
(28:08):
not be used for nefariouspurposes, or just incidentally
helping to tune a language modelwith the information that came
out of a lab where you thoughtyou were just doing what the
professor asked you to do.
SPEAKER_00 (28:22):
No, that's a great that's a great point.
And I think something for allcolleges and university leaders
to consider because it isultimately building the trust of
your learners, the trust of thecommunity, the trust of
employers, that the data you'reusing is protected and it is
accurate and is verifiable.
So good points to consider.
(28:42):
Now, let me ask you one lastquestion as we begin to wrap up.
Given the pace of change, thepace of transformation, and ASU
has been sitting right in themiddle of all this over the last
decade or so.
Where do you see this leadingASU over the next five years?
So if you're we're sitting heretalking five years from now,
(29:05):
what do you think thatconversation is going to be like
as we describe the impact of AIon the learning enterprise?
SPEAKER_01 (29:12):
I think I'll end where I started, which is here
at ASU, we genuinely have aNorth Star, which is unrelenting
focus on the mission.
And that won't change.
That won't change for now or forthe next five years.
We will be focused in on theways in which we can harness the
tools as they continue to matureand evolve in a fashion that
(29:35):
assures us that we're providingevery opportunity for students
to succeed.
And I have no doubt that even inthe next year or 18 months,
we're going to have a completelydifferent conversation about the
ways in which AI, as it evolves,continues to unlock that
possibility to advance a growthmindset.
And at the same time, to besure, there'll be all kinds of
ethical and important questionsthat we think about as we go
(29:58):
down the path together.
And I think the last word wouldbe we want to co-design this
effort with our faculty and withour students in a way that has
them owning their own destinies.
SPEAKER_00 (30:11):
All right.
On that note, Lev, thank you forjoining us here on the Rant
Podcast.
Thanks so much.
Great to see you.
Great to see you too.
Thanks for joining us,everybody.
You've been listening to myconversation with Lev Gonick,
CIO at Arizona State University.
We've been talking about agenticAI and the great innovations
happening at ASU and throughoutthe Learning Enterprise.
(30:32):
If you're watching us onYouTube, please hit subscribe,
continue to follow us.
And if you're listening to us onyour favorite audio podcast
platform, download our episodesand continue to follow us.
Thanks for joining us,everybody, and we'll see you all
soon.
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