universities

“CES2026 is a powerful reminder of just how much there is to take in right now and how rapidly technology is advancing.” [DeVaney]

On 01/12/2026, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, bots, change, colleges, community colleges, digital learning, emerging technologies, future, future of higher education, game-changing environment, generational differences, higher education, human-computer interaction (HCI), innovation, learning ecosystem, liberal arts, lifelong learning, pace of change, robotics, skills, staying relevant, student-related, teaching & learning, technology (general), trends, United States, universities, workplace, by Daniel Christian

Major Changes Reshape Law Schools Nationwide in 2026 [Fatima]

On 01/12/2026, in accreditation, assessment, career development, change, corporate / business world, curriculum, faculty/staff, health, higher education, law schools, leadership, policy, real-world assignments, skills, strategy, United States, universities, by Daniel Christian

Major Changes Reshape Law Schools Nationwide in 2026 — from jdjournal.com by Ma Fatima

Law schools across the United States are entering one of the most transformative periods in recent memory. In 2026, legal education is being reshaped by leadership turnover, shifting accreditation standards, changes to student loan policies, and the introduction of a redesigned bar exam. Together, these developments are forcing law schools to rethink how they educate students and prepare future lawyers for a rapidly evolving legal profession.

Also from jdjournal.com, see:

Healthcare Industry Legal Careers: High-Growth Roles and Paths — from jdjournal.com by Ma Fatima
The healthcare industry is rapidly emerging as one of the most promising and resilient sectors for legal professionals, driven by expanding regulations, technological innovation, and an increasingly complex healthcare delivery system. As hospitals, life sciences companies, insurers, and digital health platforms navigate constant regulatory change, demand for experienced legal talent continues to rise.

What 3 credit ratings agencies forecast for higher ed in 2026 [Unglesbee]

On 01/07/2026, in business side of he, change, changing business models, colleges, community colleges, cost of getting a degree, future of higher education, game-changing environment, higher education, learning ecosystem, United States, universities, by Daniel Christian

What 3 credit ratings agencies forecast for higher ed in 2026 — from highereddive.com by Ben Unglesbee
Fitch Ratings, S&P Global and Moody’s Ratings all predicted a tough year ahead, pointing to deteriorating financial conditions and heightened uncertainty.

Fitch Ratings labeled its higher ed financial outlook for 2026 as “deteriorating” while Moody’s Ratings described an “increasingly difficult and shifting operating environment for colleges and universities.” Similarly, S&P Global Ratings said it expects“mounting operating pressures and uncertainty” ahead for the sector’s nonprofit institutions.

Analysts cited additional disruption and belt-tightening ahead in the new year, from predicted demographic declines to pressures on international enrollment to uncertainties about how Republicans’ big spending bill passed this summer will impact demand for college.

Below are the various takes on higher ed in 2026 by Moody’s, Fitch and S&P Global Ratings:

How Your Learners Actually Learn with AI [Hardman] + another item re: AI in our learning ecosystems

On 12/22/2025, in 21st century, 24x7x365 access, adjunct faculty, adult learning, Artificial Intelligence/Agents/LLMs/and Related, bots, cloud-based computing / apps / other cloud-related, colleges, communities of practice, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital learning, education, education technology, emerging technologies, experimentation, faculty/staff, future of higher education, game-changing environment, generational differences, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, law schools, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning preferences, liberal arts, library / librarians, Microsoft, personalized/customized learning, platforms, productivity / tips and tricks, research, skills, student-related, teachers, teaching & learning, technologies for your home, tools, trends, United States, universities, vendors, workplace, youth, by Daniel Christian

How Your Learners *Actually* Learn with AI — from drphilippahardman.substack.com by Dr. Philippa Hardman
What 37.5 million AI chats show us about how learners use AI at the end of 2025 — and what this means for how we design & deliver learning experiences in 2026

Last week, Microsoft released a similar analysis of a whopping 37.5 million Copilot conversations. These conversation took place on the platform from January to September 2025, providing us with a window into if and how AI use in general — and AI use among learners specifically – has evolved in 2025.

Microsoft’s mass behavioural data gives us a detailed, global glimpse into what learners are actually doing across devices, times of day and contexts. The picture that emerges is pretty clear and largely consistent with what OpenAI’s told us back in the summer:

AI isn’t functioning primarily as an “answers machine”: the majority of us use AI as a tool to personalise and differentiate generic learning experiences and – ultimately – to augment human learning.

Let’s dive in!

Learners don’t “decide” to use AI anymore. They assume it’s there, like search, like spellcheck, like calculators. The question has shifted from “should I use this?” to “how do I use this effectively?”

8 AI Agents Every HR Leader Needs To Know In 2026 — from forbes.com by Bernard Marr

So where do you start? There are many agentic tools and platforms for AI tasks on the market, and the most effective approach is to focus on practical, high-impact workflows. So here, I’ll look at some of the most compelling use cases, as well as provide an overview of the tools that can help you quickly deliver tangible wins.
…
Some of the strongest opportunities in HR include:

Workforce management, administering job satisfaction surveys, monitoring and tracking performance targets, scheduling interventions, and managing staff benefits, medical leave, and holiday entitlement.
Recruitment screening, automatically generating and posting job descriptions, filtering candidates, ranking applicants against defined criteria, identifying the strongest matches, and scheduling interviews.
Employee onboarding, issuing new hires with contracts and paperwork, guiding them to onboarding and training resources, tracking compliance and completion rates, answering routine enquiries, and escalating complex cases to human HR specialists.
Training and development, identifying skills gaps, providing self-service access to upskilling and reskilling opportunities, creating personalized learning pathways aligned with roles and career goals, and tracking progress toward completion.

AI working competency is now a graduation requirement at Purdue [Pacton] + other items re: AI in our learning ecosystems

On 12/16/2025, in 21st century, 24x7x365 access, adjunct faculty, adult learning, Alternatives, Artificial Intelligence/Agents/LLMs/and Related, Asia, Australia, bots, career development, change, changing business models, cloud-based computing / apps / other cloud-related, CMS/LMS, collaboration, colleges, communities of practice, community colleges, computer science, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital learning, education technology, experimentation, faculty/staff, future of higher education, game-changing environment, generational differences, higher education, human-computer interaction (HCI), India, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, law schools, 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, microlearning, online media, personalized/customized learning, platforms, productivity / tips and tricks, student-related, teachers, teaching & learning, technologies for your home, the downsides of how people use tech, tools, training / L&D, trends, UK, United States, universities, vendors, vision/possibilities, youth, by Daniel Christian

AI Has Landed in Education: Now What? — from learningfuturesdigest.substack.com by Dr. Philippa Hardman

Here’s what’s shaped the AI-education landscape in the last month:

The AI Speed Trap is [still] here: AI adoption in L&D is basically won (87%)—but it’s being used to ship faster, not learn better (84% prioritising speed), scaling “more of the same” at pace.
AI tutors risk a “pedagogy of passivity”: emerging evidence suggests tutoring bots can reduce cognitive friction and pull learners down the ICAP spectrum—away from interactive/constructive learning toward efficient consumption.
Singapore + India are building what the West lacks: they’re treating AI as national learning infrastructure—for resilience (Singapore) and access + language inclusion (India)—while Western systems remain fragmented and reactive.
Agentic AI is the next pivot: early signs show a shift from AI as a content engine to AI as a learning partner—with UConn using agents to remove barriers so learners can participate more fully in shared learning.
Moodle’s AI stance sends two big signals: the traditional learning ecosystem in fragmenting, and the concept of “user sovereignty” over by AI is emerging.

Four strategies for implementing custom AIs that help students learn, not outsource — from educational-innovation.sydney.edu.au by Kria Coleman, Matthew Clemson, Laura Crocco and Samantha Clarke; via Derek Bruff

For Cogniti to be taken seriously, it needs to be woven into the structure of your unit and its delivery, both in class and on Canvas, rather than left on the side. This article shares practical strategies for implementing Cogniti in your teaching so that students:

understand the context and purpose of the agent,
know how to interact with it effectively,
perceive its value as a learning tool over any other available AI chatbots, and
engage in reflection and feedback.

In this post, we discuss how to introduce and integrate Cogniti agents into the learning environment so students understand their context, interact effectively, and see their value as customised learning companions.

In this post, we share four strategies to help introduce and integrate Cogniti in your teaching so that students understand their context, interact effectively, and see their value as customised learning companions.

Collection: Teaching with Custom AI Chatbots — from teaching.virginia.edu; via Derek Bruff
The default behaviors of popular AI chatbots don’t always align with our teaching goals. This collection explores approaches to designing AI chatbots for particular pedagogical purposes.

Example/excerpt:

Not Your Default Chatbot: Five Teaching Applications of Custom AI Bots
Agile Learning
derekbruff.org/2025/10/01/five-teaching-applications-of-custom-ai-chatbots/

Higher education faces ‘deteriorating’ 2026 outlook, Fitch says — from highereddive.com by Laura Spitalniak
A shrinking pipeline of students, uncertainty about state and federal support, and rising expenses could all hurt college finances, according to analysts.

Dive Brief:

Fitch Ratings on Thursday issued a “deteriorating” outlook for the higher education sector in 2026, continuing the gloomy prediction the agency issued for 2025.
Analysts based their forecast on a shrinking prospective student base, “rising uncertainty related to state and federal support, continued expense escalation and shifting economic conditions.”
With its report, Fitch joins Moody’s Ratings and S&P Global Ratings in predicting a grim year for higher ed — Moody’s for the sector overall and S&P for nonprofit colleges specifically.

Yale expects layoffs as leaders brace for $300M in endowment taxes — from highereddive.com by Ben Unglesbee
The Ivy League institution’s tax bill starting next year will be higher than what it spends on student aid, university officials said.

Dive Brief:

Yale University is bracing for layoffs as it prepares to pay the government hundreds of millions of dollars in endowment income taxes.
In a public message, senior leaders at the Ivy League institution said that Yale’s schools plan to take steps such as delaying hiring and reducing travel spending to save money. But they warned workforce cuts were on the horizon.
“Layoffs may be necessary” in some units where cutting open positions and other reductions are insufficient, the university officials said. They expect to complete any downsizing by the end of 2026 barring “additional significant financial changes.”

Education Department adds ‘lower earnings’ warning to FAFSA — from highereddive.com by Natalie Schwartz
The agency will warn students when they’ve indicated interest in a college whose graduates have relatively low incomes.

The U.S. Department of Education has launched a new disclosure feature that warns students who fill out the Free Application for Federal Student Aid if they’re interested in colleges whose graduates have relatively low earnings, the agency said Monday.

“Families deserve a clearer picture of how postsecondary education connects to real-world earnings, and this new indicator will provide that transparency,” U.S. Education Secretary Linda McMahon said in a Monday statement. “Not only will this new FAFSA feature make public earnings data more accessible, but it will empower prospective students to make data-driven decisions before they are saddled with debt.”

Also from highereddive.com, see:

College costs grew 3.6% in fiscal 2025, HEPI shows
Faculty salaries rose 4.3%, the highest recorded rate since the Higher Education Price Index began in 1998.
Martin University to ‘pause’ operations at the end of the month
The board of the private Indianapolis university is working to find a path toward economic viability, it said in a Tuesday press release.
Willamette University and Pacific University seek to merge
The two private nonprofits in Oregon said Thursday that they intend to create “the University of the Northwest,” with one state official voicing support.
University of Nebraska regents approve cutting 4 programs at flagship
The university’s governing board voted in favor of the plan despite sustained faculty objections over the eliminations and the process for determining them.

“My students use ChatGPT to attack their own thinking before I ever grade them.” [Winkel] + another item re: AI in our LE’s

On 12/10/2025, in adjunct faculty, adult learning, Artificial Intelligence/Agents/LLMs/and Related, bots, cloud-based computing / apps / other cloud-related, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, creativity, digital learning, education, education technology, emerging technologies, experimentation, faculty/staff, future of higher education, game-changing environment, generational differences, graphics, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, law schools, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning preferences, learning spaces, liberal arts, library / librarians, lifelong learning, multimedia, pedagogy, personalized/customized learning, platforms, productivity / tips and tricks, skills, society, student-related, teachers, teaching & learning, teaching online, technologies for your home, tools, training / L&D, trends, United States, universities, vendors, vision/possibilities, workplace, by Daniel Christian

Beyond Infographics: How to Use Nano Banana to *Actually* Support Learning — from drphilippahardman.substack.com by Dr Philippa Hardman
Six evidence-based use cases to try in Google’s latest image-generating AI tool

While it’s true that Nano Banana generates better infographics than other AI models, the conversation has so far massively under-sold what’s actually different and valuable about this tool for those of us who design learning experiences.

What this means for our workflow:

Instead of the traditional “commission ? wait ? tweak ? approve ? repeat” cycle, Nano Banana enables an iterative, rapid-cycle design process where you can:

Sketch an idea and see it refined in minutes.
Test multiple visual metaphors for the same concept without re-briefing a designer.
Build 10-image storyboards with perfect consistency by specifying the constraints once, not manually editing each frame.
Implement evidence-based strategies (contrasting cases, worked examples, observational learning) that are usually too labour-intensive to produce at scale.

This shift—from “image generation as decoration” to “image generation as instructional scaffolding”—is what makes Nano Banana uniquely useful for the 10 evidence-based strategies below.

Caring for Patients for 26 Years—and Still Not a Nurse — from workshift.org/ by Colleen Connolly

Arnett’s experience spending decades in a job she intended as a first step is common among CNAs, medical assistants, and other entry-level healthcare workers, many of them women of color from low-income backgrounds. Amid a nationwide nursing shortage, elevating those workers seems like an obvious solution, but the path from CNA to nurse isn’t so much a ladder as it is a huge leap.

And obstacle after obstacle is strewn in the way. The high cost of nursing school, lengthy prerequisite requirements, rigid schedules, and unpaid clinical hours make it difficult for many CNAs to advance in their careers, despite their willingness and ability and the dire need of healthcare facilities.

While there are no national statistics about the number of entry-level healthcare workers who move on to higher-paid positions, a study of federal grants for CNA training showed that only 3% of those who completed the training went on to pursue further education to become an LPN or RN. Only 1% obtained an associate degree or above. A similar study in California showed that 22% of people who completed CNA certificate programs at community colleges went on to get a higher-level educational credential in health, but only 13% became registered nurses within six years.

That reality perpetuates chronic shortages in nursing, and it also keeps hundreds of thousands of healthcare workers locked below a living wage, often for decades.

“Introducing AI assistants with memory” + other items re: AI in our learning ecosystems

On 12/01/2025, in accessibility / UDL, adjunct faculty, Artificial Intelligence/Agents/LLMs/and Related, bots, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate universities / corporate training, digital learning, digital video, education, education technology, emerging technologies, experimentation, faculty/staff, future of higher education, game-changing environment, generational differences, Google, higher education, human-computer interaction (HCI), innovation, instructional design, intelligent systems, IT in HE, 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, memory, multimedia, personalized/customized learning, platforms, productivity / tips and tricks, student-related, teachers, teaching & learning, tools, training / L&D, trends, United States, universities, vendors, by Daniel Christian

4 Simple & Easy Ways to Use AI to Differentiate Instruction — from mindfulaiedu.substack.com (Mindful AI for Education) by Dani Kachorsky, PhD
Designing for All Learners with AI and Universal Design Learning

So this year, I’ve been exploring new ways that AI can help support students with disabilities—students on IEPs, learning plans, or 504s—and, honestly, it’s changing the way I think about differentiation in general.

As a quick note, a lot of what I’m finding applies just as well to English language learners or really to any students. One of the big ideas behind Universal Design for Learning (UDL) is that accommodations and strategies designed for students with disabilities are often just good teaching practices. When we plan instruction that’s accessible to the widest possible range of learners, everyone benefits. For example, UDL encourages explaining things in multiple modes—written, visual, auditory, kinesthetic—because people access information differently. I hear students say they’re “visual learners,” but I think everyone is a visual learner, and an auditory learner, and a kinesthetic learner. The more ways we present information, the more likely it is to stick.

So, with that in mind, here are four ways I’ve been using AI to differentiate instruction for students with disabilities (and, really, everyone else too):

The Periodic Table of AI Tools In Education To Try Today — from ictevangelist.com by Mark Anderson

What I’ve tried to do is bring together genuinely useful AI tools that I know are already making a difference.

For colleagues wanting to explore further, I’m sharing the list exactly as it appears in the table, including website links, grouped by category below. Please do check it out, as along with links to all of the resources, I’ve also written a brief summary explaining what each of the different tools do and how they can help.

Seven Hard-Won Lessons from Building AI Learning Tools — from linkedin.com by Louise Worgan

Last week, I wrapped up Dr Philippa Hardman’s intensive bootcamp on AI in learning design. Four conversations, countless iterations, and more than a few humbling moments later – here’s what I am left thinking about.

Finally Catching Up to the New Models — from michellekassorla.substack.com by Michelle Kassorla
There are some amazing things happening out there!

An aside: Google is working on a new vision for textbooks that can be easily differentiated based on the beautiful success for NotebookLM. You can get on the waiting list for that tool by going to LearnYourWay.withgoogle.com.
…
Nano Banana Pro
Sticking with the Google tools for now, Nano Banana Pro (which you can use for free on Google’s AI Studio), is doing something that everyone has been waiting a long time for: it adds correct text to images.

Introducing AI assistants with memory — from perplexity.ai

The simple act of remembering is the crux of how we navigate the world: it shapes our experiences, informs our decisions, and helps us anticipate what comes next. For AI agents like Comet Assistant, that continuity leads to a more powerful, personalized experience.

Today we are announcing new personalization features to remember your preferences, interests, and conversations. Perplexity now synthesizes them automatically like memory, for valuable context on relevant tasks. Answers are smarter, faster, and more personalized, no matter how you work.

From DSC :
This should be important as we look at learning-related applications for AI.

For the last three days, my Substack has been in the top “Rising in Education” list. I realize this is based on a hugely flawed metric, but it still feels good. ?

– Michael G Wagner

Read on Substack

I’m a Professor. A.I. Has Changed My Classroom, but Not for the Worse. — from nytimes.com by Carlo Rotella [this should be a gifted article]
My students’ easy access to chatbots forced me to make humanities instruction even more human.

Law Firm 2.0: A Trillion-Dollar Market Begins To Move — from abovethelaw.com by Ken Crutchfield
The test cases for Law Firm 2.0 are arriving faster than many expected.

A move to separate legal advice from other legal services that don’t require advice is a big shift that would ripple through established firms and also test regulatory boundaries.
…
The LegalTech Fund (TLTF) sees a $1 trillion opportunity to reinvent legal services through the convergence of technology, regulatory changes, and innovation. TLTF calls this movement Law Firm 2.0, and the fund believes a reinvention will pave the way for entirely new, tech-enabled models of legal service delivery.

From Paper to Platform: How LegalTech Is Revolutionizing the Practice of Law — from markets.financialcontent.com by AB Newswire

For decades, practicing law has been a business about paper — contracts, case files, court documents, and floor-to-ceiling piles of precedent. But as technology transforms all aspects of modern-day business, law firms and in-house legal teams are transforming along with it. The development of LegalTech has revolutionized what was previously a paper-driven, manpower-intensive profession into a data-driven digital web of collaboration and automation.

Conclusion: Building the Future of Law
The practice of law has always been about accuracy, precedent, and human beings. Technology doesn’t alter that — it magnifies it. The shift to the platform from paper is about liberating lawyers from back-office tasks so they can concentrate on strategy, advocacy, and creativity.

By coupling intelligent automation with moral obligation, today’s firms are positioning the legal profession for a more intelligent, responsive industry. LegalTech isn’t about automation, it’s about empowering attorneys to practice at the speed of today’s business.

What Legal Can Learn from Other Industries’ AI Transformations — from jdsupra.com

Artificial intelligence has already redefined how industries like finance, healthcare, and supply chain operate — transforming once-manual processes into predictive, data-driven engines of efficiency.

Yet the legal industry, while increasingly open to innovation, still lags behind its peers in adopting automation at scale. As corporate legal departments face mounting pressure to do more with less, they have an opportunity to learn from how other sectors successfully integrated AI into their operations.

The message is clear: AI transformation doesn’t just change workflows — it changes what’s possible.

7 Legal Tech Trends To Watch In 2026 — from lexology.com

Small Language Models Are Changing Legal Tech: What That Means for Lawyers and Law Firms — from community.nasscom.in

The legal profession is at a turning point. Artificial intelligence tools are moving from novelty to everyday utility, and small language models, or SLMs, are a major reason why. For law firms and in-house legal teams that are balancing client confidentiality, tight budgets, and the need to move faster, SLMs offer a practical, high impact way to bring legal AI into routine practice. This article explains what SLMs are, why they matter to lawyers, where they fit in legal workflows, and how to adopt them responsibly.

Legal AI startup draws new $50 million Blackstone investment, opens law firm — from reuters.com by Sara Merken

NEW YORK, Nov 20 (Reuters) – Asset manager Blackstone (BX.N), opens new tab has invested $50 million in Norm Ai, a legal and compliance technology startup that also said on Thursday that it is launching an independent law firm that will offer “AI-native legal services.”

Lawyers at the new New York-based firm, Norm Law LLP, will use Norm Ai’s artificial intelligence technology to do legal work for Blackstone and other financial services clients, said Norm Ai founder and CEO John Nay.

Law School Toolbox Podcast Episode 531: What Law Students Should Know About New Legal Tech (w/Gabe Teninbaum) — from jdsupra.com

Today, Alison and Gabe Teninbaum — law professor and creator of SpacedRepetition.com — discuss how technology is rapidly transforming the legal profession, emphasizing the importance for law students and lawyers to develop technological competence and adapt to new tools and roles in the legal profession.

New York is the San Francisco of legal tech — from businessinsider.com by Melia Russell

Legal tech ?? NYC.
To win the market, startups say they need to be where the law firms and corporate legal chiefs are.
Legora and Harvey are expanding their footprints in New York, as Clio hunts for office space.

Legal Tech Startups Expand in New York to Access Law Firms — from indexbox.io

Several legal technology startups are expanding their physical presence in New York City, according to a report from Legal tech NYC. The companies state that to win market share, they need to be located where major law firms and corporate legal departments are based.

Linklaters unveils 20-strong ‘AI lawyer’ team — from legalcheek.com by Legal Cheek

Magic Circle giant Linklaters has launched a team of 20 ‘AI Lawyers’ (yes, that is their actual job title) as it ramps up its commitment to artificial intelligence across its global offices.

The new cohort is a mix of external tech specialists and Linklaters lawyers who have decided to boost their legal expertise with advanced AI know-how. They will be placed into practice groups around the world to help build prompts, workflows and other tech driven processes that the firm hopes will sharpen client delivery.

I went to a closed-door retreat for top lawyers. The message was clear: Don’t fear AI — use it. — from businessinsider.com by Melia Russell

AI is making its mark on law firms and corporate legal teams.
Clients expect measurable savings, and firms are spending real money to deliver them.
At TLTF Summit, Big Law leaders and legal-tech builders explored the future of the industry.

From Cost Center to Command Center: The Future of Litigation is Being Built In-House — from law.stanford.edu by Adam Rouse, Tamra Moore, Renee Meisel, Kassi Burns, & Olga Mack

Litigation isn’t going away, but who leads, drafts, and drives it is rapidly changing. Empirical research shows corporate legal departments have steadily expanded litigation management functions over the past decade. (Annual Litigation Trends Survey, Norton Rose Fulbright (2025)).

For decades, litigation lived squarely in the law firm domain. (Wald, Eli, Getting in and Out of the House: Career Trajectories of In-House Lawyers, Fordham Law Review, Vol. 88, No. 1765, 2020 (June 22, 2020)). Corporate legal departments played a responsive role: approving strategies, reviewing documents, and paying hourly rates. But through dozens of recent conversations with in-house legal leaders, legal operations professionals, and litigation specialists, a new reality is emerging. One in which in-house counsel increasingly owns the first draft, systematizes their litigation approach, and reshapes how outside counsel fits into the picture.

AI, analytics, exemplar libraries, playbooks, and modular document builders are not simply tools. They are catalysts for a structural shift. Litigation is becoming modular, data-informed, and orchestrated by in-house teams who increasingly want more than cost control. They want consistency, clarity, and leverage. This piece outlines five major trends from our qualitative research, predictions on their impact to the practice of law, and research questions that are worth considering to further understand these trends. A model is then introduced for understanding how litigation workflows and outside counsel relationships will evolve in the coming years.

“The AI opportunity in L&D isn’t one thing – it’s five different capability unlocks.” [Vinauskaite] + other items re: AI in our LE’s

On 11/21/2025, in Artificial Intelligence/Agents/LLMs/and Related, business, cloud-based computing / apps / other cloud-related, colleges, community colleges, corporate / business world, corporate universities / corporate training, digital learning, emerging technologies, faculty/staff, game-changing environment, higher education, innovation, instructional design, learning agents, learning ecosystem, Learning Experience Design, memory, online learning, Open AI, pedagogy, platforms, productivity / tips and tricks, professional development, simulations, skills, student-related, teachers, teaching & learning, tools, training / L&D, United States, universities, workplace, by Daniel Christian

AI’s Role in Online Learning > Take It or Leave It with Michelle Beavers, Leo Lo, and Sara McClellan — from intentionalteaching.buzzsprout.com by Derek Bruff

You’ll hear me briefly describe five recent op-eds on teaching and learning in higher ed. For each op-ed, I’ll ask each of our panelists if they “take it,” that is, generally agree with the main thesis of the essay, or “leave it.” This is an artificial binary that I’ve found to generate rich discussion of the issues at hand.

New Study: Business As Usual Could Doom Dozens Of New England Colleges — from forbes.com by Michael B. Horn

The cause of the challenges isn’t one single factor, but a series of pressures from demographic changes, shifts in the public’s perception of higher education’s value, rising operating costs, emerging alternatives to traditional colleges, and, of late, changes in federal policies and programs. The net effect is that many institutions are much closer to the brink of closure than ever before.

What’s daunting is that flat enrollment is almost certainly an overly optimistic scenario.

If enrollment at the 44 schools falls by 15 percent over the next four years and business proceeds as usual, then 28 of the schools will have less than 10 years of cash and unrestricted quasi-endowments before they would become insolvent—assuming no major cuts, additional philanthropy, new debt, or asset sales. Fourteen would have less than five years before insolvency.

Also see:

A Looming Crisis: New Analysis Shows Dozens of Well-Known Colleges Are Near Financial Trouble — from michaelbhorn.substack.com by Michael B. Horn and Steven M. Shulman

From DSC:
The cultures at many institutions of traditional higher education will make some of the necessary changes and strategies (that Michael and Steven discuss) very hard to make. For example, to merge with another institution or institutions. Such a strategy could be very challenging to implement, even as alternatives continue to emerge.

“Textbooks are no longer one-size-fits-all” [Fitzpatrick] + other items re: AI in our learning ecosystems

On 11/18/2025, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, bots, change, changing business models, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital learning, education, education technology, emerging technologies, experimentation, faculty/staff, game-changing environment, generational differences, Google, higher education, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, K-12 related, law schools, learner profiles, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning preferences, learning spaces, liberal arts, lifelong learning, Open AI, platforms, productivity / tips and tricks, student-related, teachers, teaching & learning, technologies for your home, training / L&D, trends, United States, universities, vendors, by Daniel Christian

Three Years from GPT-3 to Gemini 3 — from oneusefulthing.org by Ethan Mollick
From chatbots to agents

Three years ago, we were impressed that a machine could write a poem about otters. Less than 1,000 days later, I am debating statistical methodology with an agent that built its own research environment. The era of the chatbot is turning into the era of the digital coworker. To be very clear, Gemini 3 isn’t perfect, and it still needs a manager who can guide and check it. But it suggests that “human in the loop” is evolving from “human who fixes AI mistakes” to “human who directs AI work.” And that may be the biggest change since the release of ChatGPT.

Results May Vary — from aiedusimplified.substack.com by Lance Eaton, PhD
On Custom Instructions with GenAI Tools….

I’m sharing today about custom instructions and my use of them across several AI tools (paid versions of ChatGPT, Gemini, and Claude). I want to highlight what I’m doing, how it’s going, and solicit from readers to share in the comments some of their custom instructions that they find helpful.

I’ve been in a few conversations lately that remind me that not everyone knows about them, even some of the seasoned folks around GenAI and how you might set them up to better support your work. And, of course, they are, like all things GenAI, highly imperfect!

I’ll include and discuss each one below, but if you want to keep abreast of my custom instructions, I’ll be placing them here as I adjust and update them so folks can see the changes over time.

How is AI impacting the learning ecosystems out there (esp. L&D)? Check these postings out.

On 11/13/2025, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, assessment, bots, change, cloud-based computing / apps / other cloud-related, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate universities / corporate training, digital learning, education technology, emerging technologies, Europe, faculty/staff, future of higher education, game-changing environment, generational differences, global / globalization, Google, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, law schools, learner profiles, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning preferences, learning spaces, learning theories, liberal arts, library / librarians, lifelong learning, Microsoft, online learning, productivity / tips and tricks, skills, society, student-related, teachers, teaching & learning, tools, training / L&D, trends, UK, United States, universities, vendors, vision/possibilities, workplace, by Daniel Christian

Gen AI Is Going Mainstream: Here’s What’s Coming Next — from joshbersin.com by Josh Bersin

I just completed nearly 60,000 miles of travel across Europe, Asia, and the Middle East meeting with hundred of companies to discuss their AI strategies. While every company’s maturity is different, one thing is clear: AI as a business tool has arrived: it’s real and the use-cases are growing.

A new survey by Wharton shows that 46% of business leaders use Gen AI daily and 80% use it weekly. And among these users, 72% are measuring ROI and 74% report a positive return. HR, by the way, is the #3 department in use cases, only slightly behind IT and Finance.

What are companies getting out of all this? Productivity. The #1 use case, by far, is what we call “stage 1” usage – individual productivity.

.

From DSC:
Josh writes: “Many of our large clients are now implementing AI-native learning systems and seeing 30-40% reduction in staff with vast improvements in workforce enablement.”

While I get the appeal (and ROI) from management’s and shareholders’ perspective, this represents a growing concern for employment and people’s ability to earn a living.

And while I highly respect Josh and his work through the years, I disagree that we’re over the problems with AI and how people are using it:

Two years ago the NYT was trying to frighten us with stories of AI acting as a romance partner. Well those stories are over, and thanks to a $Trillion (literally) of capital investment in infrastructure, engineering, and power plants, this stuff is reasonably safe.

Those stories are just beginning…they’re not close to being over.

“… imagine a world where there’s no separation between learning and assessment…” — from aiedusimplified.substack.com by Lance Eaton, Ph.D. and Tawnya Means
An interview with Tawnya Means

So let’s imagine a world where there’s no separation between learning and assessment: it’s ongoing. There’s always assessment, always learning, and they’re tied together. Then we can ask: what is the role of the human in that world? What is it that AI can’t do?
…
Imagine something like that in higher ed. There could be tutoring or skill-based work happening outside of class, and then relationship-based work happening inside of class, whether online, in person, or some hybrid mix.

The aspects of learning that don’t require relational context could be handled by AI, while the human parts remain intact. For example, I teach strategy and strategic management. I teach people how to talk with one another about the operation and function of a business. I can help students learn to be open to new ideas, recognize when someone pushes back out of fear of losing power, or draw from my own experience in leading a business and making future-oriented decisions.

But the technical parts such as the frameworks like SWOT analysis, the mechanics of comparing alternative viewpoints in a boardroom—those could be managed through simulations or reports that receive immediate feedback from AI. The relational aspects, the human mentoring, would still happen with me as their instructor.

Part 2 of their interview is here:

“They’re not necessarily trying to cheat; they’re just being efficient”

A New AI Career Ladder — from ssir.org (Stanford Social Innovation Review) by Bruno V. Manno; via Matt Tower
The changing nature of jobs means workers need new education and training infrastructure to match.

AI has cannibalized the routine, low-risk work tasks that used to teach newcomers how to operate in complex organizations. Without those task rungs, the climb up the opportunity ladder into better employment options becomes steeper—and for many, impossible. This is not a temporary glitch. AI is reorganizing work, reshaping what knowledge and skills matter, and redefining how people are expected to acquire them.

The consequences ripple from individual career starts to the broader American promise of economic and social mobility, which includes both financial wealth and social wealth that comes from the networks and relationships we build. Yet the same technology that complicates the first job can help us reinvent how experience is earned, validated, and scaled. If we use AI to widen—not narrow—access to education, training, and proof of knowledge and skill, we can build a stronger career ladder to the middle class and beyond. A key part of doing this is a redesign of education, training, and hiring infrastructure.

…

What’s needed is a redesigned model that treats work as a primary venue for learning, validates capability with evidence, and helps people keep climbing after their first job. Here are ten design principles for a reinvented education and training infrastructure for the AI era.

Create hybrid institutions that erase boundaries. …
Make work-based learning the default, not the exception. …
Create skill adjacencies to speed transitions. …
Place performance-based hiring at the core. …
Ongoing supports and post-placement mobility. …
Portable, machine-readable credentials with proof attached. …
…plus several more…

Learning Ecosystems

Major Changes Reshape Law Schools Nationwide in 2026 [Fatima]

What 3 credit ratings agencies forecast for higher ed in 2026 [Unglesbee]

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