adjunct faculty

“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.

Why Co-Teaching Will Be A Hot New Trend In Higher Education — from forbes.com by Brandon Busteed

When it comes to innovation in higher education, most bets are being placed on technology platforms and AI. But the innovation students, faculty and industry need most can be found in a much more human dimension: co-teaching. And specifically, a certain kind of co-teaching – between industry experts and educators.

While higher education has largely embraced the value of interdisciplinary teaching across different majors or fields of study, it has yet to embrace the value of co-teaching between industry and academia. Examples of co-teaching through industry-education collaborations are rare and underutilized across today’s higher ed landscape. But they may be the most valuable and relevant way to prepare students for success. And leveraging these collaborations can help institutions struggling to satisfy unfulfilled student demand for immersive work experiences such as internships.

From DSC:
It’s along these lines that I think that ADJUNCT faculty members should be highly sought after and paid much better — as the up-to-date knowledge and experience they bring into the classroom is very valuable. They should have equal say in terms of curriculum/programs and in the way a college or university is run.

“A new L&D operating system for the AI Era?” [Hardman] + other items re: AI in our learning ecosystems

On 10/13/2025, in 21st century, 24x7x365 access, adjunct faculty, adult learning, animation, Artificial Intelligence/Agents/LLMs/and Related, assessment, bots, business, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, creativity, credentialing, digital audio, digital learning, digital storytelling, digital video, education, education technology, educational games / serious games, emerging technologies, engagement / engaging students, 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, interactivity, 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, lifelong learning, pedagogy, personalized/customized learning, productivity / tips and tricks, professional development, skills, story, storytelling, student-related, teachers, teaching & learning, teaching online, technologies for your home, training / L&D, trends, United States, universities, vendors, vision/possibilities, workplace, writing, youth, by Daniel Christian

From 70/20/10 to 90/10 — from drphilippahardman.substack.com by Dr Philippa Hardman
A new L&D operating system for the AI Era?

This week I want to share a hypothesis I’m increasingly convinced of: that we are entering an age of the 90/10 model of L&D.

90/10 is a model where roughly 90% of “training” is delivered by AI coaches as daily performance support, and 10% of training is dedicated to developing complex and critical skills via high-touch, human-led learning experiences.

Proponents of 90/10 argue that the model isn’t about learning less, but about learning smarter by defining all jobs to be done as one of the following:

Delegate (the dead skills): Tasks that can be offloaded to AI.
Co-Create (the 90%): Tasks which well-defined AI agents can augment and help humans to perform optimally.
Facilitate (the 10%): Tasks which require high-touch, human-led learning to develop.

So if AI at work is now both real and material, the natural question for L&D is: how do we design for it? The short answer is to stop treating learning as an event and start treating it as a system.

My daughter’s generation expects to learn with AI, not pretend it doesn’t exist, because they know employers expect AI fluency and because AI will be ever-present in their adult lives.

— Jenny Maxell

The above quote was taken from this posting.

Unlocking Young Minds: How Gamified AI Learning Tools Inspire Fun, Personalized, and Powerful Education for Children in 2025 — from techgenyz.com by Sreyashi Bhattacharya

Table of Contents

Highlight

Gamified AI Learning Tools personalize education by adapting the difficulty and content to each child’s pace, fostering confidence and mastery.
Engaging & Fun: Gamified elements like quests, badges, and stories keep children motivated and enthusiastic.
Safe & Inclusive: Attention to equity, privacy, and cultural context ensures responsible and accessible learning.

How to test GenAI’s impact on learning — from timeshighereducation.com by Thibault Schrepel
Rather than speculate on GenAI’s promise or peril, Thibault Schrepel suggests simple teaching experiments to uncover its actual effects

Generative AI in higher education is a source of both fear and hype. Some predict the end of memory, others a revolution in personalised learning. My two-year classroom experiment points to a more modest reality: Artificial intelligence (AI) changes some skills, leaves others untouched and forces us to rethink the balance.

This indicates that the way forward is to test, not speculate. My results may not match yours, and that is precisely the point. Here are simple activities any teacher can use to see what AI really does in their own classroom.

4. Turn AI into a Socratic partner
Instead of being the sole interrogator, let AI play the role of tutor, client or judge. Have students use AI to question them, simulate cross-examination or push back on weak arguments. New “study modes” now built into several foundation models make this kind of tutoring easy to set up. Professors with more technical skills can go further, design their own GPTs or fine-tuned models trained on course content and let students interact directly with them. The point is the practice it creates. Students learn that questioning a machine is part of learning to think like a professional.

Assessment tasks that support human skills — from timeshighereducation.com by Amir Ghapanchi and Afrooz Purarjomandlangrudi
Assignments that focus on exploration, analysis and authenticity offer a road map for university assessment that incorporates AI while retaining its rigour and human elements

Rethinking traditional formats

1. From essay to exploration
When ChatGPT can generate competent academic essays in seconds, the traditional format’s dominance looks less secure as an assessment task. The future lies in moving from essays as knowledge reproduction to assessments that emphasise exploration and curation. Instead of asking students to write about a topic, challenge them to use artificial intelligence to explore multiple perspectives, compare outputs and critically evaluate what emerges.

Example: A management student asks an AI tool to generate several risk plans, then critiques the AI’s assumptions and identifies missing risks.

What your students are thinking about artificial intelligence — from timeshighereducation.com by Florencia Moore and Agostina Arbia
GenAI has been quickly adopted by students, but the consequences of using it as a shortcut could be grave. A study into how students think about and use GenAI offers insights into how teaching might adapt

However, when asked how AI negatively impacts their academic development, 29 per cent noted a “weakening or deterioration of intellectual abilities due to AI overuse”. The main concern cited was the loss of “mental exercise” and soft skills such as writing, creativity and reasoning.

The boundary between the human and the artificial does not seem so easy to draw, but as the poet Antonio Machado once said: “Traveller, there is no path; the path is made by walking.”

Jelly Beans for Grapes: How AI Can Erode Students’ Creativity — from edsurge.com by Thomas David Moore

There is nothing new about students trying to get one over on their teachers — there are probably cuneiform tablets about it — but when students use AI to generate what Shannon Vallor, philosopher of technology at the University of Edinburgh, calls a “truth-shaped word collage,” they are not only gaslighting the people trying to teach them, they are gaslighting themselves. In the words of Tulane professor Stan Oklobdzija, asking a computer to write an essay for you is the equivalent of “going to the gym and having robots lift the weights for you.”

Deloitte will make Claude available to 470,000 people across its global network — from anthropic.com

As part of the collaboration, Deloitte will establish a Claude Center of Excellence with trained specialists who will develop implementation frameworks, share leading practices across deployments, and provide ongoing technical support to create the systems needed to move AI pilots to production at scale. The collaboration represents Anthropic’s largest enterprise AI deployment to date, available to more than 470,000 Deloitte people.

Deloitte and Anthropic are co-creating a formal certification program to train and certify 15,000 of its professionals on Claude. These practitioners will help support Claude implementations across Deloitte’s network and Deloitte’s internal AI transformation efforts.

How AI Agents are finally delivering on the promise of Everboarding: driving retention when it counts most — from premierconstructionnews.com

Everboarding flips this model. Rather than ending after orientation, everboarding provides ongoing, role-specific training and support throughout the employee journey. It adapts to evolving responsibilities, reinforces standards, and helps workers grow into new roles. For high-turnover, high-pressure environments like retail, it’s a practical solution to a persistent challenge.

AI agents will be instrumental in the success of everboarding initiatives; they can provide a much more tailored training and development process for each individual employee, keeping track of which training modules may need to be completed, or where staff members need or want to develop further. This personalisation helps staff to feel not only more satisfied with their current role, but also guides them on the right path to progress in their individual careers.

Digital frontline apps are also ideal for everboarding. They offer bite-sized training that staff can complete anytime, whether during quiet moments on shift or in real time on the job, all accessible from their mobile devices.

TeachLM: insights from a new LLM fine-tuned for teaching & learning — from drphilippahardman.substack.com by Dr Philippa Hardman
Six key takeaways, including what the research tells us about how well AI performs as an instructional designer

As I and many others have pointed out in recent months, LLMs are great assistants but very ineffective teachers. Despite the rise of “educational LLMs” with specialised modes (e.g. Anthropic’s Learning Mode, OpenAI’s Study Mode, Google’s Guided Learning) AI typically eliminates the productive struggle, open exploration and natural dialogue that are fundamental to learning.

This week, Polygence, in collaboration with Stanford University researcher Prof Dora Demszky. published a first-of-its-kind research on a new model — TeachLM — built to address this gap.

In this week’s blog post, I deep dive what the research found and share the six key findings — including reflections on how well TeachLM performs on instructional design.

The Dangers of using AI to Grade — from marcwatkins.substack.com by Marc Watkins
Nobody Learns, Nobody Gains

AI as an assessment tool represents an existential threat to education because no matter how you try and establish guardrails or best practices around how it is employed, using the technology in place of an educator ultimately cedes human judgment to a machine-based process. It also devalues the entire enterprise of education and creates a situation where the only way universities can add value to education is by further eliminating costly human labor.

For me, the purpose of higher education is about human development, critical thinking, and the transformative experience of having your ideas taken seriously by another human being. That’s not something we should be in a rush to outsource to a machine.

Digital Accessibility with Amy Lomellini — from intentionalteaching.buzzsprout.com by Derek Bruff

In this episode, we explore why digital accessibility can be so important to the student experience. My guest is Amy Lomellini, director of accessibility at Anthology, the company that makes the learning management system Blackboard. Amy teaches educational technology as an adjunct at Boise State University, and she facilitates courses on digital accessibility for the Online Learning Consortium. In our conversation, we talk about the importance of digital accessibility to students, moving away from the traditional disclosure-accommodation paradigm, AI as an assistive technology, and lots more.

“Provosts Are a ‘Release Valve’ for Campus Controversy” [Whitford] + a variety of items re: higher education in general

On 09/19/2025, in adjunct faculty, apprenticeships, business, business side of he, career development, change, changing business models, collaboration, colleges, community colleges, corporate / business world, cost of getting a degree, faculty/staff, funding / grants, future of higher education, game-changing environment, generational differences, higher education, ideas, innovation, instructional design, leadership, learning ecosystem, Learning Experience Design, liberal arts, pace of change, parents/guardians, participation, pedagogy, real-world assignments, reinvent, skills, student-related, teaching & learning, traditional / tradition, trends, United States, universities, vision/possibilities, workplace, by Daniel Christian

Provosts Are a ‘Release Valve’ for Campus Controversy — from insidehighered.com by Emma Whitford
According to former Western Michigan provost Julian Vasquez Heilig, provosts are stuck driving change with few, if any, allies, while simultaneously playing crisis manager for the university.

After two years, he stepped down, and he now serves as a professor of educational leadership, research and technology at Western Michigan. His frustrations with the provost role had less to do with Western Michigan and more to do with how the job is designed, he explained. “Each person sees the provost a little differently. The faculty see the provost as administration, although, honestly, around the table at the cabinet, the provost is probably the only faculty member,” Heilig said. “The trustees—they see the provost as a middle manager below the president, and the president sees [the provost] as a buffer from issues that are arising.”

Inside Higher Ed sat down with Heilig to talk about the provost job and all he’s learned about the role through years of education leadership research, conversations with colleagues and his own experience.

Brandeis University launches a new vision for American higher education, reinventing liberal arts and emphasizing career development — from brandeis.edu

Levine unveiled “The Brandeis Plan to Reinvent the Liberal Arts,” a sweeping redesign of academic structures, curricula, degree programs, teaching methods, career education, and student support systems. Developed in close partnership with Brandeis faculty, the plan responds to a rapidly shifting landscape in which the demands on higher education are evolving at unprecedented speed in a global, digital economy.

“We are living through a time of extraordinary change across technology, the economy, and society,” Levine said. “Today’s students need more than knowledge. They need the skills, experiences, and confidence to lead in a world we cannot yet predict. We are advancing a new model. We need reinvention. And that’s exactly what Brandeis is establishing.”

The Brandeis Plan transforms the student experience by integrating career preparation into every stage of a student’s education, requiring internships or apprenticeships, sustaining career counseling, and implementing a core curriculum built around the skills that employers value most. The plan also reimagines teaching. It will be more experiential and practical, and introduce new ways to measure and showcase student learning and growth over time.

Tuition Tracker from the Hechinger Report

“The next chapter in learning’s evolution” [Gonick] + other items re: AI in our learning ecosystems

On 09/17/2025, in 21st century, 24x7x365 access, adjunct faculty, Artificial Intelligence/Agents/LLMs/and Related, change, cloud-based computing / apps / other cloud-related, CMS/LMS, colleges, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital learning, education technology, emerging technologies, faculty/staff, future, future of higher education, game-changing environment, generational differences, Google, 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, learning spaces, liberal arts, lifelong learning, Microsoft, online learning, Open AI, productivity / tips and tricks, professional development, skills, student-related, teaching & learning, teaching online, technologies for your home, tools, training / L&D, trends, United States, universities, user experience (UX), vendors, vision/possibilities, youth, by Daniel Christian

From EdTech to TechEd: The next chapter in learning’s evolution — from linkedin.com by Lev Gonick

A day in the life: The next 25 years
A learner wakes up. Their AI-powered learning coach welcomes them, drawing their attention to their progress and helping them structure their approach to the day. A notification reminds them of an upcoming interview and suggests reflections to add to their learning portfolio.

Rather than a static gradebook, their portfolio is a dynamic, living record, curated by the student, validated by mentors in both industry and education, and enriched through co-creation with maturing modes of AI. It tells a story through essays, code, music, prototypes, journal reflections, and team collaborations. These artifacts are not “submitted”, they are published, shared, and linked to verifiable learning outcomes.

And when it’s time to move, to a new institution, a new job, or a new goal, their data goes with them, immutable, portable, verifiable, and meaningful.

From DSC:
And I would add to that last solid sentence that the learner/student/employee will be able to control who can access this information. Anyway, some solid reflections here from Lev.

AI Could Surpass Schools for Academic Learning in 5-10 Years — from downes.ca with commentary from Stephen Downes

I know a lot of readers will disagree with this, and the timeline feels aggressive (the future always arrives more slowly than pundits expect) but I think the overall premise is sound: “The concept of a tipping point in education – where AI surpasses traditional schools as the dominant learning medium – is increasingly plausible based on current trends, technological advancements, and expert analyses.”

The world’s first AI cabinet member — from therundown.ai by Zach Mink, Rowan Cheung, Shubham Sharma, Joey Liu & Jennifer Mossalgue

The Rundown: In this tutorial, you will learn how to combine NotebookLM with ChatGPT to master any subject faster, turning dense PDFs into interactive study materials with summaries, quizzes, and video explanations.

Step-by-step:

Go to notebooklm.google.com, click the “+” button, and upload your PDF study material (works best with textbooks or technical documents)
Choose your output mode: Summary for a quick overview, Mind Map for visual connections, or Video Overview for a podcast-style explainer with visuals
Generate a Study Guide under Reports — get Q&A sets, short-answer questions, essay prompts, and glossaries of key terms automatically
Take your PDF to ChatGPT and prompt: “Read this chapter by chapter and highlight confusing parts” or “Quiz me on the most important concepts”
Combine both tools: Use NotebookLM for quick context and interactive guides, then ChatGPT to clarify tricky parts and go deeperPro Tip: If your source is in EPUB or audiobook, convert it to PDF before uploading. Both NotebookLM and ChatGPT handle PDFs best.

Claude can now create and edit files — from anthropic.com

Claude can now create and edit Excel spreadsheets, documents, PowerPoint slide decks, and PDFs directly in Claude.ai and the desktop app. This transforms how you work with Claude—instead of only receiving text responses or in-app artifacts, you can describe what you need, upload relevant data, and get ready-to-use files in return.

Also see:

Microsoft to lessen reliance on OpenAI by buying AI from rival Anthropic — from techcrunch.com byRebecca Bellan
Microsoft will pay to use Anthropic’s AI in Office 365 apps, The Information reports, citing two sources. The move means that Anthropic’s tech will help power new features in Word, Excel, Outlook, and PowerPoint alongside OpenAI’s, marking the end of Microsoft’s previous reliance solely on the ChatGPT maker for its productivity suite. Microsoft’s move to diversify its AI partnerships comes amid a growing rift with OpenAI, which has pursued its own infrastructure projects as well as a potential LinkedIn competitor.

Ep. 11 AGI and the Future of Higher Ed: Talking with Ray Schroeder

In this episode of Unfixed, we talk with Ray Schroeder—Senior Fellow at UPCEA and Professor Emeritus at the University of Illinois Springfield—about Artificial General Intelligence (AGI) and what it means for the future of higher education. While most of academia is still grappling with ChatGPT and basic AI tools, Schroeder is thinking ahead to AI agents, human displacement, and AGI’s existential implications for teaching, learning, and the university itself. We explore why AGI is so controversial, what institutions should be doing now to prepare, and how we can respond responsibly—even while we’re already overwhelmed.

Best AI Tools for Instructional Designers — from blog.cathy-moore.com by Cathy Moore

Data from the State of AI and Instructional Design Report revealed that 95.3% of the instructional designers interviewed use AI in their daily work [1]. And over 85% of this AI use occurs during the design and development process.

These figures showcase the immense impact AI is already having on the instructional design world.

If you’re an L&D professional still on the fence about adding AI to your workflow or an AI convert looking for the next best tools, keep reading.

This guide breaks down 5 of the top AI tools for instructional designers in 2025, so you can streamline your development processes and build better training faster.

But before we dive into the tools of the trade, let’s address the elephant in the room:

3 Human Skills That Make You Irreplaceable in an AI World — from gettingsmart.com/ by Tom Vander Ark and Mason Pashia

Key Points

Update learner profiles to emphasize curiosity, curation, and connectivity, ensuring students develop irreplaceable human skills.
Integrate real-world learning experiences and mastery-based assessments to foster agency, purpose, and motivation in students.

“…students to use AI to help businesses solve ‘real world’ challenges” [McVicar] + other items re: AI in our learning ecosystems

On 09/09/2025, in adjunct faculty, adult learning, Artificial Intelligence/Agents/LLMs/and Related, bots, business, career development, change, cloud-based computing / apps / other cloud-related, collaboration, colleges, communities of practice, community colleges, content development, aggregation, repositories, copyright/ownership/NFTs, corporate / business world, corporate universities / corporate training, curriculum, data related items, digital audio, digital learning, digital storytelling, digital video, education technology, emerging technologies, experimentation, faculty/staff, future, future of higher education, game-changing environment, generational differences, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, leadership, learner profiles, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning preferences, liberal arts, multimedia, personalized/customized learning, platforms, productivity / tips and tricks, real-world assignments, reinvent, skills, society, staying relevant, student-related, teachers, teaching & learning, trends, United States, universities, vendors, vision/possibilities, workplace, by Daniel Christian

GRCC students to use AI to help businesses solve ‘real world’ challenges in new course — from www-mlive-com.cdn.ampproject.org by Brian McVicar; via Patrick Bailey on LinkedIn

GRAND RAPIDS, MI — A new course at Grand Rapids Community College aims to help students learn about artificial intelligence by using the technology to solve real-world business problems.
…
In a release, the college said its grant application was supported by 20 local businesses, including Gentex, TwistThink and the Grand Rapids Public Museum. The businesses have pledged to work with students who will use business data to develop an AI project such as a chatbot that interacts with customers, or a program that automates social media posts or summarizes customer data.

“This rapidly emerging technology can transform the way businesses process data and information,” Kristi Haik, dean of GRCC’s School of Science, Technology, Engineering and Mathematics, said in a statement. “We want to help our local business partners understand and apply the technology. We also want to create real experiences for our students so they enter the workforce with demonstrated competence in AI applications.”

As Patrick Bailey said on LinkedIn about this article:

Nice to see a pedagogy that’s setting a forward movement rather than focusing on what could go wrong with AI in a curriculum.

Forecast for Learning and Earning in 2025-2026 report — from pages.asugsvsummit.com by Jennifer Lee and Claire Zau

In this look ahead at the future of learning and work, we aim to define:

Major thematic observations
What makes this moment an inflection point
Key predictions (and their precedent)
Short- and long-term projected impacts

The LMS at 30: From Course Management to Learning Management (At Last) — from onedtech.philhillaa.com; a guest post from Matthew Pittinsky, Ph.D.

As a 30 year observer and participant, it seems to me that previous technology platform shifts like SaaS and mobile did not fundamentally change the LMS. AI is different. We’re standing at the precipice of LMS 2.0, where the branding change from Course Management System to Learning Management System will finally live up to its name. Unlike SaaS or mobile, AI represents a technology platform shift that will transform the way participants interact with learning systems – and with it, the nature of the LMS itself.

Given the transformational potential of AI, it is useful to set the context and think about how we got here, especially on this 30th anniversary of the LMS.

LMS at 30 Part 2: Learning Management in the AI Era — from onedtech.philhillaa.com; a guest post from Matthew Pittinsky, Ph.D.

Where AI is disruptive is in its ability to introduce a whole new set of capabilities that are best described as personalized learning services. AI offers a new value proposition to the LMS, roughly the set of capabilities currently being developed in the AI Tutor / agentic TA segment. These new capabilities are so valuable given their impact on learning that I predict they will become the services with greatest engagement within a school or university’s “enterprise” instructional platform.

In this way, by LMS paradigm shift, I specifically mean a shift from buyers valuing the product on its course-centric and course management capabilities, to valuing it on its learner-centric and personalized learning capabilities.

AI and the future of education: disruptions, dilemmas and directions — from unesdoc.unesco.org

This anthology reveals how the integration of AI in education poses profound philosophical, pedagogical, ethical and political questions. As this global AI ecosystem evolves and becomes increasingly ubiquitous, UNESCO and its partners have a shared responsibility to lead the global discourse towards an equity- and justice-centred agenda. The volume highlights three areas in which UNESCO will continue to convene and lead a global commons for dialog and action particularly in areas on AI futures, policy and practice innovation, and experimentation.

As guardian of ethical, equitable human-centred AI in education.
As thought leader in reimagining curriculum and pedagogy
As a platform for engaging pluralistic and contested dialogues

AI, copyright and the classroom: what higher education needs to know — from timeshighereducation.com by Cayce Myers
As artificial intelligence reshapes teaching and research, one legal principle remains at the heart of our work: copyright. Understanding its implications isn’t just about compliance – it’s about protecting academic integrity, intellectual property and the future of knowledge creation. Cayce Myers explains

The School Year We Finally Notice “The Change” — from americanstogether.substack.com by Jason Palmer

Why It Matters
A decade from now, we won’t say “AI changed schools.” We’ll say: this was the year schools began to change what it means to be human, augmented by AI.

This transformation isn’t about efficiency alone. It’s about dignity, creativity, and discovery, and connecting education more directly to human flourishing. The industrial age gave us schools to produce cookie-cutter workers. The digital age gave us knowledge anywhere, anytime. The AI age—beginning now—gives us back what matters most: the chance for every learner to become infinitely capable.

This fall may look like any other—bells ringing, rows of desks—but beneath the surface, education has begun its greatest transformation since the one-room schoolhouse.

How should universities teach leadership now that teams include humans and autonomous AI agents? — from timeshighereducation.com by Alex Zarifis
Trust and leadership style are emerging as key aspects of teambuilding in the age of AI. Here are ways to integrate these considerations with technology in teaching

Transactional and transformational leaderships’ combined impact on AI and trust
Given the volatile times we live in, a leader may find themselves in a situation where they know how they will use AI, but they are not entirely clear on the goals and journey. In a teaching context, students can be given scenarios where they must lead a team, including autonomous AI agents, to achieve goals. They can then analyse the situations and decide what leadership styles to apply and how to build trust in their human team members. Educators can illustrate this decision-making process using a table (see above).

They may need to combine transactional leadership with transformational leadership, for example. Transactional leadership focuses on planning, communicating tasks clearly and an exchange of value. This works well with both humans and automated AI agents.

“A tight housing market and a fragile job market mean those working in higher ed have fewer options than ever.” [Murphy]

On 09/05/2025, in adjunct faculty, business side of he, career development, change, colleges, community colleges, faculty/staff, funding / grants, higher education, teaching & learning, trends, United States, universities, by Daniel Christian

Higher ed’s ‘hunker-down mindset’ — from open-campus-dispatch.beehiiv.com by Colleen Murphy
A tight housing market and a fragile job market mean those working in higher ed have fewer options than ever.

Faculty and administrators could be just as constrained by the golden handcuffs of a 2% interest rate as everybody else. That makes them less likely to move for a new job, Kelchen said, especially since they’re unlikely to get the type of salary increase they’d need to offset more pricey mortgage payments. Plus, even finding an affordable house in the first place could be a challenge right now.

All of this contributes to what Kelchen called a “hunker-down mindset” in higher ed.

“Even if the institutions are giving out pay raises, the pay raises aren’t matching housing costs,” Kelchen said. “And then that creates a pressure to stay.”

While that might seem like a “first-world problem,” it also affects college and university staff members, Kelchen told me. Often the only way for staff members to make more money is to move universities — there aren’t the same in-house growth opportunities as there are for faculty. But that’s easier said than done.

“The World’s First AI Language Learning Agent” + numerous other items re: AI in our learning ecosystems

On 09/03/2025, in adjunct faculty, Artificial Intelligence/Agents/LLMs/and Related, bots, change, changing business models, cloud-based computing / apps / other cloud-related, colleges, communities of practice, community colleges, content development, aggregation, repositories, curriculum, digital learning, education, education reform, education technology, emerging technologies, engagement / engaging students, experimentation, faculty/staff, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, languages and translation, learning, learning agents, learning ecosystem, Learning Experience Design, learning preferences, learning spaces, liberal arts, lifelong learning, new business models, online media, personalized/customized learning, productivity / tips and tricks, professional development, skills, student-related, teachers, teaching & learning, tools, trends, United States, universities, vendors, by Daniel Christian

Midoo AI Launches the World’s First AI Language Learning Agent, Redefining How People Learn Languages — from morningstar.com

SINGAPORE Sept. 3, 2025 /PRNewswire/ — Today, Midoo AI proudly announces the launch of the world’s first AI language learning agent, a groundbreaking innovation set to transform language education forever.

For decades, language learning has pursued one ultimate goal: true personalization. Traditional tools offered smart recommendations, gamified challenges, and pre-written role-play scripts—but real personalization remained out of reach. Midoo AI changes that. Here is the >launch video of Midoo AI.

Imagine a learning experience that evolves with you in real time. A system that doesn’t rely on static courses or scripts but creates a dynamic, one-of-a-kind language world tailored entirely to your needs. This is the power of Midoo’s Dynamic Generation technology.

“Midoo is not just a language-learning tool,” said Yvonne, co-founder of Midoo AI. “It’s a living agent that senses your needs, adapts instantly, and shapes an experience that’s warm, personal, and alive. Learning is no longer one-size-fits-all—now, it’s yours and yours alone.”

Midoo AI Review: Meet the First AI Language Learning Agent — from autogpt.net

Language learning apps have traditionally focused on exercises, quizzes, and progress tracking. Midoo AI introduces a different approach. Instead of presenting itself as a course provider, it acts as an intelligent learning agent that builds, adapts, and sustains a learner’s journey.

This review examines how Midoo AI operates, its feature set, and what makes it distinct from other AI-powered tutors.

Midoo AI in Context: Purpose and Position
Midoo AI is not structured around distributing lessons or modules. Its core purpose is to provide an agent-like partner that adapts in real time. Where many platforms ask learners to select a “level” or “topic,”

Midoo instead begins by analyzing goals, usage context, and error patterns. The result is less about consuming predesigned units and more about co-constructing a pathway.

AI Isn’t Replacing Teachers — It’s Helping Us Teach Better — from rdene915.com by guest author Matthew Mawn

Turning Time Saved Into Better Learning
AI can save teachers time, but what can that time be used for (besides taking a breath)? For most of us, it means redirecting energy into the parts of teaching that made us want to pursue this profession in the first place: connecting with our students and helping them grow academically.

Differentiation
Every classroom has students with different readiness levels, language needs, and learning preferences. AI tools like Diffit or MagicSchool can instantly create multiple versions of a passage or assignment, differentiated by grade level, complexity, or language. This allows every student to engage with the same core concept, moving together as one cohesive class. Instead of spending an evening retyping and rephrasing, teachers can review and tweak AI drafts in minutes, ready for the next lesson.

Mass Intelligence — from oneusefulthing.org by Ethan Mollick
From GPT-5 to nano banana: everyone is getting access to powerful AI

When a billion people have access to advanced AI, we’ve entered what we might call the era of Mass Intelligence. Every institution we have — schools, hospitals, courts, companies, governments — was built for a world where intelligence was scarce and expensive. Now every profession, every institution, every community has to figure out how to thrive with Mass Intelligence. How do we harness a billion people using AI while managing the chaos that comes with it? How do we rebuild trust when anyone can fabricate anything? How do we preserve what’s valuable about human expertise while democratizing access to knowledge?

AI Is the Cognitive Layer. Schools Still Think It’s a Study Tool. — from stefanbauschard.substack.com by Stefan Bauschard

By the time today’s 9th graders and college freshman enter the workforce, the most disruptive waves of AGI and robotics may already be embedded into part society.

What replaces the old system will not simply be a more digital version of the same thing. Structurally, schools may move away from rigid age-groupings, fixed schedules, and subject silos. Instead, learning could become more fluid, personalized, and interdisciplinary—organized around problems, projects, and human development rather than discrete facts or standardized assessments.

AI tutors and mentors will allow for pacing that adapts to each student, freeing teachers to focus more on guidance, relationships, and high-level facilitation. Classrooms may feel less like miniature factories and more like collaborative studios, labs, or even homes—spaces for exploring meaning and building capacity, not just delivering content.
…
If students are no longer the default source of action, then we need to teach them to:

- Design agents,
- Collaborate with agents,
- Align agentic systems with human values,
- And most of all, retain moral and civic agency in a world where machines act on our behalf.

We are no longer educating students to be just doers.
We must now educate them to be judges, designers, and stewards of agency.

Meet Your New AI Tutor — from wondertools.substack.com by Jeremy Caplan
Try new learning modes in ChatGPT, Claude, and Gemini

AI assistants are now more than simple answer machines. ChatGPT’s new Study Mode, Claude’s Learning Mode, and Gemini’s Guided Learning represent a significant shift. Instead of just providing answers, these free tools act as adaptive, 24/7 personal tutors.

AI Tools for Instructional Design (September, 2025) — from drphilh.gumroad.com by Dr Philippa Hardman

That’s why, in preparation for my next bootcamp which kicks off September 8th 2025, I’ve just completed a full refresh of my list of the most powerful & popular AI tools for Instructional Designers, complete with tips on how to get the most from each tool.

The list has been created using my own experience + the experience of hundreds of Instructional Designers who I work with every week.

It contains the 50 most powerful AI tools for instructional design available right now, along with tips on how to optimise their benefits while mitigating their risks.

Addendums on 9/4/25:

AI Companies Roll Out Educational Tools — from insidehighered.com by Ray Schroeder
This fall, Google, Anthropic and OpenAI are rolling out powerful new AI tools for students and educators, each taking a different path to shape the future of learning.

Rethinking My List of Essential Job Skills in the Age of AI — from michellekassorla.substack.com by Michelle Kassorla

So here’s the new list of essential skills I think my students will need when they are employed to work with AI five years from now:

They can follow directions, analyze outcomes, and adapt to change when needed.
They can write or edit AI to capture a unique voice and appropriate tone in sync with an audience’s needs
They have a deep understanding of one or more content areas of a particular profession, business, or industry, so they can easily identify factual errors.
They have a strong commitment to exploration, a flexible mindset, and a broad understanding of AI literacy.
They are resilient and critical thinkers, ready to question results and demand better answers.
They are problem solvers.

And, of course, here is a new rubric built on those skills:

Anthropic Education Report: How educators use Claude — from anthropic.com

We find that:

Educators use AI in and out of the classroom
Educators’ uses range from developing course materials and writing grant proposals to academic advising and managing administrative tasks like admissions and financial planning.

Educators aren’t just using chatbots; they’re building their own custom tools with AI
Faculty are using Claude Artifacts to create interactive educational materials, such as chemistry simulations, automated grading rubrics, and data visualization dashboards.

Educators tend to automate the drudgery while staying in the loop for everything else
Tasks requiring significant context, creativity, or direct student interaction—like designing lessons, advising students, and writing grant proposals—are where educators are more likely to use AI as an enhancement. In contrast, routine administrative work such as financial management and record-keeping are more automation-heavy.

Some educators are automating grading; others are deeply opposed
In our Claude.ai data, faculty used AI for grading and evaluation less frequently than other uses, but when they did, 48.9% of the time they used it in an automation-heavy way (where the AI directly performs the task). That’s despite educator concerns about automating assessment tasks, as well as our surveyed faculty rating it as the area where they felt AI was least effective.

Now available: The 2025 Changing Landscape of Online Education (CHLOE) 10 Report

On 08/28/2025, in adjunct faculty, Artificial Intelligence/Agents/LLMs/and Related, business side of he, change, changing business models, collaboration, colleges, communications, communities of practice, community colleges, content development, aggregation, repositories, credentialing, culture, digital learning, education technology, face-to-face, faculty/staff, higher education, instructional design, IT in HE, law schools, leadership, learning, learning ecosystem, Learning Experience Design, learning preferences, learning spaces, liberal arts, new business models, online learning, online media, online tutoring, organizational change, policy, strategy, student-related, teaching & learning, teaching online, traditional / tradition, trends, United States, universities, vision/possibilities, by Daniel Christian

The 2025 Changing Landscape of Online Education (CHLOE) 10 Report — from qualitymatters.org; emphasis below from DSC

Notable findings from the 73-page report include:

Online Interest Surges Across Student Populations: …
Institutional Preparedness Falters Amid Rising Demand: Despite accelerating demand, institutional readiness has stagnated—or regressed—in key areas. …
The Online Education Marketplace Is Increasingly Competitive: …
Alternative Credentials Take Center Stage: …
AI Integration Lacks Strategic Coordination: …

Just 28% of faculty are considered fully prepared for online course design, and 45% for teaching. Alarmingly, only 28% of institutions report having fully developed academic continuity plans for future emergency pivots to online.

Also relevant, see:

Great Expectations, Fragile Foundations — from onedtech.philhillaa.com by Glenda Morgan
Lessons about growth from the CHLOE & BOnES reports

Cultural resistance remains strong. Many [Chief Online Learning Officers] COLOs say faculty and deans still believe in-person learning is “just better,” creating headwinds even for modest online growth. As one respondent at a four-year institution with a large online presence put it:

Supportive departments [that] see the value in online may have very different levels of responsiveness compared to academic departments [that] are begrudgingly online. There is definitely a growing belief that students “should” be on-ground and are only choosing online because it’s easy/ convenient. Never mind the very real and growing population of nontraditional learners who can only take online classes, and the very real and growing population of traditional-aged learners who prefer online classes; many faculty/deans take a paternalistic, “we know what’s best” approach.

…
Ultimately, what we need is not just more ambition but better ambition. Ambition rooted in a realistic understanding of institutional capacity, a shared strategic vision, investments in policy and infrastructure, and a culture that supports online learning as a core part of the academic mission, not an auxiliary one. It’s time we talked about what it really takes to grow online learning , and where ambition needs to be matched by structure.

From DSC:
Yup. Culture is at the breakfast table again…boy, those strategies taste good.

I’d like to take some of this report — like the graphic below — and share it with former faculty members and members of a couple of my past job families’ leadership. They strongly didn’t agree with us when we tried to advocate for the development of online-based learning/programs at our organizations…but we were right. We were right all along. And we were LEADING all along. No doubt about it — even if the leadership at the time said that we weren’t leading.

The cultures of those organizations hurt us at the time. But our cultivating work eventually led to the development of online programs — unfortunately, after our groups were disbanded, they had to outsource those programs to OPMs.

Arizona State University — with its dramatic growth in online-based enrollments.

“We’re witnessing the biggest shift in education since the textbook—and most institutions are still deciding whether to allow it.” [Kilgore]

On 08/26/2025, in 21st century, 24x7x365 access, adjunct faculty, Artificial Intelligence/Agents/LLMs/and Related, Asia, bots, business, Canada, career development, change, cloud-based computing / apps / other cloud-related, colleges, communities of practice, community colleges, computer science, content development, aggregation, repositories, corporate / business world, culture, curriculum, education technology, emerging technologies, expectations, experimentation, faculty/staff, future, future of higher education, game-changing environment, generational differences, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, IT in HE, law schools, learning, learning agents, learning ecosystem, Learning Experience Design, learning spaces, liberal arts, pedagogy, platforms, reinvent, skills, staying relevant, student-related, teaching & learning, trends, United States, universities, workplace, by Daniel Christian

The AI Education Revolution — from linkedin.com by Whitney Kilgore
We’re witnessing the biggest shift in education since the textbook—and most institutions are still deciding whether to allow it.

What’s In Your Statement? — from aiedusimplified.substack.com by Lance Eaton, Ph.D.
Friendly reminder that there’s a Syllabi AI Policy Repository

AI Policy Resources

AI Syllabi Policy Repository: 180+ policies
AI Institutional Policy Repository: 17 policies

Thomson Reuters CEO: Legal Profession Faces “Biggest Disruption in Its History”from AI — from lawnext.com by Bob Ambrogi

Thomson Reuters President and CEO Steve Hasker believes the legal profession is experiencing “the biggest disruption … in its history” due to generative and agentic artificial intelligence, fundamentally rewriting how legal work products are created for the first time in more than 300 years.

Speaking to legal technology reporters during ILTACON, the International Legal Technology Association’s annual conference, Hasker outlined his company’s ambitious goal to become “the most innovative company” in the legal tech sector while navigating what he described as unprecedented technological change affecting a profession that has remained largely unchanged since its origins in London tea houses centuries ago.

Legal tech hackathon challenges students to rethink access to justice — from the Centre for Innovation and Entrepreneurship, Auckland Law School
In a 24-hour sprint, student teams designed innovative tools to make legal and social support more accessible.

The winning team comprised of students of computer science, law, psychology and physics. They developed a privacy-first legal assistant powered by AI that helps people understand their legal rights without needing to navigate dense legal language.

Teaching How To ‘Think Like a Lawyer’ Revisited — from abovethelaw.com by Stephen Embry
GenAI gives the concept of training law students to think like a lawyer a whole new meaning.

Law Schools
These insights have particular urgency for legal education. Indeed, most of Cowen’s criticisms and suggested changes need to be front and center for law school leaders. It’s naïve to think that law student and lawyers aren’t going to use GenAI tools in virtually every aspect of their professional and personal lives. Rather than avoiding the subject or worse yet trying to stop use of these tools, law schools should make GenAI tools a fundamental part of research, writing and drafting training.

They need to focus not on memorization but on the critical thinking skills beginning lawyers used to get in the on-the-job training guild type system. As I discussed, that training came from repetitive and often tedious work that developed experienced lawyers who could recognize patterns and solutions based on the exposure to similar situations. But much of that repetitive and tedious work may go away in a GenAI world.

The Role of Adjunct Professors
But to do this, law schools need to better partner with actual practicing lawyers who can serve as adjunct professors. Law schools need to do away with the notion that adjuncts are second-class teachers.

It’s a New Dawn In Legal Tech: From Woodstock to ILTACON (And Beyond) — from lawnext.com by Bob Ambrogi

As someone who has covered legal tech for 30 years, I cannot remember there ever being a time such as this, when the energy and excitement are raging, driven by generative AI and a new era of innovation and new ideas of the possible.
…
But this year was different. Wandering the exhibit hall, getting product briefings from vendors, talking with attendees, it was impossible to ignore the fundamental shift happening in legal technology. Gen AI isn’t just creating new products – it is spawning entirely new categories of products that truly are reshaping how legal work gets done.

Agentic AI is the buzzword of 2025 and agentic systems were everywhere at ILTACON, promising to streamline workflows across all areas of legal practice. But, perhaps more importantly, these tools are also beginning to address the business side of running a law practice – from client intake and billing to marketing and practice management. The scope of transformation is now beginning to extend beyond the practice of law into the business of law.
…
Largely missing from this gathering were solo practitioners, small firm lawyers, legal aid organizations, and access-to-justice advocates – the very people who stand to benefit most from the democratizing potential of AI.
…
However, now more than ever, the innovations we are seeing in legal tech have the power to level the playing field, to give smaller practitioners access to tools and capabilities that were once prohibitively expensive. If these technologies remain priced for and marketed primarily to Big Law, we will have succeeded only in widening the justice gap rather than closing it.

How AI is Transforming Deposition Review: A LegalTech Q&A — from jdsupra.com

Thanks to breakthroughs in artificial intelligence – particularly in semantic search, multimodal models, and natural language processing – new legaltech solutions are emerging to streamline and accelerate deposition review. What once took hours or days of manual analysis now can be accomplished in minutes, with greater accuracy and efficiency than possible with manual review.

From Skepticism to Trust: A Playbook for AI Change Management in Law Firms — from jdsupra.com by Scott Cohen

Historically, lawyers have been slow adopters of emerging technologies, and with good reason. Legal work is high stakes, deeply rooted in precedent, and built on individual judgment. AI, especially the new generation of agentic AI (systems that not only generate output but initiate tasks, make decisions, and operate semi-autonomously), represents a fundamental shift in how legal work gets done. This shift naturally leads to caution as it challenges long-held assumptions about lawyer workflows and several aspects of their role in the legal process.

The path forward is not to push harder or faster, but smarter. Firms need to take a structured approach that builds trust through transparency, context, training, and measurement of success. This article provides a five-part playbook for law firm leaders navigating AI change management, especially in environments where skepticism is high and reputational risk is even higher.

ILTACON 2025: The vendor briefings – Agents, ecosystems and the next stage of maturity — from legaltechnology.com by Caroline Hill

This year’s ILTACON in Washington was heavy on AI, but the conversation with vendors has shifted. Legal IT Insider’s briefings weren’t about potential use cases or speculative roadmaps. Instead, they focused on how AI is now being embedded into the tools lawyers use every day — and, crucially, how those tools are starting to talk to each other.

Taken together, they point to an inflection point, where agentic workflows, data integration, and open ecosystems define the agenda. But it’s important amidst the latest buzzwords to remember that agents are only as good as the tools they have to work with, and AI only as good as its underlying data. Also, as we talk about autonomous AI, end users are still struggling with cloud implementations and infrastructure challenges, and need vendors to be business partners that help them to make progress at speed.

Harvey’s roadmap is all about expanding its surface area — connecting to systems like iManage, LexisNexis, and more recently publishing giant Wolters Kluwer — so that a lawyer can issue a single query and get synthesised, contextualised answers directly within their workflow. Weinberg said: “What we’re trying to do is get all of the surface area of all of the context that a lawyer needs to complete a task and we’re expanding the product surface so you can enter a search, search all resources, and apply that to the document automatically.”

The common thread: no one is talking about AI in isolation anymore. It’s about orchestration — pulling together multiple data sources into a workflow that actually reflects how lawyers practice.

5 Pitfalls Of Delaying Automation In High-Volume Litigation And Claims — from jdsupra.com

Why You Can’t Afford to Wait to Adopt AI Tools that have Plaintiffs Moving Faster than Ever
Just as photocopiers shifted law firm operations in the early 1970s and cloud computing transformed legal document management in the early 2000s, AI automation tools are altering the current legal landscape—enabling litigation teams to instantly structure unstructured data, zero in on key arguments in seconds, and save hundreds (if not thousands) of hours of manual work.

Your Firm’s AI Policy Probably Sucks: Why Law Firms Need Education, Not Rules — from jdsupra.com

The Floor, Not the Ceiling
Smart firms need to flip their entire approach. Instead of dictating which AI tools lawyers must use, leadership should set a floor for acceptable use and then get out of the way.

The floor is simple: no free versions for client work. Free tools are free because users are the product. Client data becomes training data. Confidentiality gets compromised. The firm loses any ability to audit or control how information flows. This isn’t about control; it’s about professional responsibility.

But setting the floor is only the first step. Firms must provide paid, enterprise versions of AI tools that lawyers actually want to use. Not some expensive legal tech platform that promises AI features but delivers complicated workflows. Real AI tools. The same ones lawyers are already using secretly, but with enterprise security, data protection, and proper access controls.

Education must be practical and continuous. Single training sessions don’t work. AI tools evolve weekly. New capabilities emerge constantly. Lawyers need ongoing support to experiment, learn, and share discoveries. This means regular workshops, internal forums for sharing prompts and techniques, and recognition for innovative uses.

The education investment pays off immediately. Lawyers who understand AI use it more effectively. They catch its mistakes. They know when to verify outputs. They develop specialized prompts for legal work. They become force multipliers, not just for themselves but for their entire teams.

Learning Ecosystems

“A tight housing market and a fragile job market mean those working in higher ed have fewer options than ever.” [Murphy]

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