corporate / business world

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.

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

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 Evolving L&D Roles in 2026 Exploring who you might become next — from liftedlnd.substack.com by Lifted L&D

1. The Learning Experience Architect
This is really the evolution of the instructional designer. The difference is that the focus is no longer on building individual courses. Instead, the focus shifts towards designing capability ecosystems.

In modern learning platforms, learning is dynamic and increasingly personalised. AI engines infer skill levels, recommend resources, generate practice scenarios and adapt content based on how people engage. The role of the Learning Experience Architect is to orchestrate that environment so it genuinely supports capability development.
…

Across all of these emerging roles, three themes keep appearing.

The first is data fluency. …
The second is systems thinking. …
The third is human judgement.

Also relevant/see:

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

How Constructivism Learning Theory Shapes Modern Instructional Design And L&D Strategy — from elearningindustry.com by Christopher Pappas
.

Also see:

Microlearning Trends And Strategies In 2026 — from elearningindustry.com by Christopher Pappas

Three items re: AI in our LE’s (involving corporate training, higher ed, and K-12)

On 06/10/2026, in 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, attention, colleges, communities of practice, community colleges, corporate / business world, corporate universities / corporate training, education, education reform, education technology, emerging technologies, engagement / engaging students, experimentation, faculty/staff, game-changing environment, generational differences, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, K-12 related, learning, learning ecosystem, Learning Experience Design, liberal arts, student-related, teachers, teaching & learning, training / L&D, United States, universities, youth, by Daniel Christian

Rethinking Learning Design in Elementary Schools — from edcircuit.com
Why K–5 leaders must redesign—not just adopt—technology to restore attention, deepen thinking, and align AI with how children actually learn

Rethinking learning design in elementary schools is critical as screen time and AI reshape attention, thinking, and student engagement.

Designing for Thinking, Not Just Doing
At its core, learning design must shift from task completion to thinking development.

This requires creating environments where students:

Spend time processing ideas
Work through confusion without immediate answers
Build persistence through challenge

It also requires clarity around the role of technology.

Technology should:

Extend thinking
Provide meaningful feedback
Support exploration

It should not:

Replace effort
Short-circuit reasoning
Eliminate productive struggle

The goal is not to reduce technology use.

It is to ensure that students remain the ones doing the thinking.

Should We Integrate AI into Our Teaching?: Evidence-Based Guidelines for Deciding When AI Belongs — from Faculty Focus by Norman Eng, EdD

Four Questions for Deciding Whether to Use AI

Question 1: Will this AI tool help students use, recall, and demonstrate understanding of core disciplinary content?
Question 2: Will this AI tool require students to apply their learning to a new context?
Question 3: Will this AI tool support—not replace—independent, evidence-based reasoning?
Question 4: Will this AI integration preserve meaningful human interaction?

Christian: Could this be a part of our future learning ecosystems?

On 06/09/2026, in 21st century, 24x7x365 access, adult learning, Artificial Intelligence/Agents/LLMs/and Related, career development, cloud-based computing / apps / other cloud-related, CMS/LMS, communities of practice, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, Daniel S. Christian, digital learning, education technology, emerging technologies, engagement / engaging students, experimentation, faculty/staff, future, future of higher education, game-changing environment, global / globalization, heutagogy, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, informal learning, innovation, instructional design, intelligent systems, intelligent tutoring, K-12 related, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning preferences, learning spaces, liberal arts, library / librarians, lifelong learning, love of learning, microlearning, more voice more choice more control, online learning, online media, passions, personalized/customized learning, platforms, professional development, skills, social media, streams of content, student-related, teachers, teaching & learning, technologies for your home, training / L&D, United States, user experience (UX), vendors, vision/possibilities, by Daniel Christian

From DSC:
Could this be a part of our future learning ecosystems? Education as a personalized content feed.

Coursera wants users to learn through shorter, faster content — from digitaltrends.com by Moinak Pal
Coursera wants online learning to feel more like TikTok
.

Online learning platform Coursera is taking a page straight out of TikTok’s playbook. The company has launched a new AI-powered feed designed to serve short-form educational content in a scrollable, personalized format, signaling a major shift in how digital learning platforms may try to keep users engaged.

The feature introduces bite-sized video lessons, clips, and explainers curated through artificial intelligence based on a user’s interests, learning habits, career goals, and previous course activity. Instead of committing to hour-long lectures or full certification programs upfront, users can now discover short educational snippets designed to make learning feel more casual, accessible, and addictive.

Users scroll through a feed of short educational videos and AI-curated learning moments covering topics ranging from coding and business to AI, productivity, data science, and personal development.

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.

GenAI practice blossoms through the open exchange of insights — from timeshighereducation.com by Samuel Doherty, who is the education and innovation coordinator at the University of Newcastle in Australia
How a structured GenAI professional development series, built around practice, peer voices and multiple entry points, fosters open exchange among colleagues, universities and industry

Connect internal practice to sector-wide thinking
Whatever is happening within any single institution is only part of the picture. Effective GenAI practice grows through open exchange of insights among colleagues, universities, professional bodies and industry, and a development programme that is entirely inward-looking risks missing both useful knowledge and important shifts in expectation.

Our AI sector voices sessions aim to bring external contributors into the programme: researchers, practitioners and sector representatives working at the intersection of GenAI and higher education. The aim is to situate institutional practice within the wider conversation and to signal to staff that the institution is genuinely engaged with that conversation, not just managing it internally.

In the Australian context, the Tertiary Education Quality and Standards Agency (Teqsa) people pillar positions staff as drivers, enablers, users and innovators of GenAI practice, and identifies a lack of information or understanding as one of the primary barriers to ethical and effective engagement. That framing is useful regardless of regulatory context: institutions that treat their people as active participants in shaping practice, rather than recipients of policy, are likely to develop more durable capability.

Regular, lightweight communications, a weekly community of practice update and a monthly all-staff digest can maintain momentum between sessions without adding significantly to anyone’s workload.

What AI-Enabled Education Actually Looks Like When It’s Working for Workforce Students — from gettingsmart.com by Stephen Griffin

Key Points

Institutions can use AI to make skills, pathways, and job outcomes visible to students and employers in ways traditional transcripts cannot.
Academic affairs, workforce development, career services, and employers need a shared definition of readiness and competency before tools can deliver meaningful value.

The second is portable competency records. Learning and employment records — AI-enabled documentation of what a student knows and can do, expressed in language employers recognize — are the infrastructure that makes credentials legible across the education-to-employment continuum. When a student can show an employer not just “completed Supply Chain Management 101” but “demonstrated proficiency in inventory optimization, route planning, and logistics software at the industry-recognized level,” the credential stops being abstract. It becomes evidence. Building these records requires investment in tools, yes — but more importantly, it requires faculty, workforce development staff, and employer partners to agree on what competency actually looks like before the technology is ever purchased.

Learning Ecosystems

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]

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