U.S. Law Schools Make AI Training Mandatory as Technology Becomes Core Legal Skill — from jdjournal.com by Fatima E
A growing number of U.S. law schools are now requiring students to train in artificial intelligence, marking a shift from optional electives to essential curriculum components. What was once treated as a “nice-to-have” skill is fast becoming integral as the legal profession adapts to the realities of AI tools.
From Experimentation to Obligation
Until recently, most law schools relegated AI instruction to upper-level electives or let individual professors decide whether to incorporate generative AI into their teaching. Now, however, at least eight law schools require incoming students—especially in their first year—to undergo training in AI, either during orientation, in legal research and writing classes, or via mandatory standalone courses.
Some of the institutions pioneering the shift include Fordham University, Arizona State University, Stetson University, Suffolk University, Washington University in St. Louis, Case Western, and the University of San Francisco.
Beyond the Classroom & LMS: How AI Coaching is Transforming Corporate Learning — from by Dr Philippa Hardman
What a new HBR study tells about the changing nature of workplace L&D
There’s a vision that’s been teased Learning & Development for decades: a vision of closing the gap between learning and doing—of moving beyond stopping work to take a course, and instead bringing support directly into the workflow. This concept of “learning in the flow of work” has been imagined, explored, discussed for decades —but never realised. Until now…?
This week, an article published Harvard Business Review provided some some compelling evidence that a long-awaited shift from “courses to coaches” might not just be possible, but also powerful.
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The two settings were a) traditional in-classroom workshops, led by an expert facilitator and b) AI-coaching, delivered in the flow of work. The results were compelling….
TLDR: The evidence suggests that “learning in the flow of work” is not only feasible as a result of gen AI—it also show potential to be more scalable, more equitable and more efficient than traditional classroom/LMS-centred models.
The 10 Most Popular AI Chatbots For Educators — from techlearning.com by Erik Ofgang
Educators don’t need to use each of these chatbots, but it pays to be generally aware of the most popular AI tools
I’ve spent time testing many of these AI chatbots for potential uses and abuses in my own classes, so here’s a quick look at each of the top 10 most popular AI chatbots, and what educators should know about each. If you’re looking for more detail on a specific chatbot, click the link, as either I or other Tech & Learning writers have done deeper dives on all these tools.
…which links to:
Beyond Tool or Threat: GenAI and the Challenge It Poses to Higher Education — from er.educause.edu by Adam Maksl, Anne Leftwich, Justin Hodgson and Kevin Jones
Generative artificial intelligence isn’t just a new tool—it’s a catalyst forcing the higher education profession to reimagine its purpose, values, and future.
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As experts in educational technology, digital literacy, and organizational change, we argue that higher education must seize this moment to rethink not just how we use AI, but how we structure and deliver learning altogether.
At This Rural Microschool, Students Will Study With AI and Run an Airbnb — from edsurge.com by Daniel Mollenkamp
Over the past decade, microschools — experimental small schools that often have mixed-age classrooms — have expanded.
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Some superintendents have touted the promise of microschools as a means for public schools to better serve their communities’ needs while still keeping children enrolled in the district. But under a federal administration that’s trying to dismantle public education and boost homeschool options, others have critiqued poor oversight and a lack of information for assessing these models.
Microschools offer a potential avenue to bring innovative, modern experiences to rural areas, argues Keith Parker, superintendent of Elizabeth City-Pasquotank Public Schools.
Are We Ready for the AI University? An AI in Higher Education Webinar with Dr. Scott Latham
Imagining Teaching with AI Agents… — from michellekassorla.substack.com by Michelle Kassorla
Teaching with AI is only one step toward educational change, what’s next?
More than two years ago I started teaching with AI in my classes. At first I taught against AI, then I taught with AI, and now I am moving into unknown territory: agents. I played with Manus and n8n and some other agents, but I really never got excited about them. They seemed more trouble than they were worth. It seemed they were no more than an AI taskbot overseeing some other AI bots, and that they weren’t truly collaborating. Now, I’m looking at Perplexity’s Comet browser and their AI agent and I’m starting to get ideas for what the future of education might hold.
I have written several times about the dangers of AI agents and how they fundamentally challenge our systems, especially online education. I know there is no way that we can effectively stop them–maybe slow them a little, but definitely not stop them. I am already seeing calls to block and ban agents–just like I saw (and still see) calls to block and ban AI–but the truth is they are the future of work and, therefore, the future of education.
So, yes! This is my next challenge: teaching with AI agents. I want to explore this idea, and as I started thinking about it, I got more and more excited. But let me back up a bit. What is an agent and how is it different than Generative AI or a bot?
Agentic AI and the New Era of Corporate Learning for 2026 — from hrmorning.com by Carol Warner
That gap creates compliance risk and wasted investment. It leaves HR leaders with a critical question: How do you measure and validate real learning when AI is doing the work for employees?
Designing Training That AI Can’t Fake
Employees often find static slide decks and multiple-choice quizzes tedious, while AI can breeze through them. If employees would rather let AI take training for them, it’s a red flag about the content itself.
One of the biggest risks with agentic AI is disengagement. When AI can complete a task for employees, their incentive to engage disappears unless they understand why the skill matters, Rashid explains. Personalization and context are critical. Training should clearly connect to what employees value most – career mobility, advancement, and staying relevant in a fast-changing market.
Nearly half of executives believe today’s skills will expire within two years, making continuous learning essential for job security and growth. To make training engaging, Rashid recommends:
- Delivering content in formats employees already consume – short videos, mobile-first modules, interactive simulations, or micro-podcasts that fit naturally into workflows. For frontline workers, this might mean replacing traditional desktop training with mobile content that integrates into their workday.
- Aligning learning with tangible outcomes, like career opportunities or new responsibilities.
- Layering in recognition, such as digital badges, leaderboards, or team shout-outs, to reinforce motivation and progress
Microsoft 365 Copilot AI agents reach a new milestone — is teamwork about to change? — from windowscentral.comby Adam Hales
Microsoft expands Copilot with collaborative agents in Teams, SharePoint and more to boost productivity and reshape teamwork.
Microsoft is pitching a recent shift of AI agents in Microsoft Teams as more than just smarter assistance. Instead, these agents are built to behave like human teammates inside familiar apps such as Teams, SharePoint, and Viva Engage. They can set up meeting agendas, keep files in order, and even step in to guide community discussions when things drift off track.
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Unlike tools such as ChatGPT or Claude, which mostly wait for prompts, Microsoft’s agents are designed to take initiative. They can chase up unfinished work, highlight items that still need decisions, and keep projects moving forward. By drawing on Microsoft Graph, they also bring in the right files, past decisions, and context to make their suggestions more useful.
Chris Dede’s comments on LinkedIn re: Aibrary
As an advisor to Aibrary, I am impressed with their educational philosophy, which is based both on theory and on empirical research findings. Aibrary is an innovative approach to self-directed learning that complements academic resources. Expanding our historic conceptions of books, libraries, and lifelong learning to new models enabled by emerging technologies is central to empowering all of us to shape our future.
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Also see:
Why AI literacy must come before policy — from timeshighereducation.com by Kathryn MacCallum and David Parsons
When developing rules and guidelines around the uses of artificial intelligence, the first question to ask is whether the university policymakers and staff responsible for implementing them truly understand how learners can meet the expectations they set
Literacy first, guidelines second, policy third
For students to respond appropriately to policies, they need to be given supportive guidelines that enact these policies. Further, to apply these guidelines, they need a level of AI literacy that gives them the knowledge, skills and understanding required to support responsible use of AI. Therefore, if we want AI to enhance education rather than undermine it, we must build literacy first, then create supportive guidelines. Good policy can then follow.
AI training becomes mandatory at more US law schools — from reuters.com by Karen Sloan and Sara Merken
Sept 22 (Reuters) – At orientation last month, 375 new Fordham Law students were handed two summaries of rapper Drake’s defamation lawsuit against his rival Kendrick Lamar’s record label — one written by a law professor, the other by ChatGPT.
The students guessed which was which, then dissected the artificial intelligence chatbot’s version for accuracy and nuance, finding that it included some irrelevant facts.
The exercise was part of the first-ever AI session for incoming students at the Manhattan law school, one of at least eight law schools now incorporating AI training for first-year students in orientation, legal research and writing courses, or through mandatory standalone classes.
Workday Acquires Sana To Transform Its Learning Platform And Much More— from joshbersin.com by Josh Bersin
Well now, as the corporate learning market shifts to AI, (read the details in our study “The Revolution in Corporate Learning” ), Workday can jump ahead. This is because the $400 billion corporate training market is moving quickly to an AI-Native dynamic content approach (witness OpenAI’s launch of in-line learning in its chatbot). We’re just finishing a year-long study of this space and our detailed report and maturity model will be out in Q4.
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With Sana, and a few other AI-native vendors (Uplimit, Arist, Disperz, Docebo), companies can upload audios, videos, documents, and even interviews with experts and the system build learning programs in minutes. We use Sana for Galileo Learn (our AI-powered learning academy for Leadership and HR), and we now have 750+ courses and can build new programs in days instead of months.
And there’s more; this type of system gives every employee a personalized, chat-based experience to learn.
ChatGPT: the world’s most influential teacher — from drphilippahardman.substack.com by Dr. Philippa Hardman; emphasis DSC
New research shows that millions of us are “learning with AI” every week: what does this mean for how (and how well) humans learn?
This week, an important piece of research landed that confirms the gravity of AI’s role in the learning process. The TLDR is that learning is now a mainstream use case for ChatGPT; around 10.2% of all ChatGPT messages (that’s ~2BN messages sent by over 7 million users per week) are requests for help with learning.
The research shows that about 10.2% of all messages are tutoring/teaching, and within the “Practical Guidance” category, tutoring is 36%. “Asking” interactions are growing faster than “Doing” and are rated higher quality by users. Younger people contribute a huge share of messages, and growth is fastest in low- and middle-income countries (How People Use ChatGPT, 2025).
If AI is already acting as a global tutor, the question isn’t “will people learn with AI?”—they already are. The real question we need to ask is: what does great learning actually look like, and how should AI evolve to support it? That’s where decades of learning science help us separate “feels like learning” from “actually gaining new knowledge and skills”.
Let’s dive in.
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
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Update learner profiles to emphasize curiosity, curation, and connectivity, ensuring students develop irreplaceable human skills.
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Integrate real-world learning experiences and mastery-based assessments to foster agency, purpose, and motivation in students.
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.
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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.
From Content To Capability: How AI Agents Are Redefining Workplace Learning — from forbes.com by Nelson Sivalingam
Real, capability-building learning requires three key elements: content, context and conversation.
The Rise Of AI Agents: Teaching At Scale
The generative AI revolution is often framed in terms of efficiency: faster content creation, automated processes and streamlined workflows. But in the world of L&D, its most transformative potential lies elsewhere: the ability to scale great teaching.
AI gives us the means to replicate the role of an effective teacher across an entire organization. Specifically, AI agents—purpose-built systems that understand, adapt and interact in meaningful, context-aware ways—can make this possible. These tools understand a learner’s role, skill level and goals, then tailor guidance to their specific challenges and adapt dynamically over time. They also reinforce learning continuously, nudging progress and supporting application in the flow of work.
More than simply sharing knowledge, an AI agent can help learners apply it and improve with every interaction. For example, a sales manager can use a learning agent to simulate tough customer scenarios, receive instant feedback based on company best practices and reinforce key techniques. A new hire in the product department could get guidance on the features and on how to communicate value clearly in a roadmap meeting.
In short, AI agents bring together the three essential elements of capability building, not in a one-size-fits-all curriculum but on demand and personalized for every learner. While, obviously, this technology shouldn’t replace human expertise, it can be an effective tool for removing bottlenecks and unlocking effective learning at scale.
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.
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If students are no longer the default source of action, then we need to teach them to:
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- 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:
The future of L&D is here, and it’s powered by AI. — from linkedin.com by Josh Cavalier
4 Ways I Use AI to Think Better — from wondertools.substack.com by Jeremy Caplan
How AI helps me learn, decide, and create
Learn something new.
Map out a personalized curriculum
Try this: Give an AI assistant context about what you want to learn, why, and how.
- Detail your rationale and motivation, which may impact your approach.
- Note your current knowledge or skill level, ideally with examples.
Summarize your learning preferences
- Note whether you prefer to read, listen to, or watch learning materials.
- Mention if you like quizzes, drills, or exercises you can do while commuting or during a break at work.
- If you appreciate learning games, task your AI assistant with generating one for you, using its coding capabilities detailed below.
- Ask for specific book, textbook, article, or learning path recommendations using the Web search or Deep Research capabilities of Perplexity, ChatGPT, Gemini or Claude. They can also summarize research literature about effective learning tactics.
- If you need a human learning partner, ask for guidance on finding one or language you can use in reaching out.
The Ends of Tests: Possibilities for Transformative Assessment and Learning with Generative AI
GPT-5 for Instructional Designers — from drphilippahardman.substack.com by Dr Philippa Hardman
10 Hacks to Work Smarter & Safer with OpenAI’s Latest Model
The TLDR is that as Instructional Designers, we can’t afford to miss some of the very real benefits of GPT-5’s potential, but we also can’t ensure our professional standards or learner outcomes if we blindly accept its outputs without due testing and validation.
For this reason, I decided to synthesise the latest GPT-5 research—from OpenAI’s technical documentation to independent security audits to real-world user testing—into 10 essential reality checks for using GPT-5 as an Instructional Designer.
These aren’t theoretical exercises; they’re practical tests designed to help you safely unlock GPT-5’s benefits while identifying and mitigating its most well-documented limitations.
Grammarly launches new specialist AI agents providing personalized assistance for students — from edtechinnovationhub.com by Rachel Lawler
Grammarly, an AI communication tool, has announced the launch of eight new specialized AI agents. The new assistants can support specific writing challenges such as finding credible sources and checking originality.
Students will now be offered “responsible AI support” through Grammarly, with the eight new agents:
- Reader Reactions agent …
- AI Grader agent …
- Citation Finder agent …
- Expert Review agent …
- Proofreader agent …
- AI Detector agent …
- Plagiarism Checker agent …
- Paraphraser agent …
Why Perplexity AI Is My Go-To Research Tool as a Higher Education CIO — from mikekentz.substack.com; a guest post from Michael Lyons, CIO at MassBay Community College
While I regularly use tools like ChatGPT, Grammarly, Microsoft Copilot, and even YouTube Premium (I would cancel Netflix before this), Perplexity has earned a top spot in my toolkit. It blends AI and real-time web search into one seamless, research-driven platform that saves time and improves the quality of information I rely on every day.
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.
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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.
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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.
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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.
Back to School in the AI Era: Why Students Are Rewriting Your Lesson Plan — from linkedin.com by Hailey Wilson
As a new academic year begins, many instructors, trainers, and program leaders are bracing for familiar challenges—keeping learners engaged, making complex material accessible, and preparing students for real-world application.
But there’s a quiet shift happening in classrooms and online courses everywhere.
This fall, it’s not the syllabus that’s guiding the learning experience—it’s the conversation between the learner and an AI tool.
From bootcamp to bust: How AI is upending the software development industry — from reuters.com by Anna Tong; via Paul Fain
Coding bootcamps have been a mainstay in Silicon Valley for more than a decade. Now, as AI eliminates the kind of entry-level roles for which they trained people, they’re disappearing.
Coding bootcamps have been a Silicon Valley mainstay for over a decade, offering an important pathway for non-traditional candidates to get six-figure engineering jobs. But coding bootcamp operators, students and investors tell Reuters that this path is rapidly disappearing, thanks in large part to AI.
“Coding bootcamps were already on their way out, but AI has been the nail in the coffin,” said Allison Baum Gates, a general partner at venture capital fund SemperVirens, who was an early employee at bootcamp pioneer General Assembly.
Gates said bootcamps were already in decline due to market saturation, evolving employer demand and market forces like growth in international hiring.
Bringing the best of AI to college students for free — from blog.google by Sundar Pichai
Millions of college students around the world are getting ready to start classes. To help make the school year even better, we’re making our most advanced AI tools available to them for free, including our new Guided Learning mode. We’re also providing $1 billion to support AI education and job training programs and research in the U.S. This includes making our AI and career training free for every college student in America through our AI for Education Accelerator — over 100 colleges and universities have already signed up.
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Guided Learning: from answers to understanding
AI can broaden knowledge and expand access to it in powerful ways, helping anyone, anywhere learn anything in the way that works best for them. It’s not about just getting an answer, but deepening understanding and building critical thinking skills along the way. That opportunity is why we built Guided Learning, a new mode in Gemini that acts as a learning companion guiding you with questions and step-by-step support instead of just giving you the answer. We worked closely with students, educators, researchers and learning experts to make sure it’s helpful for understanding new concepts and is backed by learning science.
BREAKING: Google introduces Guided Learning — from aieducation.substack.com by Claire Zau
Some thoughts on what could make Google’s AI tutor stand out
Another major AI lab just launched “education mode.”
Google introduced Guided Learning in Gemini, transforming it into a personalized learning companion designed to help you move from quick answers to real understanding.
Instead of immediately spitting out solutions, it:
- Asks probing, open-ended questions
- Walks learners through step-by-step reasoning
- Adapts explanations to the learner’s level
- Uses visuals, videos, diagrams, and quizzes to reinforce concepts
This Socratic style tutor rollout follows closely behind similar announcements like OpenAI’s Study Mode (last week) and Anthropic’s Claude for Education (April 2025).
How Sci-Fi Taught Me to Embrace AI in My Classroom — from edsurge.com by Dan Clark
I’m not too naive to understand that, no matter how we present it, some students will always be tempted by “the dark side” of AI. What I also believe is that the future of AI in education is not decided. It will be decided by how we, as educators, embrace or demonize it in our classrooms.
My argument is that setting guidelines and talking to our students honestly about the pitfalls and amazing benefits that AI offers us as researchers and learners will define it for the coming generations.
Can AI be the next calculator? Something that, yes, changes the way we teach and learn, but not necessarily for the worse? If we want it to be, yes.
How it is used, and more importantly, how AI is perceived by our students, can be influenced by educators. We have to first learn how AI can be used as a force for good. If we continue to let the dominant voice be that AI is the Terminator of education and critical thinking, then that will be the fate we have made for ourselves.
AI Tools for Strategy and Research – GT #32 — from goodtools.substack.com by Robin Good
Getting expert advice, how to do deep research with AI, prompt strategy, comparing different AIs side-by-side, creating mini-apps and an AI Agent that can critically analyze any social media channel
In this issue, discover AI tools for:
- Getting Expert Advice
- Doing Deep Research with AI
- Improving Your AI Prompt Strategy
- Comparing Results from Different AIs
- Creating an AI Agent for Social Media Analysis
- Summarizing YouTube Videos
- Creating Mini-Apps with AI
- Tasting an Award-Winning AI Short Film
GPT-Building, Agentic Workflow Design & Intelligent Content Curation — from drphilippahardman.substack.com by Dr. Philippa Hardman
What 3 recent job ads reveal about the changing nature of Instructional Design
In this week’s blog post, I’ll share my take on how the instructional design role is evolving and discuss what this means for our day-to-day work and the key skills it requires.
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With this in mind, I’ve been keeping a close eye on open instructional design roles and, in the last 3 months, have noticed the emergence of a new flavour of instructional designer: the so-called “Generative AI Instructional Designer.”
Let’s deep dive into three explicitly AI-focused instructional design positions that have popped up in the last quarter. Each one illuminates a different aspect of how the role is changing—and together, they paint a picture of where our profession is likely heading.
Designers who evolve into prompt engineers, agent builders, and strategic AI advisors will capture the new premium. Those who cling to traditional tool-centric roles may find themselves increasingly sidelined—or automated out of relevance.
Google to Spend $1B on AI Training in Higher Ed — from insidehighered.com by Katherine Knott
Google’s parent company announced Wednesday (8/6/25) that it’s planning to spend $1 billion over the next three years to help colleges teach and train students about artificial intelligence.
Google is joining other AI companies, including OpenAI and Anthropic, in investing in AI training in higher education. All three companies have rolled out new tools aimed at supporting “deeper learning” among students and made their AI platforms available to certain students for free.
5 Predictions for How AI Will Impact Community Colleges — from pistis4edu.substack.com by Feng Hou
Based on current technology capabilities, adoption patterns, and the mission of community colleges, here are five well-supported predictions for AI’s impact in the coming years.
- Universal AI Tutor Access
- AI as Active Teacher
- Personalized Learning Pathways
- Interactive Multimodal Learning
- Value-Centric Education in an AI-Abundant World
One-size-fits-all learning is about to become completely obsolete. — from linkedin.com by Allie Miller
AI in the University: From Generative Assistant to Autonomous Agent This Fall — from insidehighered.com by
This fall we are moving into the agentic generation of artificial intelligence.
“Where generative AI creates, agentic AI acts.” That’s how my trusted assistant, Gemini 2.5 Pro deep research, describes the difference.
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Agents, unlike generative tools, create and perform multistep goals with minimal human supervision. The essential difference is found in its proactive nature. Rather than waiting for a specific, step-by-step command, agentic systems take a high-level objective and independently create and execute a plan to achieve that goal. This triggers a continuous, iterative workflow that is much like a cognitive loop. The typical agentic process involves six key steps, as described by Nvidia:
AI in Education Podcast — from aipodcast.education by Dan Bowen and Ray Fleming
The State of AI in Education 2025 Key Findings from a National Survey — from Carnegie Learning
Our 2025 national survey of over 650 respondents across 49 states and Puerto Rico reveals both encouraging trends and important challenges. While AI adoption and optimism are growing, concerns about cheating, privacy, and the need for training persist.
Despite these challenges, I’m inspired by the resilience and adaptability of educators. You are the true game-changers in your students’ growth, and we’re honored to support this vital work.
This report reflects both where we are today and where we’re headed with AI. More importantly, it reflects your experiences, insights, and leadership in shaping the future of education.
Instructure and OpenAI Announce Global Partnership to Embed AI Learning Experiences within Canvas — from instructure.com
This groundbreaking collaboration represents a transformative step forward in education technology and will begin with, but is not limited to, an effort between Instructure and OpenAI to enhance the Canvas experience by embedding OpenAI’s next-generation AI technology into the platform.
IgniteAI announced earlier today, establishes Instructure’s future-ready, open ecosystem with agentic support as the AI landscape continues to evolve. This partnership with OpenAI exemplifies this bold vision for AI in education. Instructure’s strategic approach to AI emphasizes the enhancement of connections within an educational ecosystem comprising over 1,100 edtech partners and leading LLM providers.
“We’re committed to delivering next-generation LMS technologies designed with an open ecosystem that empowers educators and learners to adapt and thrive in a rapidly changing world,” said Steve Daly, CEO of Instructure. “This collaboration with OpenAI showcases our ambitious vision: creating a future-ready ecosystem that fosters meaningful learning and achievement at every stage of education. This is a significant step forward for the education community as we continuously amplify the learning experience and improve student outcomes.”
Faculty Latest Targets of Big Tech’s AI-ification of Higher Ed — from insidehighered.com by Kathryn Palmer
A new partnership between OpenAI and Instructure will embed generative AI in Canvas. It may make grading easier, but faculty are skeptical it will enhance teaching and learning.
The two companies, which have not disclosed the value of the deal, are also working together to embed large language models into Canvas through a feature called IgniteAI. It will work with an institution’s existing enterprise subscription to LLMs such as Anthropic’s Claude or OpenAI’s ChatGPT, allowing instructors to create custom LLM-enabled assignments. They’ll be able to tell the model how to interact with students—and even evaluate those interactions—and what it should look for to assess student learning. According to Instructure, any student information submitted through Canvas will remain private and won’t be shared with OpenAI.
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Faculty Unsurprised, Skeptical
Few faculty were surprised by the Canvas-OpenAI partnership announcement, though many are reserving judgment until they see how the first year of using it works in practice.











