trends

The July 2026 update to A Framework for Artificial Intelligence in Business Education is live. [Means]

On 08/10/2026, in Artificial Intelligence/Agents/LLMs/and Related, business, MBA, trends, United States, universities, workplace, by Daniel Christian

Tawnya Means posting on LinkedIn.com

The 2031 Crisis in Higher Education: a stark scenario — from bryanalexander.org by Bryan Alexander — with commentary on a posting by Matthew F. Wilson, Ph.D.

Today’s post is about a scenario for higher ed’s future. It’s not from me, but created by one Matthew F. Wilson, director of Research Translation and AI Strategy at Baylor’s Institute for Global Human Flourishing. “The 2031 Crisis in Higher Education” is a dark one, imagining an accelerating decline for American colleges and universities.
…
One key assumption of this scenario is that most colleges and universities will be unable to redesign themselves for the changing time.
…
All of that said, it’s a fascinating and daunting scenario. It’s an interesting vision of my post-peak higher ed world.

A graphic from Matthew Wilson:

From DSC:
From what I can tell and have read, the things in the above graphic are already happening — and have been happening for some time now.

Also, I don’t think traditional institutions of higher education have the culture(s) it takes to change. So that part about colleges and U’s not being able to redesign themselves for the changing times could easily turn out to be the case.

The AI-native university, AI literacy, AI and accessibility + other items re: AI in our learning ecosystems

On 07/22/2026, in 21st century, 24x7x365 access, accessibility / UDL, Artificial Intelligence/Agents/LLMs/and Related, colleges, communities of practice, community colleges, corporate / business world, corporate universities / corporate training, data related items, education technology, emerging technologies, experimentation, faculty/staff, game-changing environment, generational differences, higher education, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, learning, learning ecosystem, Learning Experience Design, liberal arts, lifelong learning, personalized/customized learning, productivity / tips and tricks, student-related, teachers, teaching & learning, training / L&D, trends, United States, universities, by Daniel Christian

AI & Accessibility: 5 Practical Ways to Use LLMs to Support Inclusive Learning — from learningguild.com by Dr. Athena Joyce Stanley (B.A., M.A.E., Ph.D.)

The following strategies focus on how instructional designers can design for accessibility by embedding or enabling AI-supported tools within learning experiences. These approaches move beyond access to content and begin to support access to understanding, expression, and participation.
…
Personalized Clarification Through AI Copilots
Learners often need additional explanation, but may hesitate to ask questions in live sessions or require more individualized support.

Instructional designers can integrate AI copilots, LLM-powered conversational interfaces, into learning environments to provide on-demand clarification. These tools can act as digital coaches, helping learners understand concepts through simplified explanations and relevant examples.

This approach supports learners who benefit from additional processing time and personalized guidance.

Sample Prompt (for IDs Configuring Copilot Behavior)
You are a workplace learning coach.

Explain the following concept in a clear, simple way:

- Use plain language
- Provide one practical, job-relevant example
- Avoid jargon unless necessary (and define it if used)

Then ask one follow-up question to check for understanding.

Jeff’s posting on LinkedIn.

Teaching AI Literacy with Susan Ray — from intentionalteaching.buzzsprout.com by Derek Bruff and Susan Ray

Per Derek Bruff:
In my conversation with Susan, we talk about that syllabus activity, as well as the AI transparency journals she asks her students to keep during her courses. We also talk about how her personal background prepared her to navigate the challenges and opportunities that AI has posed to her teaching, how she approaches assessing student learning in this age of AI—especially in her online asynchronous courses—and much more.

Building the AI-Native University: Student Success and Lifelong Learning — from coursera.org

In this episode, you’ll discover:

Why building an AI-native campus requires a data-first foundation
How to build an “achievement architecture” for lifelong success
How faculty-built AI tutors cut one program’s course attrition from 40% to 10%
What it means to be a lifelong learning companion

We’re Raising the First AI Generation. They’re Pushing Back. (Rebecca Winthrop, Brookings) — from humanistxyz.substack.com by Allison Dulin Salisbury
“Young people harbor real anger about AI because they’re already experiencing its consequences in their schools, relationships, job prospects, and feeds.”

As Rebecca told me:

“Kids harbor real anger. They’re pissed about climate impacts. They’re upset about job prospects. They’re outraged about AI being used to plagiarize writing and produce counterfeit artwork. Their relationships are being affected, and they’re seeing deepfakes in their feeds.”

Our conversation explores what follows from taking those concerns seriously. We discuss cognitive stunting, the case for small, purpose-built AI models over frontier models in education, why students should spend far more time in explorer mode, and how schools can cultivate agency, curiosity, and independent thinking in an age of AI.

The interview ends with one of Rebecca’s most practical recommendations: every school should have a student AI council, not as a symbolic gesture, but with real influence over the tools their schools adopt, the ways they’re used, and the data students are asked to hand over.

Every generation of technology seems to relearn the same lesson: build with people, not for them. AI should be no exception.

“Teachers ban it. Employers demand it.”

Also relevant/see:

The Shifting Career Ladder — from nafez.substack.com by Nafez Dakkak
AI is changing how work works and quietly removing the pathways through which young people learn to become experts.

AI is reshaping how people build skills, enter professions, and move along the career ladder and through the labour market.

In this conversation, I sit down with Matt Sigelmen founder of LightCast and now the President of Burning Glass Institute. Matt has dedicated his career to understanding the labor market and helping society improve the connections within in it.

Matt and I explore why people and opportunities are often only “a few skills apart,” why entry-level work may be losing its traditional role as the first rung of expertise, and why schools, universities, and employers now need to rethink the pathways that turn potential into mastery.

Educators need to be deeply aligned with what these changes are, and they need to shift the AI discourse from “how” questions to “what” questions. What do we need to teach? What do we need to keep in the curriculum?

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.

Instructional Design Trends: What’s Shaping The Future Of Learning? [Pappas] + “The Future Of Personalized Learning And The Leaders Being Trained To Deliver It” [Ayers]

On 07/06/2026, in analytics, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, educational games / serious games, elearning, emerging technologies, engagement / engaging students, future, game-changing environment, human-computer interaction (HCI), ideas, immersion, innovation, instructional design, intelligent systems, intelligent tutoring, leadership, organizational change, personalized/customized learning, skills, strategy, traditional / tradition, training / L&D, trends, user experience (UX), by Daniel Christian

Instructional Design Trends: What’s Shaping The Future Of Learning? — from elearningindustry.com by Christopher Pappas

Table of contents

1. Why Instructional Design Is Entering A New Era
2. The State Of Instructional Design Today
3. Top Instructional Design Trends Shaping 2026
4. The Future Of Instructional Design And Technology

Also from elearningindustry.com, see:

The Future Of Personalized Learning And The Leaders Being Trained To Deliver It — by Ryan Ayers

Table of contents

1. Personalized Learning For Future Leaders
2. Where Personalized Learning Is Heading
3. What Implementing Personalized Learning At Scale Actually Requires
4. The Educational Leaders Being Trained To Deliver This Future
5. Conclusion

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

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?

.

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

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 >>

American Microschools 2026 Sector Analysis [microschoolingcenter.org]

On 06/14/2026, in Alternatives, education, education reform, homeschooling/homeschoolers, K-12 related, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, legislatures / government / legal, parents/guardians, policy, student-related, teachers, trends, United States, youth, by Daniel Christian

American Microschools 2026 Sector Analysis — from microschoolingcenter.org

The National Microschooling Center just published its latest report, the American Microschools 2026 Sector Analysis, it’s most ambitious yet.

This report comprises the most thorough research published to date on microschools in America, examining 1,000 microschools located in all 50 states, the District of Columbia and Puerto Rico. Most are currently operating, with prelaunch microschools as well as those which have closed their doors also included.
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This 2026 edition of the annual American Microschools Sector Analysis series by the National Microschooling Center includes questions on a number of new topics, including ways microschools are impacted by different regulatory and policy stipulations, specifics of educational, business and operational aspects within the microschooling sector. Other questions revisit topics examined in previous studies, to illuminate trends over time and effects of growth and evolution on the ways microschools operate.

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.

Tuition discount rate reaches 57% for private nonprofits, NACUBO says [Unglesbee]

On 06/01/2026, in business side of he, colleges, higher education, trends, United States, universities, by Daniel Christian

Tuition discount rate reaches 57% for private nonprofits, NACUBO says — from highereddive.com by Ben Unglesbee
Price cuts are getting even deeper for first-year undergraduates, while net tuition revenue has fallen, according to the organization.

Early data from the 2025-26 academic year shows historically deep tuition discounts getting even deeper at private nonprofit colleges, according to a study released Monday from the National Association of College and University Business Officers.

For first-time undergraduates, the tuition discount rate at these colleges is projected to reach 57.1% in the current academic year. That’s up from 54.5% from the year before, and the highest point in the past decade. For all undergraduates, the discount rate is poised to hit 51.3%, up from 50% last year and above the most recent peak at 50.8% in 2022-23.

However, revenue declines across the undergraduate body pose difficulties for tuition-dependent colleges. It “suggests that retention alone is not enough to eliminate financial strain at many tuition-dependent institutions,” NACUBO said in its report.

Workplace Readiness: Can Higher Education Develop AI-Ready Students? — from learningguild.com by Eddie Lin and Roshan Bharwaney

For higher education to remain relevant, curricula must evolve. Here are some overarching recommendations for directions in higher education to bridge the skills gaps between universities and workplaces:

AI ethics and safety: Prepare students to navigate issues of fairness, bias, privacy, and societal impact.
Tackling complex questions: Emphasize open-ended challenges that blend structured and unstructured skills and reduce reliance on standardized tests and repetitive drills.
Critical thinking: Develop new assessments for judgment, creativity, and metacognition—essential to supervise AI outputs.
Human-AI synergy: Embed AI fluency across all disciplines, encouraging students to find the niches where human value is maximized.
Industry connection: Maintain close industry partnerships and collaborations including open innovation opportunities and collective intelligence approaches (Bharwaney & Sleeva, 2024).

Experiential learning and communities of practice are central to this vision. Internships, simulations, and cross-disciplinary projects can help students practice human-AI collaboration, resilience, and decision-making in environments that mirror the workplace’s ambiguity and complexity.

Universities that condemn the use of AI by students risk isolating themselves from the realities of today’s workplace, where interns and new hires are expected to be or quickly become adept at using AI for routine tasks and complex projects.

Learning Ecosystems

The 2031 Crisis in Higher Education: a stark scenario [Bryan Alexander]

Instructional Design Trends: What’s Shaping The Future Of Learning? [Pappas] + “The Future Of Personalized Learning And The Leaders Being Trained To Deliver It” [Ayers]

Tuition discount rate reaches 57% for private nonprofits, NACUBO says [Unglesbee]

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