How UMGC Is Building Accountable AI Around Student Outcomes

by Presidents Forum | May 22, 2026 | Innovation

How UMGC Is Building Accountable AI Around Student Outcomes

UMGC’s AI strategy starts with governance

University of Maryland Global Campus is approaching AI adoption with a clear institutional principle: innovation only matters if it improves outcomes for students.

President Gregory Fowler describes a strategy built around governance, measurement, and practical implementation rather than experimentation for its own sake. The university has already implemented institution-wide AI training and established an AI Governance Board to ensure adoption remains aligned with institutional mission and student support goals.

The approach reflects a broader shift happening across higher education. Institutions are moving beyond curiosity about AI and focusing on how it can responsibly improve student success and operational effectiveness.

Why UMGC built a closed AI testing environment

UMGC launched nebulaONE as a controlled environment where faculty and staff can safely test AI tools, concepts, and workflows before wider deployment.

More than 300 team members are already using the platform.

The goal is not unrestricted experimentation, it is structured evaluation that allows the institution to identify where AI creates value, where it falls short, and how it can be implemented responsibly.

This type of infrastructure is becoming increasingly important as institutions look for ways to balance innovation with governance and accountability.

How AI is being applied to support students

UMGC is focusing AI adoption on practical student-facing applications.

Conversational AI is helping identify and support struggling learners earlier in the student journey. In the Registrar’s Office, transcript review processes that were previously manual are now partly automated, allowing staff to focus more attention on complex cases that require judgment and intervention.

Career Services has also integrated AI into resume review and mock interview preparation. These tools provide students with more opportunities for practice and faster feedback than traditional one-on-one support models alone can provide at scale.

The focus throughout is operational support that strengthens human-centered services rather than replacing them.

Why measurement matters in AI adoption

AI should function as a strategic enabler, not a replacement for teaching, advising, or institutional judgment.

That requires continuous measurement.

UMGC is evaluating adoption rates, operational outcomes, and areas where systems underperform. The institution then adjusts implementation based on those findings.

This approach reflects a growing expectation across higher education that AI adoption should be tied to measurable student impact rather than broad claims about innovation.

What accountable innovation looks like

The question is no longer whether AI is interesting or technically capable. The question is whether institutions can deploy it ethically, transparently, and in ways that genuinely improve student outcomes.

For UMGC, accountable innovation means governance, human oversight, operational measurement, and a consistent focus on serving learners more effectively.

Transcript

0:03
When we talk about innovation at UMGC, I tell our team all the time we’re not here to chase bright, shiny objects.

0:10
Our approach to AI has been deliberate.

0:13
We’re providing AI training for every team member,

0:15
as a baseline, not as an aspiration.

0:18
We established an AI Governance Board to make sure adoption stays aligned with our mission and our obligation to our learners.

0:25
And we adopted nebulaONE as a closed environment where faculty and staff can test new tools, concepts, and strategies.

0:32
More than 300 team members are using it now.

0:35
That infrastructure matters.

0:36
Because the real question is not whether AI is interesting, it is whether it actually helps us serve students better.

0:42
So we’re being very specific about where to apply it.

0:45
Conversational AI now guides earlier outreach to learners who may be struggling.

0:50
In our Registrar’s office,

0:51
transcript review, which used to be largely manual, is now partly automated – freeing staff members to focus on the cases that need real judgment or intervention.

1:01
Similarly, Career Services have integrated AI into resume editing and mock interviews, giving students more practice and faster feedback than we could ever provide one-on-one.

1:10
Let me be clear.

1:12
AI is not replacing teaching, advising, or judgment.

1:15
It is a strategic enabler.

1:17
The way we know it is working is through measurement of outcomes, of adoption, of the areas where it comes up short.

1:24
Then we adjust based on what we learn.

1:27
That is what accountable innovation looks like here –

1:29
practical, ethical and always tested against the benchmark of whether it genuinely serves the people who partner with us on their learning journeys.

Accountable Innovation with AI: Building Trust in Higher Education

by Presidents Forum | May 13, 2026 | Innovation

Jessica Smagler, Head of Research and Outcomes, Kyron Learning

Across higher education, the most common question about AI is no longer “what can it do?” It’s “how do we know it will behave?” That question reflects something important about where the sector stands right now: enthusiasm is no longer the barrier to adoption. Trust is.

Trust in AI isn’t built through promises – it’s built through systems. Without clear internal accountability structures, AI tools operate on good faith alone – and good faith isn’t a governance model.

Institutions evaluating AI-powered tools should look for four interlocking commitments, treated not as product features but as obligations: guardrails, benchmarks, educator control, and a foundation in learning science.

The first line of that accountability is governance – specifically, the guardrails that define how AI is permitted to behave.

Guardrails Built for Learning

AI chatbots routinely welcome off-topic conversations, taking focus away from intended course content and derailing learning goals. Without strict guardrails to ensure that AI behavior stays aligned with education, safety, and institutional expectations, the integrity of the learning experience is at risk.

In the edtech space, guardrails should operate at two levels. One is educational, making sure the AI stays within lesson boundaries, supports reasoning without shortcuts, and redirects students who go off course. The other is around student security and privacy, ensuring student data is protected, sensitive information is automatically redacted, and access to systems remains tightly controlled. And these guardrails should be structural rather than add-ons, built into how the system works from the ground up, not applied as a filter after the fact.

Neither layer is visible to students but both matter to the administrators and instructors who are responsible for what happens in their courses. Together, these are guardrails that institutions can trust and hold companies accountable to, because in education, responsible behavior must be verifiable, not assumed.

Benchmarking for Measurable Results

Guardrails define how an AI system should behave. Benchmarking is how companies prove that it does – and how institutions can hold them to it. Without continuous measurement, guardrails are a promise rather than a practice.

In practice, benchmarking should also operate at two levels. Continuous benchmarking should be run against real learner interactions to detect behavioral drift and measure ongoing alignment with learning objectives. Periodic broader evaluations – run across curated datasets in multiple academic domains – should test for safety, instructional integrity, and consistency.

Critically, institutions should expect AI providers to share benchmarking results openly. A track record that institutions can point to is what separates accountable innovation from well-intentioned experimentation.

End to End Educator Control

AI should amplify great instructors – not replace them. Human oversight is an essential component of AI-powered instruction and should extend across the entire learning cycle, from content creation to the student experience.

At Kyron, for example, no lesson reaches a student without educator review and approval. Instructors set the learning objectives that shape what our AI generates, and retain full editorial control before anything is deployed. This process ensures that what students experience is always aligned to institutional goals.

Educator control should not end once a lesson is deployed to learners. Products should offer visibility into what students are struggling with in aggregate and at the individual learner level, allowing faculty to intervene, adjust, and improve. Insight into misconceptions creates a feedback loop that keeps instructors and institutions informed on student progress.

Grounded in Learning Science

Responsible AI providers don’t stop at governance and oversight. They are also accountable for whether students actually learn. Rooting instruction in established learning science frameworks – like Chi and Wylie’s ICAP model and Vygotsky’s Zone of Proximal Development – isn’t just good teaching. It is a standard that AI providers should hold themselves to and a standard institutions should expect when adopting AI-powered instruction.

Decades of research have made clear that real learning doesn’t happen by giving students answers. It happens when students are encouraged to think critically, reason logically, and develop conceptual understanding. It happens when lessons are intentionally structured to achieve clear learning goals.

A landmark study by Graesser and Person found that 92% of student questions focused on surface facts rather than deeper reasoning, meaning most misunderstandings go undetected and unaddressed. Because students can so easily appear engaged without building true conceptual understanding, instruction must be intentionally designed to surface reasoning and guide deeper thinking.

When AI providers root their tools in learning science, they are making a verifiable commitment to student outcomes – not just a promise of engagement.

This is Accountable Innovation

AI in education demands more than innovation, it demands accountability. Institutions have a right to ask AI providers how they know their tools will behave, and AI providers have an obligation to answer concretely. Organizations using AI must do so in ways that are safe for students and transparent to institutions. By setting guardrails and benchmarks, keeping educators in control throughout, and grounding tools in learning science, we can be confident that we are innovating responsibly.

At Kyron, our commitment to safe, accountable AI has helped us build enduring partnerships with institutions like Miami Dade College and Western Governors University, while creating opportunities to collaborate with forward-looking colleges like Rio Salado College and established curriculum companies like McGraw Hill. When we answer questions with evidence rather than promises, we build the kind of trust that makes responsible AI adoption possible, both for our partners and for the students they serve.

Interested in learning more about Kyron Learning? Visit www.kyronlearning.com or connect with our team to get started.

May Update: Accountable Innovation in Practice

by Presidents Forum | May 6, 2026 | Innovation

May Update: Accountable Innovation in Practice

What does accountable innovation mean in higher education

Accountable innovation is becoming the defining expectation for higher education leaders.

Across the Presidents Forum network, this means designing new models that are not only innovative but also measurable. Institutions are focusing on flexible pathways for working learners, stronger alignment between education and workforce opportunity, and delivery models that reflect how students actually live and learn.

The emphasis is clear: innovation must lead to better outcomes, not just new ideas.

How institutions are putting innovation into practice

Institutions are translating this principle into concrete changes.

Flexible scheduling and online delivery are being paired with clearer pathways to completion. Programs are being designed with employer input to ensure relevance. Student support models are expanding to address barriers outside the classroom.

These changes reflect a broader shift. The goal is not access alone. It is access that leads to completion, employment, and long-term mobility.

What is happening in federal policy right now

At the federal level, the Department of Education’s AIM negotiated rulemaking is reinforcing this shift.

The first week of negotiations signaled a move away from a compliance-driven system toward one focused on outcomes, value, and consumer protection. At the same time, the proposals introduce new expectations around transparency and legal compliance.

Negotiators worked through a large portion of the draft text, but key issues remain unresolved. Areas such as outcomes-based accountability and accreditor flexibility continue to generate debate.

The second round of negotiations, scheduled for May 18 to 22, will be critical in shaping how these policies take final form.

Why policymakers are focused on outcomes and value

The direction of policy reflects broader public expectations.

Students, families, and policymakers are asking more direct questions about return on investment. They want to understand how education leads to employment, earnings, and career advancement.

This is driving a shift toward program-level outcomes, clearer disclosures, and stronger accountability frameworks. Institutions that can demonstrate value will be better positioned in this environment.

What this means for institutional strategy

Higher education is entering a period where innovation and accountability are closely linked.

Institutions will need to align program design, student support, and data systems with clear outcome measures. They will also need to communicate those outcomes effectively to policymakers and the public.

The opportunity is significant. Institutions that can demonstrate both innovation and results will define the next era of higher education.

The bottom line

Accountable innovation is no longer optional.

It is the standard by which institutions will be evaluated, funded, and trusted.

Transcript

Shalise Obray: Our theme for May is Accountable Innovation in Practice. Across our network, accountable innovation looks like flexible pathways for working learners, stronger alignment between education and opportunity, and new models that meet students where they are, while holding ourselves to clear standards for quality, value, and results.

On the policy front, we’re tracking the Department of Education’s AIM negotiated rulemaking on accreditation, innovation, and modernization. The first week of negotiations made clear this is not a minor adjustment — it reflects a real shift toward outcomes, value, and consumer protection, alongside new expectations around transparency and compliance.⁠⁠ The second week of negotiations is scheduled for May 18 to 22, and we’ll continue translating what’s happening into what members need to know.⁠⁠

We’re actively working with many of our members on content for June that responds to the question we heard repeatedly from congressional offices in Washington: **How is AI actually benefiting students?**⁠⁠ We’re building a set of practical stories and examples that show real student-facing impact and measurable operational results.⁠⁠

Ultimately, that’s the Forum’s mission: innovation that proves itself in better outcomes for students.

From Liberal Arts to the Labor Market: How NOVA Is Connecting Humanities Students to Careers

by Presidents Forum | May 1, 2026 | Innovation

By Anne M. Kress, President, Northern Virginia Community College

Higher education leaders and policymakers could be forgiven for making AI the center of every conversation about preparing students for a world of work changing at record speed. The numbers are striking: a Lightcast study found that one-third of the skills required for the average job changed between 2021 and 2024. A LinkedIn executive observed in a May 2025 New York Times opinion piece that AI was breaking the bottom rung of the career ladder — the entry-level roles where generations of young workers got their start—and that was a year ago.

AI deserves our attention. But it isn’t the only issue that does.

At Northern Virginia Community College (NOVA), we hear consistently from students and employers that career-connected learning is often the difference between a graduate who gets hired and one who doesn’t. Students pursuing IT and engineering at NOVA already benefit from that connection: internships and apprenticeships with partners like Micron, Digital Realty, Microsoft, and AWS, plus the opportunity to earn employer-valued credentials on the path to their certificates and degrees. These opportunities build careers.

They also build the durable skills that employers – not just in STEM fields – say they need in their early-career workers. A study last year by Presidents Forum member Western Governor’s University and UpSkill America defined durable skills as the “enduring skills that are not job/role specific but are valued across all roles and workplaces (teamwork/collaboration, active listening, communication, etc.).” It also noted a prevailing belief among employers that skills needed to succeed on Day One of a job (trustworthiness, attention to detail, collaboration, integrity) are critical – and gained through real-world experience rather than academic instruction.

How do we equip students, regardless of discipline, with the durable skills needed to thrive in today’s whirlwind workplace?

In fall 2022, more than 44,000 students were enrolled in liberal arts courses across nearly 2,000 sections at NOVA. With support from the Jack, Joseph and Morton Mandel Foundation and partners in the business community, NOVA launched an initiative to expand our career-readiness infrastructure to these students. The result is a two-part model: a micro-credential program that makes the skills embedded in a humanities education visible and verifiable to employers, and a micro-internship program that puts those skills to work in real professional settings.

We started, as we always do, by asking employers what they actually need and value. We convened a group of 40 professionals working in humanities-adjacent fields and posed a direct question: What does an emerging professional need to succeed? Over eight weeks of structured discussion, faculty synthesized employers’ responses into five defining characteristics: workplace humility, adaptability, a willingness to learn, strong communication, and technical fluency. Those conversations became the foundation of a micro-credential program comprising 24 digital badges across three pathways — Critical Thinking, Communication Skills, and Leadership. These are employer-informed markers of specific, validated competencies — designed from the outset for college-wide adoption, so any NOVA student, regardless of discipline, can build and demonstrate these skills.

The micro-internship program grounds those credentials in real experience. These are short-term, project-based, remote or hybrid engagements that fit the realities of students’ schedules: over 70% of NOVA students are part-time, juggling classes, jobs, and caregiving, so we wanted the micro-internships to be accessible and achievable. We also wanted the students’ work to be consequential. NOVA students helped Smithsonian curators sort through a newly acquired collection of 19th century postcards. Others analyzed truancy data for a Chatham County judge, created content celebrating the Alexandria Film Festival’s 20th anniversary, and documented campus life for NOVA’s marketing office. These micro-internships are not simulations. They are real projects, for real organizations — exactly the experiences that help a student walk into a job interview and say, with evidence, what they can do.

The skills these students develop — synthesis, communication, ethical reasoning, adaptability — are hardest to automate and most valuable in a world reshaped by AI. Thanks to funding from the Mandel Foundation, NOVA has been able to build the infrastructure that supports the development and demonstration of these skills. Through this project we have learned that our students are ready and their prospective employers are willing. The only question is whether more higher education institutions can follow NOVA’s lead and meet them both halfway.

Competition is an Illusion: How Higher Ed Partnerships Can Increase Access to Online Learning – Sooner than Later

by Presidents Forum | Apr 29, 2026 | Innovation, Outcomes and Accountability, Partner, Uncategorized

By Kate Smith, president of Rio Salado College, and Trevor Kubatzke, president of Lake Michigan College

The demand for online learning has surged in the last 5 years; however, many colleges are struggling to keep pace. According to a 2025 Changing Landscape of Online Education (CHLOE 10) Report and forbes.com analysis, nearly 9 in 10 colleges plan to expand online offerings but many do not have the technology, funding, faculty readiness, and other critical structures in place to make the transition fast enough to meet learner demands.

Lake Michigan College (LMC) and Rio Salado College presidents came up with a solution that’s been working since 2022 – a partnership agreement that gives LMC students the option to complete some courses online with Rio Salado.

The partnership, which is the first of its kind in the country, resulted from a conversation between LMC’s President Trevor A. Kubatzke and Rio Salado’s President Kate Smith during an Alliance for Innovation and Transformation conference a few years ago.

The outcome — LMC was able to enhance its offerings and provide online learning options to its 3,300 students without the logistical barriers or expense of expanding instructional development, staffing courses, or integrating an online platform.

LMC students enrolled in 174 Rio Salado class seats last academic year, which were previously unavailable to them in an online modality.

“This is a model of mutual support, not competition,” said President Smith. “When students win – we all win.”

LMC serves as the home institution, providing academic advising, enrollment support, and degree credit for courses completed through Rio Salado. LMC students pay in-district tuition rates, not out-of-state tuition.

“At Lake Michigan College, our commitment is to remove every barrier that stands between our students and their goals,” said President Kubatzke. “This partnership with Rio Salado College does exactly that. By allowing our students to access specialized courses at our domestic tuition rate, we’re expanding what a Lake Michigan College education can look like without asking students to sacrifice affordability. This is what it means to put students first.”

Current offerings include American Sign Language, French, Arabic, Chinese, and Insurance courses, as well as courses to complete an Advanced Certificate in Cybersecurity.

Students can access the expanded catalog through LMC’s advising process and seamlessly enroll in Rio Salado courses as part of their academic plan, supported by advisors at their home campus who help them navigate which courses transfer and apply toward graduation requirements.

A streamlined payment processing structure supports a smooth transition for students, as does LMC’s robust Student Information System, which enables efficient data exchange and supports timely administrative processes. Equally important, is the consistent engagement of faculty and administration from both colleges, who are committed to working in a spirit of collaboration.

The investment has paid off for both colleges, increasing enrollments and opportunities for new course offerings to meet other student interests.

“Innovation at Rio Salado College has always been rooted in increasing access to higher learning and student success, especially by way of partnerships,” said President Smith. “Our growing partnership with Lake Michigan College demonstrates what’s possible when institutions lean into collaboration with a common goal. By sharing our online expertise and specialized courses, we’re not just expanding catalogs — we’re expanding opportunity. Together, we’re building a model where resources are maximized, and students are empowered to reach their goals in ways that fit their lives.”

What is Holding Back AI Innovation in Higher Education?

by Presidents Forum | Apr 10, 2026 | Innovation, Video, Working Learners

What is Holding Back AI Innovation in Higher Education?

What is holding back AI innovation in higher education?

Outdated regulations, especially those tied to seat time and “regular and substantive interaction”, are limiting innovation.

These rules were designed to prevent low-quality correspondence programs, but today they:

Regulate how education is delivered (inputs) instead of what students learn (outcomes)
Make it harder to scale self-paced, AI-enabled learning
Reinforce faculty-centric models that don’t reflect modern technology

Why does AI require a new model of learning?

AI changes how people learn in two key ways:

Students will start at different skill levels
They will take different paths to reach mastery

This makes fixed-time, one-size-fits-all education models obsolete.

How much will AI change jobs and skills?

A major takeaway from the Capitol Hill discussion:

70% of the skills in a typical job will change within five years

This means:

Nearly every worker will need to reskill or upskill
Learning will shift from “once and done” to continuous and lifelong

Can the current education system handle this level of reskilling?

No.

Today’s system is not built to:

Retrain the majority of the workforce at scale
Support continuous learning for people who already graduated
Deliver education efficiently enough to match the pace of AI change

What role should AI play in solving the reskilling challenge?

AI must be part of the solution.

According to Rajen Sheth:

We will need to train everyone on AI
And use AI to train everyone

That means:

Personalized learning tailored to specific jobs
Scalable delivery across millions of learners
Education embedded into real work contexts

What did policymakers on Capitol Hill understand about AI and education?

There are encouraging signs:

Federal agencies are already experimenting with scalable models (e.g., AI literacy via text messaging)
There is bipartisan awareness of the need to support innovation
Stakeholders across government, industry, and education are engaging together

However, coordination and speed remain challenges.

What needs to happen next?

To meet the scale of AI-driven change:

Policy must:

Shift from regulating inputs → measuring outcomes
Enable flexible, technology-driven learning models

Institutions must:

Build systems for lifelong learning at scale
Focus on skills, not just degrees

Technology must:

Deliver personalized, accessible learning for every worker

Bottom line: What is the biggest takeaway?

AI is forcing a shift from:

Static education → continuous learning
Standardized pathways → personalized mastery
Inputs → outcomes

The systems that adapt fastest will define the future of both education and the workforce.

Transcript:

00;00;05;13 – 00;00;30;24 Wes Smith As our audience knows, the President’s Forum was created to drive accountable innovation in higher education. The promise of innovation to improve higher ed by lowering costs and improving outcomes has never been more obvious. Our guest today is Rajan Sheth. He’s the CEO and co-founder of Kiran Learning. And last week we had the chance to cross paths in Washington, D.C..

00;00;30;26 – 00;00;33;02 Wes Smith Rajan, great to see you again today.

00;00;33;04 – 00;00;35;09 Rajen Sheth Hey, Wes. Good to see you as well.

00;00;35;11 – 00;01;05;25 Wes Smith Hey, one of the conversations that we had last week when we were together in D.C. with the President’s Forum, it revolved around some of the outdated regulations that are hampering innovation. And I just want to start with your reaction to hearing the president’s thinking around, rules and laws slowing down the adoption of AI and other innovation that could really improve the outcomes for students.

00;01;05;28 – 00;01;33;02 Rajen Sheth Yeah. Well, it was interesting for me as a technologist. It was a really enlightening conversation. I didn’t fully appreciate the barriers that universities run up against when they’re trying to do innovative things. What was interesting about that room is that you had the most innovative universities in the nation that were there, all who are open to innovation and who have been for many, many years.

00;01;33;04 – 00;01;52;12 Rajen Sheth But they’re running into barriers, with this. So, you know, I think one of the things that that really was interesting is when they started to talk about how there’s, how there is a, regulation on seat type, like, you have to be in class for X amount of time in order for it to be accredited.

00;01;52;14 – 00;02;33;28 Rajen Sheth And that is something that is just going to change rapidly in the world of AI. It’s just, you know, everyone’s going to start from a different starting point and they’re going to take a different path to getting to mastery. And that’s something that we’re going to have to plan for. With, with students that are out there. The other interesting thing that was interesting about the discussion is I came to appreciate kind of the coming soon that is coming with how every job is going to change, with, with AI and we’re going to need to make sure the regulatory environment is such that our best universities are most innovative universities able to educate those

00;02;33;28 – 00;02;37;17 Rajen Sheth students. And the scale of this is going to be massive.

00;02;37;19 – 00;03;07;09 Wes Smith Right, right. The conversation that you’re referencing, with the, the seat time, issues that that need to be resolved. It’s something that like insiders on, well, at least at the president’s forum are thinking about all the time. And it’s the regular and substantive interaction, regulation. The Department of Education was essentially trying to prevent, you know, low quality programs, from accessing federal aid.

00;03;07;11 – 00;03;31;03 Wes Smith And those used to be, you know, low program, low quality programs that were essentially, hey, this is this is, a program that you can send in. They’ll send you some material, you send it back, they’ll, you know, decide if you did well or not. And and they’re pulling down federal financial aid for programs that just weren’t very good.

00;03;31;05 – 00;04;05;01 Wes Smith And so it had a great intent as it started. But but it started regulating, the the inputs rather than the outcomes. And when you start regulating inputs, well, when the inputs become, more effective, delivered through technology, well, then your regulations are outdated. It kind of hard codes, faculty centric models and and it really hampers, you know, self-paced learning.

00;04;05;03 – 00;04;06;15 Rajen Sheth Yeah. So yeah.

00;04;06;17 – 00;04;12;16 Wes Smith Yeah, that’s the issue that we have to deal with. It really discourages technology enabled scale is what it does. Yeah.

00;04;12;18 – 00;04;33;06 Rajen Sheth You know I think it’s a really good point that yeah, it’s almost like you need to separate the of the intent from the execution. And, you know, in technology, a lot of times for particularly product management and technology, we try to separate out the what versus the how. So like for example, when we specify a product, we try not to specify the how too much.

00;04;33;08 – 00;05;00;13 Rajen Sheth We try to specify the problem and then let the engineers figure out the how in the most creative way that that that meets that requirement. And I think we got to do the same thing with policy. We need to understand the intent and then the how it’s going to change rapidly over time. But then, you know, as long as we’re going towards that intent, which is a strong good intent, then we’re going to we’re going to be able to meet it in different ways.

00;05;00;16 – 00;05;08;17 Wes Smith Yeah. I mean, in this case, we’re we’re functioning under regulations that were designed for correspondence courses.

00;05;08;22 – 00;05;09;05 Rajen Sheth Right.

00;05;09;06 – 00;05;43;18 Wes Smith Exactly. And we’re so far past that, the idea that you that you’re regulating that the how it’s done, you’re going to be perpetually, you know, behind with technology that’s just the fact unless you can figure out, you know, the, the why, the why is going to be really important. Okay. Exactly. So after our meeting, last week, after the president’s four meetings, you joined an effort to provide, insight to Capitol Hill staffers about the evolving technology, specifically AI.

00;05;43;20 – 00;05;50;01 Wes Smith And, and that was up on the Hill. Can you tell us a little bit about the event and what you observed there?

00;05;50;04 – 00;06;13;17 Rajen Sheth Yeah. Yeah, it was a wonderful event. You know, one, it was just interesting for me to be in the capital. That was the first time I was I was over there. And you know, you are. You’re in a place where so much history has been made and you can see the, the, the kind of, the intent of that is there for so many people to kind of adapt where we are to the new environment.

00;06;13;19 – 00;06;34;20 Rajen Sheth What was interesting about this, though, the forum was basically a set of companies that had been thinking about AI skilling, you know, how do we scale the workforce about AI? There are a variety of NGOs and nonprofits that have analyzed different aspects of this. And then there was, there were government. So there’s the, congressional staffers who were there.

00;06;34;20 – 00;06;59;07 Rajen Sheth There was the Department of Labor, Department of Education, that there were all there. And it’s the right group to bring this together. What was really striking to me is to understand the magnitude of the tsunami we are about to encounter. And like Lincoln was talking about how 70% of the skills of any typical job will change over the next five years because of AI.

00;06;59;09 – 00;07;26;26 Rajen Sheth And the vast majority of workers out there are going to have to be reskill, for this. And we also talked about how the existing environment, whether it be, you know, institutions, you know, learning and development training within corporations, it’s just not scale to deal with that. We’ve never had a situation where that portion of, you know, that giant portion of employees need to be rescaled.

00;07;26;28 – 00;07;52;00 Rajen Sheth And, you know, what was really interesting for me and what I talked about there was, we’re going to need to train every single person about AI and how you use AI for what they do. And we’re going to need to use AI to to train every single person. Like we’re going to need to figure out how do we extend our institution so that it is personalized for that person.

00;07;52;00 – 00;08;06;24 Rajen Sheth That’s an accountant in this particular organization that’s now learning how to use AI or a, you know, a, machinist in a particular organization that’s trying to use AI. You know, those are the things that need to happen if we’re going to, if we’re going to meet that scale.

00;08;06;26 – 00;08;21;03 Wes Smith Well, this is when I hear that, from, presents for perspective, the, the amount of reskilling that we’ll need. Did you say 70% of jobs will need to be updated?

00;08;21;06 – 00;08;46;06 Rajen Sheth What’s the what he said was the 70% of the skills for the typical job will need to be reskill. And what that means is, actually, it may be even more striking than that. It could mean the vast majority of people are going to need to learn how to use AI as part of their job. In some cases, in small ways, in a lot of cases, in very big ways, in order to still do their same job five years from now.

00;08;46;08 – 00;09;20;28 Wes Smith So I mean, when I hear that, what I hear is the current system that we have will never accommodate that kind, that scale of reskilling. So we have to think through how we can reskill individuals in a much, much more efficient way. And we have to I mean, when we’re looking at this lifelong learnings, a tagline that a lot of, in higher ed of have been saying a lot, you know, you hear, oh, yeah, we’re moving towards lifelong learning.

00;09;21;01 – 00;09;43;02 Wes Smith This is truly one of those areas where we’re going to have to incorporate back into systems. People have graduated with what they thought were terminal degrees and. Yeah, yeah, we’re done. And we, and they have to come back and reskill. They have to they have to upskill. They have to learn more about. And we don’t we don’t have the system that can do that right now.

00;09;43;05 – 00;10;03;10 Rajen Sheth Absolutely. And I think what’s interesting is that over the past, you know, ten, 15 years, lifelong learning is, is has gotten more traction. But it isn’t nice to have as a person must have. Upskilling has gotten traction, but it’s a nice to have as the person must have. Now all of a sudden, it’s going to be a must have.

00;10;03;17 – 00;10;19;05 Rajen Sheth Like you cannot replace all those people with people that know it because nobody knows it, and everybody’s going to need to, is going to need to learn. We need to get our systems to the point where, yeah, where they can be able to train that volume of people.

00;10;19;08 – 00;10;44;20 Wes Smith Well, I’m assuming that this was kind of shocking, to, to Hill staffers and government employees to say this is the kind of, of massive change that we have to prepare for. Did you get any sense from them? About their, you know, their preparation for this or how they’re planning to, you know, facilitate innovation through policy?

00;10;44;23 – 00;11;05;14 Rajen Sheth Yeah. Well, I was actually very impressed with how much they are understanding what’s what’s hitting and the kinds of things that they’re thinking about. The Department of Labor, talked about some of the things that they’re doing. They demo, for example, a, an AI literacy, module that they, they put out via text messaging.

00;11;05;14 – 00;11;25;05 Rajen Sheth So you just sign up for a text message and then it takes you through a ten day course, which I’m taking right now. I’m actually going through it right now. And it is, it gives you kind of the basics of how you think about AI. In with my other. Had I told you this before? I teach a class on intro, the AI at Stanford.

00;11;25;08 – 00;11;46;12 Rajen Sheth And it was interesting because a lot of the same principles that that I focus on there things that they were teaching via text messaging. And so their point was you can reach many, many more people via text, and you can, you can get them the right information to make them not afraid of AI. And I think I’m impressed that the people are starting to think about that.

00;11;46;14 – 00;12;09;02 Rajen Sheth However, it’s going to need to be a coordinated, coordinated thing between the government, between institutions, between companies to really actually solve this problem. It’s it’s, you know, one of the biggest things we need to solve. The other interesting thing is that they talked about, particularly LinkedIn, talked about the economic positive impact that could happen because of AI.

00;12;09;05 – 00;12;23;05 Rajen Sheth Like it could be an additional $4 trillion, in terms of adding to our GDP. So it’s a huge amount, but we have to do it in the right way. To actually get there.

00;12;23;08 – 00;12;45;02 Wes Smith Well, I’m impressed just by the idea that the Department of Labor is ahead of the curve on this text messaging, campaign. That’s that’s impressive to me. I mean, if somebody is thinking ahead and saying, hey, this has to be a huge focus for us, we need to start educating and facilitating a transition to an AI world.

00;12;45;05 – 00;13;12;02 Rajen Sheth Yeah, absolutely. They have a guy named Taylor Stockton that, is their chief innovation officer and been thinking about things the right way. And, you know, he comes from the startup world. He was a Google before as well. And, I’m impressed that they’re they’re thinking in a very agile way. And, you know, obviously it’s hard to get things done in, in, in the political world, but I think we’re all going to need to work together to figure out how to how to move quickly here.

00;13;12;06 – 00;13;46;14 Wes Smith Yeah, absolutely. And the meetings that we had on the Hill with presidents last week, I thought it was pretty remarkable how consistent the responses were from, Democrat leadership and Republican leadership with regard to, facilitating innovation. I think both sides, they understand the issue and they want to solve the problem. The next step is actually, you know, putting some of the solutions into legislation.

00;13;46;14 – 00;14;01;12 Wes Smith That’s the hard part in DC, right, is getting something through and signed and, and, it’s just inherently political. But, on this particular issue, it seemed fairly bipartisan to me. I don’t know if that was your experience with Hill staffers.

00;14;01;14 – 00;14;02;10 Rajen Sheth Yeah.

00;14;02;12 – 00;14;04;06 Wes Smith We saw something different.

00;14;04;09 – 00;14;23;18 Rajen Sheth No, I saw the same thing. I think everyone is realizing that this is going to be an issue, and that is not polarizing. Everyone knows this is coming. And so, you know, we know we will have a big problem with the job market if we don’t do something about this. And so, there was a lot of unity out there.

00;14;23;18 – 00;14;39;25 Rajen Sheth And I think now we got to see what kind of policy can we put in place, what kind of innovation can be put in place, how that can be rolled out, and how you involve the institutions, and, and the other companies into this to, to make it a reality.

00;14;39;27 – 00;15;09;29 Wes Smith Right. Okay. Well, I want to wrap this with your takeaways. So based on your experience and what you saw, at the Capitol last week, what would your takeaways be for specifically for higher ed innovators who are looking to incorporate, AI and other solutions into their work so they can lower costs and so they can, you know, increase the outcomes, the quality of outcomes that students experience.

00;15;10;02 – 00;15;12;27 Wes Smith What are your takeaways based on what you learned?

00;15;12;29 – 00;15;37;09 Rajen Sheth Well, I think that a lot of what we talked about in the president’s form about bringing down the cost of education, reaching more people, it’s going to become vital over the course of the next few years. And I think that we’re going to have to move quickly. We’re going to have to adopt AI in our teaching practices and make it such that we can really, truly personalize for every situation, every learner that’s out there.

00;15;37;11 – 00;15;50;25 Rajen Sheth And we’re going to have to remove the barriers from a policy perspective such that we can all move faster. There’s a lot of intent to move faster, but it’s really hard to do that right now. And so if we can do that, we can actually meet this challenge. It’s about faces.

00;15;50;27 – 00;15;57;05 Wes Smith Yeah. Well Rajan, thanks for joining us today. Thanks for the debrief on the time in DC. It’s been a pleasure.

00;15;57;07 – 00;15;58;24 Rajen Sheth Yeah. Thank you. I really appreciate.

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