change

The Law School Deans Driving AI Innovation in Legal Education — from natlawreview.com by Shivani Vedhere, AI & the Law Newsletter; via Colin S. Levy

Artificial intelligence is no longer a peripheral issue for legal education. It is quickly becoming one of the central questions facing law schools: how to prepare future lawyers for a profession in which AI will affect research, client counseling, litigation strategy, access to justice, and the business of law.

For decades, law schools treated legal technology as an elective or a niche interest for students already inclined toward innovation. That era is ending. Law firms are adopting AI tools at scale and even investing in developing their own tools. Clients are asking harder questions about efficiency, cost, and competence. Courts are sanctioning lawyers and litigants for AI-generated hallucinations, with the number of identified cases in the United States now exceeding 1,000. Students entering the profession will be expected to keep up with this rapidly changing landscape.

The most forward-looking law schools are responding accordingly. That transformation is being driven in large part by a group of innovative law school deans who are treating AI not as a passing trend, but as a structural change in legal education.

These initiatives signal a broader shift in legal academia where law schools are no longer merely debating whether AI belongs in the curriculum. The more pressing question is how deeply, how early, and how responsibly AI should be integrated into legal education.

Higher Education Can’t Wait for the Future to Arrive (Lev Gonick, Arizona State University) [Salisbury]

On 07/07/2026, in 21st century, 24x7x365 access, career development, change, changing business models, collaboration, colleges, community colleges, competency-based learning/education, faculty/staff, future, future of higher education, game-changing environment, heutagogy, higher education, innovation, instructional design, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning preferences, liberal arts, more voice more choice more control, skills, society, student-related, teaching & learning, trends, United States, universities, vision/possibilities, by Daniel Christian

Higher Education Can’t Wait for the Future to Arrive (Lev Gonick, Arizona State University) — from humanistxyz.substack.com by Allison Dulin Salisbury
“The biggest risk we face as a sector is assuming we can wait out AI.”

We have an opportunity right now to reorient the university around student experience—not as an aspiration, but as a necessity. I’m calling this shift TechEd, which I explore in detail in my LinkedIn series The TechEd Revolution.

AI poses a fundamental shift in how technology might empower students to own their discovery and educational journey, and to drastically reduce the friction that makes college so unappealing to so many.

To that end, we need to urgently redesign systems and opportunities around skills and competencies. That work should be far more advanced than it currently is. And one of the hardest challenges is rethinking how we operate as a workforce in academia.

Everything colleges and universities need to know about the collapse of the youth labor market, internships and entry-level jobs… [Busteed]

On 07/06/2026, in business side of he, career development, change, colleges, community colleges, faculty/staff, higher education, parents/guardians, society, student-related, trends, United States, universities, by Daniel Christian

Brandon’s posting on LinkedIn.com

Artificial Intelligence and the Future of Entry-Level Work: A Framework for Safeguarding and Reinventing Early Career Pathways

On 06/29/2026, in 21st century, Artificial Intelligence/Agents/LLMs/and Related, business, career development, change, corporate / business world, economics, global / globalization, participation, pathways, policy, reinvent, society, student-related, workplace, by Daniel Christian

Artificial Intelligence and the Future of Entry-Level Work: A Framework for Safeguarding and Reinventing Early Career Pathways — from the World Economic Forum (weforum.org) and PwC

Artificial intelligence (AI) is reshaping how organizations hire, develop and advance talent, and this is most visible at entry-level. Globally, more than one in three young workers are employed in occupations with medium to high exposure to AI-driven task change. How these roles evolve will have significant implications for organizational performance, workforce participation and economic mobility.

Will learning curated by employers replace degrees? — from universityworldnews.com by Louise Nicol

If universities do not future-proof their offer through deeper and more credible partnerships with employers and industry, what exactly prevents employers from educating and training people themselves?

This is why the future of higher education depends on far deeper and more operational partnerships with industry. Not symbolic advisory boards or occasional guest lectures but genuine co-design of curricula, shared ownership of applied projects and clear accountability for graduate capability.

Universities that integrate live industry problems, cross-faculty collaboration and work-based learning into the core of their programmes make themselves harder to replace. Those that acknowledge the existence of external learning platforms and deliberately build them into a broader educational journey strengthen rather than weaken their position.

The real risk for universities is not replacement but marginalisation. Employers will not abandon universities out of hostility or ideology. They will do so pragmatically if universities fail to add distinctive value beyond what employers can now deliver themselves.

The Current State of Play: AI in Higher Education and the Road Ahead [Gamby, Kil, Koblic, LeBlanc, Moldoveanu & Siemens]

On 06/29/2026, in 21st century, Artificial Intelligence/Agents/LLMs/and Related, business side of he, career development, change, colleges, community colleges, corporate / business world, culture, emerging technologies, ethics, expectations, experimentation, faculty/staff, game-changing environment, generational differences, higher education, ideas, innovation, instructional design, intelligent systems, IT in HE, leadership, learning, learning agents, learning ecosystem, Learning Experience Design, liberal arts, morals/values, organizational change, pace of change, parents/guardians, personalized/customized learning, policy, reinvent, relationships, skills, society, strategy, student-related, teaching & learning, trends, United States, universities, vision/possibilities, by Daniel Christian

The Current State of Play: AI in Higher Education and the Road Ahead — from er.educause.edu by Tanya Gamby, David Kil, Rachel Koblic, Paul LeBlanc, Mihnea Moldoveanu and George Siemens

The conventional explanation for this strategic vacuum points to the speed of technological change; it is moving too fast for institutions built for deliberation. That is true. . . and incomplete. The deeper issue is cultural. In fairness to higher education, many industries are struggling to keep up with the pace of AI advances. Higher education, however, moves even more slowly and is not built for the kind of transformational speed now underway. Getting institutional stakeholders to engage, rethink the work, and move faster may be the central challenge facing presidents and chancellors today, and that’s saying a lot in such volatile times.

From DSC:
I highlighted this paragraph because it hits upon the key item involved here — culture. “The deeper issue is cultural.” I think that’s a very true statement.

Part of the culture and setup of many institutions includes giving faculty members full rein of their classes and their departments. Faculty members have a great deal of leeway and power in how they do things. So trying to get X faculty members to get on board — including the Department Chairs — is not an easy task.

Another part of culture involves being willing — or not — to change in the first place. Some institutions are like Google and are used to making changes and being more innovative. But those institutions are not the norm, at least in my experience. And this doesn’t even address another topic the article mentioned — the pace of these changes. As the authors point out, most institutions of traditional higher education are not equipped to deal with the current pace of change (nor are most of our other types of institutions and our corporations as well).

I’m going to end this posting with another brief excerpt from the article:

Institutions rooted in human relationships, committed to truth-seeking, and oriented toward the full development of persons play a central role. AI cannot manufacture the experience of mattering to another human being. It cannot model intellectual courage or ethical discernment. It cannot build the kind of community in which students discover who they are and what they believe.

These are not small things. They are, in fact, the things most worth doing. At their best, colleges and universities are not only preparing better workers but shaping individuals and strengthening society.

AI’s getting expensive for us these days

On 06/23/2026, in Adobe, Artificial Intelligence/Agents/LLMs/and Related, business side of he, change, changing business models, cloud-based computing / apps / other cloud-related, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, cost of getting a degree, Daniel S. Christian, education technology, emerging technologies, experimentation, faculty/staff, funding / grants, game-changing environment, graphics, higher education, human-computer interaction (HCI), innovation, intelligent systems, IT in HE, learning ecosystem, liberal arts, library / librarians, new business models, Open AI, platforms, student-related, teaching & learning, technologies for your home, tools, trends, United States, universities, by Daniel Christian

From DSC:
I used to be able to bring up Firefly on the web and use it “free” of charge — I didn’t have to go purchase tokens or credits. (I was actually paying for the Adobe Creative Cloud Pro suite of tools…so it wasn’t really free.)

But the other day I was trying to figure out what the latest pricing is at Adobe with that suite of tools and the use of credits for AI-based features. They say Adobe Creative Cloud Pro users get 4000 credits a month. Well, I have that suite and I’m still getting prompted to purchase credits. Firefly for individuals runs from $9.99 (2,000 credits/month) to $139.91 per month (50,000 credits per month). Not inexpensive, right? Below are other items along these lines.

The Era of Affordable AI Is Over. What Comes Next? — from builtin.com by Ameya Kanitkar
AI providers are shifting to usage-based billing for their services. AI fluency is more important now than ever to make the most of your tools to avoid unnecessary spending.

Summary: The era of cheap, flat-rate AI is ending as providers shift to usage-based billing. Every prompt now carries a direct cost, turning casual use into major budget risks, as seen when Uber depleted its 2026 AI budget in four months. Leaders must now track real-time value and token efficiency.

For a brief window, companies had access to the most transformative technology in a generation at the cost of a streaming subscription. Tools like ChatGPT put AI within reach of anyone with a browser and time for experimentation, while GitHub Copilot came in at just $10 a month, with token costs remaining relatively low. In the beginning, experimentation felt cost-effective, easy and relatively low-risk.

But that era is ending, and the bill is coming due faster than a lot of enterprise leaders anticipated.

The Fable of AI in Education — from downes.ca by Stephen Downes
Marc Watkins, Rhetorica, Jun 17, 2026

Tokenomics will be a hot topic of discussion on university campuses because, as Marc Watkins notes in this article, there is no realistic path forward to providing all students with access to advanced AI.

From this posting on LinkedIn.com from Dr. Nick Jackson:

And now there is a third layer emerging. Institutions are waking up to a systems-level question they are likely not remotely prepared for. Who pays for AI? How are budgets managed when there are unclear token consumption pricing models? How is AI procured? Who decides what tools get used and by whom and who gets access and at what level?

.

If AI Eats the Entry-Level Job, Where Do Young People Learn to Work? (Ryan Craig, Achieve Partners) — from humanistxyz.substack.com by Allison Dulin Salisbury; via Ryan Craig
“The public should not be subsidizing colleges whose students lack relevant, paid, in-field work experience.”

That is the trap at the center of this conversation: everyone wants to hire someone with three years of experience, and almost no one wants to provide those three years.

And Ryan’s policy prescription is unusually concrete: pay employers to hire and train apprentices, following the countries that have scaled apprenticeship far faster than the U.S.; require colleges receiving federal student aid to provide relevant, paid, in-field work experience; and build a market of intermediaries that can make the whole thing operational.

Ryan’s view is that higher education remains critically important. But college without meaningful work experience may become a much worse bet, especially for students who cannot afford to guess wrong.

The unbundling of lawyer institutions [Furlong]

On 06/18/2026, in 21st century, 24x7x365 access, Access to Justice (A2J), Artificial Intelligence/Agents/LLMs/and Related, change, changing business models, game-changing environment, law schools, Legal operations, legal reform, legal technologies, legislatures / government / legal, new business models, by Daniel Christian

The unbundling of lawyer institutions — from jordanfurlong.substack.com by Jordan Furlong
AI will strip law firms and law schools of their commodity features. Their future depends on whether they can rebuild around their highest-value functions and their trust-bearing core.

Two very different articles — one from a law professor, one from a legal technology analyst — crossed my desk last month. They each say something really important about law schools and law firms, respectively. But taken together, they point us towards what I think is an even more profound reality about lawyer institutions in the post-AI world.

At his eponymous Substack, Professor Michael Plaxton’s “To Our Next Law Dean” is really addressed to every dean of every law school, asking: After AI, how will you justify our existence? His concern is that AI is rapidly learning to perform many of the tasks law schools train students to do, and to deliver much of the general legal knowledge law schools provide at scale, including research, writing, analysis, and explanation.
…
At Legal Technology Hub, Nikki Shaver’s “Law Firms Want to Change; They Just Can’t” asks whether law firms are capable of managing the transition to a post-AI legal market.

Law schools and law firms are the legal profession’s most important institutions. But they were built for a world in which legal intelligence was scarce, and that world is rapidly passing away.

Also related/see:

Affordable & Accessible: The Democratization of Legal Tech (Tyler Foreman VP of AI – Rocket Lawyer) — from tlpodcast.com with Tyler Foreman & Chad Main
Tyler Foreman, the Vice President of AI at Rocket Lawyer, joins the show to discuss the intersection of artificial intelligence and the legal industry.

The conversation focuses on how modern generative AI and Large Language Models (LLMs) act as a legal operating system to simplify contract reviews, document drafting, and client intake, while maintaining essential connections to human attorneys.

Important insights from this PwC global jobs report — from linkedin.com by Ross Dawson & PwC

The Tyranny of College Admissions: Why It’s So Challenging to Have Real Change in K-12 Education — from gettingsmart.com by Jon Alfuth

Key Points

College admissions policy shapes K-12 practice. If colleges continue to privilege course sequences, seat time, and grades, high schools will remain constrained in how far they can move toward competency-based learning.
States and institutions already offer models for change. Wisconsin, Colorado, Indiana, and pilots like CUNY and Michigan Ross show that admissions can incorporate portfolios, demonstrations of learning, and durable skills.

If we could instead orient K-12 education around skill development and application rather than Carnegie Units and grades, we could create a new paradigm for where, when and how students demonstrate college and career readiness. Competency-based education moves schools and systems towards this desirable future that balances knowledge with skills.

Despite tremendous evidence of its potential, efforts to accelerate this shift have been stymied by the tyranny of college admissions requirements and processes. Parents, teachers, administrators and policymakers end up in a quandary. Anyone attempting to shift away from this traditional course sequence is criticized as trying to lock kids out of higher education and we snap back to the way things have always been done.

Why Students Aren’t All In on AI—And What They Want From Colleges — from insidehighered.com by Colleen Flaherty
New Student Voice data reveal students are embracing AI as a learning tool while worrying about dependence, career disruption and inconsistent institutional responses.

Read on for six takeaways from the survey and additional insights—including how institutions can start to close the gap between students’ optimism about AI as a learning tool and their faith in their colleges’ ability to help them navigate change.

Takeaway 1: More students are using AI than ever for coursework, while a significant share—20 percent—remain resisters.

Takeaway 2: “Worried about dependence” is the most common student stance on AI.

Takeaway 3: A majority of all students expect AI to somewhat (39 percent) or very (16 percent) negatively impact their career prospects.

Takeaway 4: Just one in 10 students says that their institution is handling AI’s rise very well, in a thoughtful and proactive way.

…and more >>

And here’s the link to Robert’s posting on LinkedIn.

OPINION: If higher education wants to rebuild public trust, start with making college affordable — from hechingerreport.org by John B. King, Jr.
Addressing high tuition, food insecurity and child care needs are important first steps

Higher education is under siege, with many students and parents balking at high costs. In a series of op-eds, university leaders lay out their efforts to keep college affordable. This is the first in the series.

For many people across the country, paying for college is the largest investment they will ever make. Increasingly, it’s one that feels out of reach.

Over the past two decades, tuition and fees at private, national universities have jumped by 112 percent; at some “elite” and highly selective schools the annual cost of attendance now approaches $100,000.

If higher education is to rebuild public trust, affordability can’t be an afterthought. It must be at the center of our strategic focus.

Also from The Hechinger Report, see:

What it’s like to enter the job market in the middle of an AI revolution — from hechingerreport.org by Neal Morton
‘It’s not looking good’: The unemployment rate for recent grads is the highest in five years, but AI is not primarily to blame — at least not yet

Addendum on 6/10/25:

The Real Mission of Higher Education Is Hiding in Plain Sight — from insidehighered.com by John Warner
A guest post laying out a path forward for all institutions.

Most colleges and universities are not actually organized around learning. They’re organized around teaching, research productivity, rankings, revenue, and the preservation of institutional prestige. Students sense this, even when they can’t articulate it. The public senses it, too. Academic researchers themselves have been making this argument for decades, but it has rarely felt more urgent than it does right now.

The Yale report says, wisely, that “trust is earned by doing what you say you’re going to do.” Universities say they’re about learning. The way to rebuild trust is to actually mean it and to build institutions that prove it.

The Yale committee is right that trust must be rebuilt through action over messaging. The most fundamental action, and the one most often overlooked, is this: Get learning right.

Addendum:

AI Budgets in Education Show No Sign of Decline — from campustechnology.com by Rhea Kelly

Key Takeaways

Education AI budgets are holding steady or increasing: Wasabi found that 98% of education organizations expect AI infrastructure budgets to increase or remain steady, with 46% planning increases.
Storage costs are the top AI implementation challenge: Half of education respondents cited data storage issues, including storage and access costs, as the No. 1 challenge for AI projects.
Cloud security and ROI remain pressure points: Only 47% feel confident keeping data unaltered and operational after a cyberattack, 44% lost access to public cloud data after an attack, and 37% of AI projects currently show positive ROI.

Learning Ecosystems

Categories

Tags