intelligent systems

2025: The Year the Frontier Firm Is Born — from Microsoft

We are entering a new reality—one in which AI can reason and solve problems in remarkable ways. This intelligence on tap will rewrite the rules of business and transform knowledge work as we know it. Organizations today must navigate the challenge of preparing for an AI-enhanced future, where AI agents will gain increasing levels of capability over time that humans will need to harness as they redesign their business. Human ambition, creativity, and ingenuity will continue to create new economic value and opportunity as we redefine work and workflows.

As a result, a new organizational blueprint is emerging, one that blends machine intelligence with human judgment, building systems that are AI-operated but human-led. Like the Industrial Revolution and the internet era, this transformation will take decades to reach its full promise and involve broad technological, societal, and economic change.

To help leaders understand how knowledge work will evolve, Microsoft analyzed survey data from 31,000 workers across 31 countries, LinkedIn labor market trends, and trillions of Microsoft 365 productivity signals. We also spoke with AI-native startups, academics, economists, scientists, and thought leaders to explore what work could become. The data and insights point to the emergence of an entirely new organization, a Frontier Firm that looks markedly different from those we know today. Structured around on-demand intelligence and powered by “hybrid” teams of humans + agents, these companies scale rapidly, operate with agility, and generate value faster.

Frontier Firms are already taking shape, and within the next 2–5 years we expect that every organization will be on their journey to becoming one. 82% of leaders say this is a pivotal year to rethink key aspects of strategy and operations, and 81% say they expect agents to be moderately or extensively integrated into their company’s AI strategy in the next 12–18 months. Adoption is accelerating: 24% of leaders say their companies have already deployed AI organization-wide, while just 12% remain in pilot mode.

The time to act is now. The question for every leader and employee is: how will you adapt?

On a somewhat related note, also see:

Exclusive: Anthropic warns fully AI employees are a year away — from axios.com by Sam Sabin

Anthropic expects AI-powered virtual employees to begin roaming corporate networks in the next year, the company’s top security leader told Axios in an interview this week.

Why it matters: Managing those AI identities will require companies to reassess their cybersecurity strategies or risk exposing their networks to major security breaches.

The big picture: Virtual employees could be the next AI innovation hotbed, Jason Clinton, the company’s chief information security officer, told Axios.

“AI agents arrive in US classrooms” [Rajkumar] + other items re: AI in our learning ecosystems

On 04/25/2025, in Artificial Intelligence/Agents/LLMs/and Related, colleges, community colleges, content development, aggregation, repositories, creativity, education, education technology, emerging technologies, experimentation, faculty/staff, game-changing environment, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, liberal arts, personalized/customized learning, podcasting, research, teachers, teaching & learning, trends, UK, United States, universities, vendors, by Daniel Christian

AI agents arrive in US classrooms — from zdnet.com by Radhika Rajkumar
Kira AI’s personalized learning platform is currently being implemented in Tennessee schools. How will it change education?

AI for education is a new but rapidly expanding field. Can it support student outcomes and help teachers avoid burnout?

On Wednesday, AI education company Kira launched a “fully AI-native learning platform” for K-12 education, complete with agents to assist teachers with repetitive tasks. The platform hosts assignments, analyzes progress data, offers administrative assistance, helps build lesson plans and quizzes, and more.

“Unlike traditional tools that merely layer AI onto existing platforms, Kira integrates artificial intelligence directly into every educational workflow — from lesson planning and instruction to grading, intervention, and reporting,” the release explains. “This enables schools to improve student outcomes, streamline operations, and provide personalized support at scale.”

Also relevant/see:

Coursera Founder Andrew Ng’s New Venture Brings A.I. to K–12 Classrooms — from observer.com by Victor Dey
Andrew Ng’s Kira Learning uses A.I. agents to transform K–12 education with tools for teachers, students and administrators.

“Teachers today are overloaded with repetitive tasks. A.I. agents can change that, and free up their time to give more personalized help to students,” Ng said in a statement.

Kira was co-founded by Andrea Pasinetti and Jagriti Agrawal, both longtime collaborators of Ng. The platform embeds A.I. directly into lesson planning, instruction, grading and reporting. Teachers can instantly generate standards-aligned lesson plans, monitor student progress in real time and receive automated intervention strategies when a student falls behind.

Students, in turn, receive on-demand tutoring tailored to their learning styles. A.I. agents adapt to each student’s pace and mastery level, while grading is automated with instant feedback—giving educators time to focus on teaching.

‘Using GenAI is easier than asking my supervisor for support’ — from timeshighereducation.com
Doctoral researchers are turning to generative AI to assist in their research. How are they using it, and how can supervisors and candidates have frank discussions about using it responsibly?

Generative AI is increasingly the proverbial elephant in the supervisory room. As supervisors, you may be concerned about whether your doctoral researchers are using GenAI. It can be a tricky topic to broach, especially when you may not feel confident in understanding the technology yourself.

While the potential impact of GenAI use among undergraduate and postgraduate taught students, especially, is well discussed (and it is increasingly accepted that students and staff need to become “AI literate”), doctoral researchers often slip through the cracks in institutional guidance and policymaking.

AI as a Thought Partner in Higher Education — from er.educause.edu by Brian Basgen

When used thoughtfully and transparently, generative artificial intelligence can augment creativity and challenge assumptions, making it an excellent tool for exploring and developing ideas.
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The glaring contrast between the perceived ubiquity of GenAI and its actual use also reveals fundamental challenges associated with the practical application of these tools. This article explores two key questions about GenAI to address common misconceptions and encourage broader adoption and more effective use of these tools in higher education.

AI for Automation or Augmentation of L&D? — from drphilippahardman.substack.com by Dr. Philippa Hardman
An audio summary of my Learning Technologies talk

Like many of you, I spent the first part of this week at Learning Technologies in London, where I was lucky enough to present a session on the current state of AI and L&D.

In this week’s blog post, I summarise what I covered and share an audio summary of my paper for you to check out.

Bridging the AI Trust Gap — from chronicle.com by Ian Wilhelm, Derek Bruff, Gemma Garcia, and Lee Rainie

In a 2024 Chronicle survey, 86 percent of administrators agreed with the statement: “Generative artificial intelligence tools offer an opportunity for higher education to improve how it educates, operates, and conducts research.” In contrast, just 55 percent of faculty agreed, showing the stark divisions between faculty and administrative perspectives on adopting AI.

Among many faculty members, a prevalent distrust of AI persists — and for valid reasons. How will it impact in-class instruction? What does the popularity of generative AI tools portend for the development of critical thinking skills for Gen-Z students? How can institutions, at the administrative level, develop policies to safeguard against students using these technologies as tools for cheating?

Given this increasing ‘trust gap,’ how can faculty and administrators work together to preserve academic integrity as AI seeps into all areas of academia, from research to the classroom?

Join us for “Bridging the AI Trust Gap,” an extended, 75-minute Virtual Forum exploring the trust gap on campus about AI, the contours of the differences, and what should be done about it.

“Age appropriate” AI literacy, the future of AI in education + other items re: AI in our LE’s

On 04/17/2025, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, bots, career development, change, cloud-based computing / apps / other cloud-related, colleges, communications, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, design, digital learning, education, 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, law schools, learning, learning ecosystem, Learning Experience Design, learning theories, workplace, by Daniel Christian

What does ‘age appropriate’ AI literacy look like in higher education? — from timeshighereducation.com by Fun Siong Lim
As AI literacy becomes an essential work skill, universities need to move beyond developing these competencies at ‘primary school’ level in their students. Here, Fun Siong Lim reflects on frameworks to support higher-order AI literacies

Like platforms developed at other universities, Project NALA offers a front-end interface (known as the builder) for faculty to create their own learning assistant. An idea we have is to open the builder up to students to allow them to create their own GenAI assistant as part of our AI literacy curriculum. As they design, configure and test their own assistant, they will learn firsthand how generative AI works. They get to test performance-enhancement approaches beyond prompt engineering, such as grounding the learning assistant with curated materials (retrieval-augmented generation) and advanced ideas such as incorporating knowledge graphs.

They should have the opportunity to analyse, evaluate and create responsible AI solutions. Offering students the opportunity to build their own AI assistants could be a way forward to develop these much-needed skills.

How to Use ChatGPT 4o’s Update to Turn Key Insights Into Clear Infographics (Prompts Included) — from evakeiffenheim.substack.com by Eva Keiffenheim
This 3-step workflow helps you break down books, reports, or slide-decks into professional visuals that accelerate understanding.

This article shows you how to find core ideas, prompt GPT-4o3 for a design brief, and generate clean, professional images that stick. These aren’t vague “creative visuals”—they’re structured for learning, memory, and action.

If you’re a lifelong learner, educator, creator, or just someone who wants to work smarter, this process is for you.

You’ll spend less time re-reading and more time understanding. And maybe—just maybe—you’ll build ideas that not only click in your brain, but also stick in someone else’s.

SchoolAI Secures $25 Million to Help Teachers and Schools Reach Every Student — from globenewswire.com
The Classroom Experience platform gives every teacher and student their own AI tools for personalized learning

SchoolAI’s Classroom Experience platform combines AI assistants for teachers that help with classroom preparation and other administrative work, and Spaces–personalized AI tutors, games, and lessons that can adapt to each student’s unique learning style and interests. Together, these tools give teachers actionable insights into how students are doing, and how the teacher can deliver targeted support when it matters most.

“Teachers and schools are navigating hard challenges with shrinking budgets, teacher shortages, growing class sizes, and ongoing recovery from pandemic-related learning gaps,” said Caleb Hicks, founder and CEO of SchoolAI. “It’s harder than ever to understand how every student is really doing. Teachers deserve powerful tools to help extend their impact, not add to their workload. This funding helps us double down on connecting the dots for teachers and students, and later this year, bringing school administrators and parents at home onto the platform as well.”

AI in Education, Part 3: Looking Ahead – The Future of AI in Learning — from rdene915.com by Dr. Rachelle Dené Poth

In the first and second parts of my AI series, I focused on where we see AI in classrooms. Benefits range from personalized learning and accessibility tools to AI-driven grading and support of a teaching assistant. In Part 2, I chose to focus on some of the important considerations related to ethics that must be part of the conversation. Schools need to focus on data privacy, bias, overreliance, and the equity divide. I wanted to focus on the future for this last part in the current AI series. Where do we go from here?

Anthropic Education Report: How University Students Use Claude — from anthropic.com

The key findings from our Education Report are:

STEM students are early adopters of AI tools like Claude, with Computer Science students particularly overrepresented (accounting for 36.8% of students’ conversations while comprising only 5.4% of U.S. degrees). In contrast, Business, Health, and Humanities students show lower adoption rates relative to their enrollment numbers.
We identified four patterns by which students interact with AI, each of which were present in our data at approximately equal rates (each 23-29% of conversations): Direct Problem Solving, Direct Output Creation, Collaborative Problem Solving, and Collaborative Output Creation.
Students primarily use AI systems for creating (using information to learn something new) and analyzing (taking apart the known and identifying relationships), such as creating coding projects or analyzing law concepts. This aligns with higher-order cognitive functions on Bloom’s Taxonomy. This raises questions about ensuring students don’t offload critical cognitive tasks to AI systems.

From the Kuali Days 2025 Conference: A CEO’s View of Planning for AI — from campustechnology.com by Mary Grush
A Conversation with Joel Dehlin

How can a company serving higher education navigate the changes AI brings to the ed tech marketplace? What will customers expect in this dynamic? Here, CT talks with Kuali CEO Joel Dehlin, who shared his company’s AI strategies in a featured plenary session, “Sneak Peek of AI in Kuali Build,” at Kuali Days 2025 in Anaheim.

How students can use generative AI — from aliciabankhofer.substack.com by Alicia Bankhofer
Part 4 of 4 in my series on Teaching and Learning in the AI Age

This article is the culmination of a series exploring AI’s impact on education.

Part 1: What Educators Need outlined essential AI literacy skills for teachers, emphasizing the need to move beyond basic ChatGPT exploration to understand the full spectrum of AI tools available in education.

Part 2: What Students Need addressed how students require clear guidance to use AI safely, ethically, and responsibly, with emphasis on developing critical thinking skills alongside AI literacy.

Part 3: How Educators Can Use GenAI presented ten practical use cases for teachers, from creating differentiated resources to designing assessments, demonstrating how AI can reclaim 5-7 hours weekly for meaningful student interactions.

Part 4: How Students Can Use GenAI (this article) provides frameworks for guiding student AI use based on Joscha Falck’s dimensions: learning about, with, through, despite, and without AI.

Mapping a Multidimensional Framework for GenAI in Education — from er.educause.edu by Patricia Turner
Prompting careful dialogue through incisive questions can help chart a course through the ongoing storm of artificial intelligence.

The goal of this framework is to help faculty, educational developers, instructional designers, administrators, and others in higher education engage in productive discussions about the use of GenAI in teaching and learning. As others have noted, theoretical frameworks will need to be accompanied by research and teaching practice, each reinforcing and reshaping the others to create understandings that will inform the development of approaches to GenAI that are both ethical and maximally beneficial, while mitigating potential harms to those who engage with it.

Instructional Design Isn’t Dying — It’s Specialising — from drphilippahardman.substack.com by Dr. Philippa Hardman
Aka, how AI is impacting role & purpose of Instructional Design

Together, these developments have revealed something important: despite widespread anxiety, the instructional design role isn’t dying—it’s specialising.

What we’re witnessing isn’t the automation of instructional design and the death of the instructional designer, but rather the evolution of the ID role into multiple distinct professional pathways.

The generalist “full stack” instructional designer is slowly but decisively fracturing into specialised roles that reflect both the capabilities of generative AI and the strategic imperatives facing modern organisations.

In this week’s blog post, I’ll share what I’ve learned about how our field is transforming, and what it likely means for you and your career path.

Those instructional designers who cling to traditional generalist models risk being replaced, but those who embrace specialisation, data fluency, and AI collaboration will excel and lead the next evolution of the field. Similarly, those businesses that continue to view L&D as a cost centre and focus on automating content delivery will be outperformed, while those that invest in building agile, AI-enabled learning ecosystems will drive measurable performance gains and secure their competitive advantage.

Adding AI to Every Step in Your eLearning Design Workflow — from learningguild.com by George Hanshaw

We know that eLearning is a staple of training and development. The expectations of the learners are higher than ever: They expect a dynamic, interactive, and personalized learning experience. As instructional designers, we are tasked with meeting these expectations by creating engaging and effective learning solutions.

The integration of Artificial Intelligence (AI) into our eLearning design process is a game-changer that can significantly enhance the quality and efficiency of our work.

No matter if you use ADDIE or rapid prototyping, AI has a fit in every aspect of your workflow. By integrating AI, you can ensure a more efficient and effective design process that adapts to the unique needs of your learners. This not only saves time and resources but also significantly enhances the overall learning experience. We will explore the needs analysis and the general design process.

Bob Ambrogi posts several solid items re: legaltech & legal education

On 04/17/2025, in Access to Justice (A2J), Artificial Intelligence/Agents/LLMs/and Related, collaboration, Europe, innovation, intelligent systems, law schools, legal reform, legal technologies, legislatures / government / legal, research, United States, user experience (UX), vendors, by Daniel Christian

Thomson Reuters Survey: Over 95% of Legal Professionals Expect Gen AI to Become Central to Workflow Within Five Year — from lawnext.com by Bob Ambrogi

Thomson Reuters today released its 2025 Generative AI in Professional Services Report, and it reveals that legal professionals have become increasingly optimistic about generative AI, with adoption rates nearly doubling over the past year and a growing belief that the technology should be incorporated into legal work.

According to the report, 26% of legal organizations are now actively using gen AI, up from 14% in 2024. While only 15% of law firm respondents say gen AI is currently central to their workflow, a striking 78% believe it will become central within the next five years.

AI-Powered Legal Work Redefined: Libra Launches Major Update for Legal Professionals — from lawnext.com by Bob Ambrogi

Berlin, April 14, 2025 – Berlin-based Legal Tech startup Libra is launching its most comprehensive update to date, leveraging AI to relieve law firms and legal departments of routine tasks, accelerate research, and improve team collaboration. “Libra v2” combines highly developed AI, a modern user interface, and practical tools to set a new standard for efficient and precise work in all legal areas.

“We listened intently to feedback from law firms and in-house teams,” said Viktor von Essen, founder of Libra. “The result is Libra v2: an AI solution that intelligently supports every step of daily legal work – from initial research to final contract review. We want legal experts to be able to fully concentrate on what is essential: excellent legal advice.”

The Three Cs of Teaching Technology to Law Students — from lawnext.com by Bob Ambrogi

In law practice today, technology is no longer optional — it’s essential. As practicing attorneys increasingly rely on technology tools to serve clients, conduct research, manage documents and streamline workflows, the question is often debated: Are law schools adequately preparing students for this reality?

Unfortunately, for the majority of law schools, the answer is no. But that only begs the question: What should they be doing?

A coincidence of events last week had me thinking about law schools and legal tech, chief among them my attendance at LIT Con, Suffolk Law School’s annual conference to showcase legal innovation and technology — with a portion of it devoted to access-to-justice projects developed by Suffolk Law students themselves.

While not from Bob, I’m also going to include this one here:

Your AI Options: 7 Considerations Before You Buy — from artificiallawyer.com by Liza Pestillos-Ocat

But here’s the problem: not all AI is useful and not all of it is built for the way your legal team works.

Most firms aren’t asking whether they should use AI because they already are. The real question now is what comes next? How do you expand the value of AI across more teams, more matters, and more workflows without introducing unnecessary risk, complexity, or cost?

To get this right, legal professionals need to understand which tools will solve real problems and deliver the most value to their team. That starts with asking better questions, including the ones that follow, before making your next investment in AI for lawyers.

Reflections on “2025 EDUCAUSE Students and Technology Report” [Christian]

On 04/14/2025, in accessibility / UDL, adjunct faculty, Alternatives, Artificial Intelligence/Agents/LLMs/and Related, Bias | Diversity Equity & Inclusion (DE&I), blended learning, career development, CMS/LMS, colleges, communications, community colleges, cost of getting a degree, dangers of the status quo, Daniel S. Christian, digital learning, education technology, emerging technologies, faculty/staff, future of higher education, game-changing environment, higher education, human-computer interaction (HCI), hybrid learning, instructional design, intelligent systems, IT in HE, learning ecosystem, Learning Experience Design, learning preferences, neurodivergent/special needs, online learning, student-related, teaching & learning, technologies for your home, technology (general), United States, universities, workplace, by Daniel Christian

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2025 EDUCAUSE Students and Technology Report: Shaping the Future of Higher Education Through Technology, Flexibility, and Well-Being — from library.educause.edu

The student experience in higher education is continually evolving, influenced by technological advancements, shifting student needs and expectations, evolving workforce demands, and broadening sociocultural forces. In this year’s report, we examine six critical aspects of student experiences in higher education, providing insights into how institutions can adapt to meet student needs and enhance their learning experience and preparation for the workforce:

Satisfaction with Technology-Related Services and Supports
Modality Preferences
Hybrid Learning Experiences
Generative AI in the Classroom
Workforce Preparation
Accessibility and Mental Health

DSC: Shame on higher ed for not preparing students for the workplace (see below). You’re doing your students wrong…again. Not only do you continue to heap a load of debt on their backs, but you’re also continuing to not get them ready for the workplace. So don’t be surprised if eventually you’re replaced by a variety of alternatives that students will flock towards.
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DSC: And students don’t have a clue as to what awaits them in the workplace — they see AI-powered tools and technologies at an incredibly low score of only 3%. Yeh, right. You’ll find out. Here’s but one example from one discipline/field of work –> Thomson Reuters Survey: Over 95% of Legal Professionals Expect Gen AI to Become Central to Workflow Within Five Years

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Figure 15. Competency Areas Expected to Be Important for Career

How might the memory of an AI — over time — impact personalized and lifelong learning? [Christian]

On 04/11/2025, in 21st century, 24x7x365 access, adjunct faculty, adult learning, Artificial Intelligence/Agents/LLMs/and Related, cloud-based computing / apps / other cloud-related, colleges, community colleges, corporate universities / corporate training, Daniel S. Christian, education, education reform, education technology, emerging technologies, experimentation, faculty/staff, formal learning, future, future of higher education, game-changing environment, generational differences, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, informal learning, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning preferences, lifelong learning, online learning, online media, online tutoring, personalized/customized learning, platforms, skills, society, student-related, teachers, teaching & learning, teaching online, technologies for your home, training / L&D, trends, universities, vendors, vision/possibilities, web-based collaboration, by Daniel Christian

From DSC:
After seeing Sam’s posting below, I can’t help but wonder:

How might the memory of an AI over time impact the ability to offer much more personalized learning?
How will that kind of memory positively impact a person’s learning-related profile?
Which learning-related agents get called upon?
Which learning-related preferences does a person have while learning about something new?
Which methods have worked best in the past for that individual? Which methods didn’t work so well with him or her?

we have greatly improved memory in chatgpt–it can now reference all your past conversations!

this is a surprisingly great feature imo, and it points at something we are excited about: ai systems that get to know you over your life, and become extremely useful and personalized.

— Sam Altman (@sama) April 10, 2025

Starting today, memory in ChatGPT can now reference all of your past chats to provide more personalized responses, drawing on your preferences and interests to make it even more helpful for writing, getting advice, learning, and beyond. pic.twitter.com/s9BrWl94iY

— OpenAI (@OpenAI) April 10, 2025

Reflections on “Are You Ready for the AI University? Everything is about to change.” [Latham]

On 04/10/2025, in 21st century, 24x7x365 access, accreditation, adjunct faculty, adult learning, Artificial Intelligence/Agents/LLMs/and Related, assessment, Blockchain, bots, career development, change, changing business models, cloud-based computing / apps / other cloud-related, CMS/LMS, collaboration, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, cost of getting a degree, credentialing, culture, curriculum, dangers of the status quo, Daniel S. Christian, data related items, Design Thinking, digital learning, disruption, education technology, emerging technologies, Emotion, engagement / engaging students, expectations, experimentation, faculty/staff, future, future of higher education, game-changing environment, generational differences, global / globalization, Google, higher education, human-computer interaction (HCI), IBM, ideas, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, leadership, learner profiles, learning, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning preferences, learning spaces, liberal arts, lifelong learning, MBA, Michigan, new business models, online learning, online media, online tutoring, organizational change, pace of change, pedagogy, personalized/customized learning, platforms, productivity / tips and tricks, professional development, reinvent, skills, society, staying relevant, strategy, student-related, surviving, teaching & learning, technologies for your home, tools, trends, United States, universities, usability, user experience (UX), virtual tutoring, vision/possibilities, web-based collaboration, workplace, by Daniel Christian

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Are You Ready for the AI University? Everything is about to change. — from chronicle.com by Scott Latham

Over the course of the next 10 years, AI-powered institutions will rise in the rankings. US News & World Report will factor a college’s AI capabilities into its calculations. Accrediting agencies will assess the degree of AI integration into pedagogy, research, and student life. Corporations will want to partner with universities that have demonstrated AI prowess. In short, we will see the emergence of the AI haves and have-nots.
…
What’s happening in higher education today has a name: creative destruction. The economist Joseph Schumpeter coined the term in 1942 to describe how innovation can transform industries. That typically happens when an industry has both a dysfunctional cost structure and a declining value proposition. Both are true of higher education.
…
Out of the gate, professors will work with technologists to get AI up to speed on specific disciplines and pedagogy. For example, AI could be “fed” course material on Greek history or finance and then, guided by human professors as they sort through the material, help AI understand the structure of the discipline, and then develop lectures, videos, supporting documentation, and assessments.
…
In the near future, if a student misses class, they will be able watch a recording that an AI bot captured. Or the AI bot will find a similar lecture from another professor at another accredited university. If you need tutoring, an AI bot will be ready to help any time, day or night. Similarly, if you are going on a trip and wish to take an exam on the plane, a student will be able to log on and complete the AI-designed and administered exam. Students will no longer be bound by a rigid class schedule. Instead, they will set the schedule that works for them.

Early and mid-career professors who hope to survive will need to adapt and learn how to work with AI. They will need to immerse themselves in research on AI and pedagogy and understand its effect on the classroom.

From DSC:
I had a very difficult time deciding which excerpts to include. There were so many more excerpts for us to think about with this solid article. While I don’t agree with several things in it, EVERY professor, president, dean, and administrator working within higher education today needs to read this article and seriously consider what Scott Latham is saying.

Change is already here, but according to Scott, we haven’t seen anything yet. I agree with him and, as a futurist, one has to consider the potential scenarios that Scott lays out for AI’s creative destruction of what higher education may look like. Scott asserts that some significant and upcoming impacts will be experienced by faculty members, doctoral students, and graduate/teaching assistants (and Teaching & Learning Centers and IT Departments, I would add). But he doesn’t stop there. He brings in presidents, deans, and other members of the leadership teams out there.

There are a few places where Scott and I differ.

The foremost one is the importance of the human element — i.e., the human faculty member and students’ learning preferences. I think many (most?) students and lifelong learners will want to learn from a human being. IBM abandoned their 5-year, $100M ed push last year and one of the key conclusions was that people want to learn from — and with — other people:

To be sure, AI can do sophisticated things such as generating quizzes from a class reading and editing student writing. But the idea that a machine or a chatbot can actually teach as a human can, he said, represents “a profound misunderstanding of what AI is actually capable of.”

Nitta, who still holds deep respect for the Watson lab, admits, “We missed something important. At the heart of education, at the heart of any learning, is engagement. And that’s kind of the Holy Grail.”

— Satya Nitta, a longtime computer researcher at
IBM’s Watson Research Center in Yorktown Heights, NY
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By the way, it isn’t easy for me to write this. As I wanted AI and other related technologies to be able to do just what IBM was hoping that it would be able to do.

Also, I would use the term learning preferences where Scott uses the term learning styles.

Scott also mentions:

“In addition, faculty members will need to become technologists as much as scholars. They will need to train AI in how to help them build lectures, assessments, and fine-tune their classroom materials. Further training will be needed when AI first delivers a course.”

It has been my experience from working with faculty members for over 20 years that not all faculty members want to become technologists. They may not have the time, interest, and/or aptitude to become one (and vice versa for technologists who likely won’t become faculty members).

That all said, Scott relays many things that I have reflected upon and relayed for years now via this Learning Ecosystems blog and also via The Learning from the Living [AI-Based Class] Room vision — the use of AI to offer personalized and job-relevant learning, the rising costs of higher education, the development of new learning-related offerings and credentials at far less expensive prices, the need to provide new business models and emerging technologies that are devoted more to lifelong learning, plus several other things.

So this article is definitely worth your time to read, especially if you are working in higher education or are considering a career therein!

Addendum later on 4/10/25:

U-M’s Ross School of Business, Google Public Sector launch virtual teaching assistant pilot program — from news.umich.edu by Jeff Karoub; via Paul Fain

Google Public Sector and the University of Michigan’s Ross School of Business have launched an advanced Virtual Teaching Assistant pilot program aimed at improving personalized learning and enlightening educators on artificial intelligence in the classroom.

The AI technology, aided by Google’s Gemini chatbot, provides students with all-hours access to support and self-directed learning. The Virtual TA represents the next generation of educational chatbots, serving as a sophisticated AI learning assistant that instructors can use to modify their specific lessons and teaching styles.

The Virtual TA facilitates self-paced learning for students, provides on-demand explanations of complex course concepts, guides them through problem-solving, and acts as a practice partner. It’s designed to foster critical thinking by never giving away answers, ensuring students actively work toward solutions.

The 2025 AI Index Report [Stanford University]

On 04/09/2025, in 21st century, 24x7x365 access, Africa, Artificial Intelligence/Agents/LLMs/and Related, Asia, bots, business, Canada, change, changing business models, cloud-based computing / apps / other cloud-related, collaboration, communities of practice, computer science, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital learning, economics, education, education technology, emerging technologies, ethics, Europe, experimentation, faculty/staff, future, game-changing environment, global / globalization, health, human-computer interaction (HCI), innovation, intelligent systems, learning ecosystem, legislatures / government / legal, mathematics, morals/values, platforms, policy, research, science, society, trends, United States, universities, workplace, by Daniel Christian

The 2025 AI Index Report — from Stanford University’s Human-Centered Artificial Intelligence Lab (hai.stanford.edu); item via The Neuron

Top Takeaways

AI performance on demanding benchmarks continues to improve.
AI is increasingly embedded in everyday life.
Business is all in on AI, fueling record investment and usage, as research continues to show strong productivity impacts.
The U.S. still leads in producing top AI models—but China is closing the performance gap.
The responsible AI ecosystem evolves—unevenly.
Global AI optimism is rising—but deep regional divides remain.
…and several more

Also see:

12 Graphs That Explain the State of AI in 2025 — from by Eliza Strickland; item via The Neuron
Stanford’s AI Index tracks performance, investment, public opinion, and more

The Neuron’s take on this:

So, what should you do? You really need to start trying out these AI tools. They’re getting cheaper and better, and they can genuinely help save time or make work easier—ignoring them is like ignoring smartphones ten years ago.

Just keep two big things in mind:

Making the next super-smart AI costs a crazy amount of money and uses tons of power (seriously, they’re buying nuclear plants and pushing coal again!).
Companies are still figuring out how to make AI perfectly safe and fair—cause it still makes mistakes.

So, use the tools, find what helps you, but don’t trust them completely.

We’re building this plane mid-flight, and Stanford’s report card is just another confirmation that we desperately need better safety checks before we hit major turbulence.

Addendum on 4/16:

The 2025 ABA Techshow Startup Alley Pitch Competition Ended In A Tie – Here Are The Winners — from lawnext.com by Bob Ambrogi

This year, two startups ended up with an equal number of votes for the top spot:

Case Crafter, a company from Norway that helps legal professionals build compelling visual timelines based on case files and evidence.
Querious, a product that provides attorneys with real-time insights during client conversations into legal issues, relevant content, and suggested questions and follow-ups.
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DC: If https://t.co/c3Io6EqFds can do this with legal-related conversations, what about with lectures & learning-related applications of this?

Querious transforms client conversations with real-time legal insights while reducing non-billable administrative tasks.#legaltech #AI pic.twitter.com/s0r9o4N89q

— Daniel S. Christian (@dchristian5) April 9, 2025

AI academy gives law students a head start on legal tech, says OBA innovator — from canadianlawyermag.com by Branislav Urosevic

The Ontario Bar Association has recently launched a hands-on AI learning platform tailored for lawyers. Called the AI Academy, the initiative is designed to help legal professionals explore, experiment with, and adopt AI tools relevant to their practice.

Colin Lachance, OBA’s innovator-in-residence and the lead designer of the platform, says that although the AI Academy was built for practising lawyers, it is also well-suited for law students.

“AI agents that can train thousands of employees simultaneously” [Nuñez], “Introducing Claude for Education” [Anthropic], + other items re: AI in our LEs

On 04/03/2025, in adult learning, Artificial Intelligence/Agents/LLMs/and Related, chemistry, cloud-based computing / apps / other cloud-related, colleges, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, design, education technology, emerging technologies, experimentation, future, future of higher education, game-changing environment, generational differences, Google, graphics, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning spaces, lifelong learning, mathematics, multimedia, Open AI, pedagogy, platforms, productivity / tips and tricks, student-related, teachers, teaching & learning, tools, training / L&D, trends, United States, universities, vendors, workplace, youth, by Daniel Christian

Uplimit raises stakes in corporate learning with suite of AI agents that can train thousands of employees simultaneously — from venturebeat.com by Michael Nuñez|

Uplimit unveiled a suite of AI-powered learning agents today designed to help companies rapidly upskill employees while dramatically reducing administrative burdens traditionally associated with corporate training.

The San Francisco-based company announced three sets of purpose-built AI agents that promise to change how enterprises approach learning and development: skill-building agents, program management agents, and teaching assistant agents. The technology aims to address the growing skills gap as AI advances faster than most workforces can adapt.

“There is an unprecedented need for continuous learning—at a scale and speed traditional systems were never built to handle,” said Julia Stiglitz, CEO and co-founder of Uplimit, in an interview with VentureBeat. “The companies best positioned to thrive aren’t choosing between AI and their people—they’re investing in both.”

Introducing Claude for Education — from anthropic.com

Today we’re launching Claude for Education, a specialized version of Claude tailored for higher education institutions. This initiative equips universities to develop and implement AI-enabled approaches across teaching, learning, and administration—ensuring educators and students play a key role in actively shaping AI’s role in society.

As part of announcing Claude for Education, we’re introducing:

Learning mode: A new Claude experience that guides students’ reasoning process rather than providing answers, helping develop critical thinking skills
University-wide Claude availability: Full campus access agreements with Northeastern University, London School of Economics and Political Science (LSE), and Champlain College, making Claude available to all students
Academic partnerships: Joining Internet2 and working with Instructure to embed AI into teaching & learning with Canvas LMS
Student programs: A new Claude Campus Ambassadors program along with an initiative offering API credits for student projects

A comment on this from The Rundown AI:

Why it matters: Education continues to grapple with AI, but Anthropic is flipping the script by making the tech a partner in developing critical thinking rather than an answer engine. While the controversy over its use likely isn’t going away, this generation of students will have access to the most personalized, high-quality learning tools ever.

Should College Graduates Be AI Literate? — from chronicle.com by Beth McMurtrie (behind a paywall)
More institutions are saying yes. Persuading professors is only the first barrier they face.

Last fall one of Jacqueline Fajardo’s students came to her office, eager to tell her about an AI tool that was helping him learn general chemistry. Had she heard of Google NotebookLM? He had been using it for half a semester in her honors course. He confidently showed her how he could type in the learning outcomes she posted for each class and the tool would produce explanations and study guides. It even created a podcast based on an academic paper he had uploaded. He did not feel it was important to take detailed notes in class because the AI tool was able to summarize the key points of her lectures.

Showing Up for the Future: Why Educators Can’t Sit Out the AI Conversation — from marcwatkins.substack.com with a guest post from Lew Ludwig

The Risk of Disengagement
Let’s be honest: most of us aren’t jumping headfirst into AI. At many of our institutions, it’s not a gold rush—it’s a quiet standoff. But the group I worry most about isn’t the early adopters. It’s the faculty who’ve decided to opt out altogether.

That choice often comes from a place of care. Concerns about data privacy, climate impact, exploitative labor, and the ethics of using large language models are real—and important. But choosing not to engage at all, even on ethical grounds, doesn’t remove us from the system. It just removes our voices from the conversation.

And without those voices, we risk letting others—those with very different priorities—make the decisions that shape what AI looks like in our classrooms, on our campuses, and in our broader culture of learning.

Turbocharge Your Professional Development with AI — from learningguild.com by Dr. RK Prasad

You’ve just mastered a few new eLearning authoring tools, and now AI is knocking on the door, offering to do your job faster, smarter, and without needing coffee breaks. Should you be worried? Or excited?

If you’re a Learning and Development (L&D) professional today, AI is more than just a buzzword—it’s transforming the way we design, deliver, and measure corporate training. But here’s the good news: AI isn’t here to replace you. It’s here to make you better at what you do.

The challenge is to harness its potential to build digital-ready talent, not just within your organization but within yourself.

Let’s explore how AI is reshaping L&D strategies and how you can leverage it for professional development.

5 Recent AI Notables — from automatedteach.com by Graham Clay

1. OpenAI’s New Image Generator
What Happened: OpenAI integrated a much more powerful image generator directly into GPT-4o, making it the default image creator in ChatGPT. Unlike previous image models, this one excels at accurately rendering text in images, precise visualization of diagrams/charts, and multi-turn image refinement through conversation.

Why It’s Big: For educators, this represents a significant advancement in creating educational visuals, infographics, diagrams, and other instructional materials with unprecedented accuracy and control. It’s not perfect, but you can now quickly generate custom illustrations that accurately display mathematical equations, chemical formulas, or process workflows — previously a significant hurdle in digital content creation — without requiring graphic design expertise or expensive software. This capability dramatically reduces the time between conceptualizing a visual aid and implementing it in course materials.
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The 4 AI modes that will supercharge your workflow — from aiwithallie.beehiiv.com by Allie K. Miller
The framework most people and companies won’t discover until 2026

AI in Education Survey: What UK and US Educators Think in 2025 — from twinkl.com
As artificial intelligence (AI) continues to shape the world around us, Twinkl conducted a large-scale survey between January 15th and January 22nd to explore its impact on the education sector, as well as the work lives of teachers across the UK and the USA.

Teachers’ use of AI for work continues to rise
Twinkl’s survey asked teachers whether they were currently using AI for work purposes. Comparing these findings to similar surveys over recent years shows the use of AI tools by teachers has seen a significant increase across both the UK and USA.

According to two UK surveys by the National Literacy Trust – 30% of teachers used generative AI in 2023 and nearly half (47.7%) in 2024. Twinkl’s survey indicates that AI adoption continues to rise rapidly, with 60% of UK educators currently integrating it into their work lives in 2025.
Similarly, with 62% of US teachers currently using AI for work, uptake appears to have risen greatly in the past 12 months, with just 25% saying they were leveraging the new technology in the 2023-24 school year according to a RAND report.
Teachers are using AI more for work than in their personal lives: In the UK, personal usage drops to 43% (from 60% at school). In the US, 52% are using AI for non-work purposes (versus 62% in education settings).

60% of UK teachers and 62% of US teachers use AI in their work life in 2025.

OpenAI opens OpenAI Academy — A free, online platform to help people gain AI literacy

On 03/28/2025, in 21st century, 24x7x365 access, adjunct faculty, adult learning, Artificial Intelligence/Agents/LLMs/and Related, bots, 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, corporate universities / corporate training, curriculum, digital audio, digital learning, digital video, economics, education technology, emerging technologies, experimentation, faculty/staff, future, game-changing environment, global / globalization, heutagogy, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), informal learning, intelligent systems, IT in HE, K-12 related, law schools, learning ecosystem, multimedia, new media literacies, online learning, online media, online tutoring, Open AI, open courseware and systems, platforms, productivity / tips and tricks, professional development, skills, social learning / networks, society, staying relevant, student teaching/teacher education, student-related, teachers, teaching & learning, technologies for your home, tools, trends, United States, universities, vendors, workplace, youth, by Daniel Christian

Students and folks looking for work may want to check out:

AI Career Prep: Resumes and Interviews

Also relevant/see:

OpenAI Launches OpenAI Academy: Free Guide To Understanding AI — from voi.id
OpenAI Launches OpenAI Academy to Drive AI Innovation in Low- and Middle-Income Countries — from startupsvibes.com by Emmaunel Daniji

The Third Horizon of Learning Shifting beyond the Industrial Model — from gettingsmart.com by Sujata Bhatt & Mason Pashia

Over 24 blog posts, we have sketched a bold vision of what this next horizon of education looks like in action and highlighted the many innovators working to bring it to life. These pioneers are building new models that prioritize human development, relationships, and real-world relevance as most valuable. They are forging partnerships, designing and adopting transformative technologies, developing new assessment methods, and more. These shifts transform the lived experiences of young people and serve the needs of families and communities. In short, they are delivering authentic learning experiences that better address the demands of today’s economy, society, and learners.

We’ve aggregated our findings from this blog series and turned it into an H3 Publication. Inside, you’ll find our key transformation takeaways for school designers and system leaders, as well as a full list of the contributing authors. Thank you to all of the contributors, including LearnerStudio for sponsoring the series and Sujata Bhatt at Incubate Learning for authorship, editing and curation support throughout the entirety of the series and publication.
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“A Big Gap In Legal Tech Satisfaction” [Barke] + other items re: legaltech

On 03/21/2025, in 21st century, Artificial Intelligence/Agents/LLMs/and Related, emerging technologies, Europe, innovation, intelligent systems, law schools, Legal operations, legal reform, legal technologies, legislatures / government / legal, UK, United States, usability, user experience (UX), by Daniel Christian

Stat(s) Of The Week: A Big Gap In Legal Tech Satisfaction — from abovethelaw.com by Jeremy Barke
Comparing sentiment across the pond.

Legal tech users in the U.S. and the U.K. report widely different levels of satisfaction with their systems, according to a new survey, raising questions about how companies are meeting lawyers’ needs.

According to “The State of Legal Tech Adoption” report by London-based Definely, 51% of U.S. respondents say they’re satisfied with the ROI of their legal technology, while only 22% of U.K. respondents say the same.

Legal tech company Clio acquires AI-focused platform specializing in large firms — from abajournal.com by Danielle Braff

Legal technology company Clio announced [on 3/13/25] that it acquired ShareDo, an artificial intelligence-focused platform specializing in large law firms.

The move represents a major departure for Clio, which was founded in 2008 and is based in Vancouver, British Columbia. The practice management software platform originally focused on solo, small and midsize firms.

“ShareDo has built a powerhouse, proving that large firms are hungry for smarter, faster and more flexible technology,” said Jack Newton, the CEO and founder of Clio, in a statement. “The large law firm market is on the brink of a major shift, and this acquisition cements our role in leading that change.”

How Wexler AI is transforming legal fact analysis and case strategy — from tech.eu by Cate Lawrence
Wexler AI has developed an AI-embedded platform that enables lawyers to uncover key facts, identify inconsistencies, and streamline case preparation.

It core functionalities include:

Advanced fact extraction and analysis: The system can process up to 500,000 documents simultaneously, surfacing critical facts and connections that might otherwise go unnoticed.
Chronology creation: Lawyers collaborate with Wexler AI to construct detailed timelines from extensive document sets, ensuring transparency in how key facts are selected and connected.
Inconsistency mapping: The AI detects contradictions between testimony and evidence, enhancing cross-examination and case strategy development.

Essential AI tools for better work — from wondertools.substack.com by Jeremy Caplan
My favorite tactics for making the most of AI — a podcast conversation

AI tools I consistently rely on (areas covered mentioned below)

Research and analysis
Communication efficiency
Multimedia creation

AI tactics that work surprisingly well

1. Reverse interviews
Instead of just querying AI, have it interview you. Get the AI to interview you, rather than interviewing it. Give it a little context and what you’re focusing on and what you’re interested in, and then you ask it to interview you to elicit your own insights.”

This approach helps extract knowledge from yourself, not just from the AI. Sometimes we need that guide to pull ideas out of ourselves.

OpenAI’s Deep Research Agent Is Coming for White-Collar Work — from wired.com by Will Knight
The research-focused agent shows how a new generation of more capable AI models could automate some office tasks.

Isla Fulford, a researcher at OpenAI, had a hunch that Deep Research would be a hit even before it was released.

Fulford had helped build the artificial intelligence agent, which autonomously explores the web, deciding for itself what links to click, what to read, and what to collate into an in-depth report. OpenAI first made Deep Research available internally; whenever it went down, Fulford says, she was inundated with queries from colleagues eager to have it back. “The number of people who were DMing me made us pretty excited,” says Fulford.

Since going live to the public on February 2, Deep Research has proven to be a hit with many users outside the company too.

Nvidia to open quantum computing research center in Boston — from seekingalpha.com by Ravikash Bakolia

Nvidia (NASDAQ:NVDA) will open a quantum computing research lab in Boston which is expected to start operations later this year.

The Nvidia Accelerated Quantum Research Center, or NVAQC, will integrate leading quantum hardware with AI supercomputers, enabling what is known as accelerated quantum supercomputing, said the company in a March 18 press release.

Nvidia’s CEO Jensen Huang also made this announcement on Thursday at the company’s first-ever Quantum Day at its annual GTC event.

French quantum computer firm Pasqal links up with NVIDIA — from reuters.com

PARIS, March 21 (Reuters) – Pasqal, a fast-growing French quantum computer start-up company, announced on Friday a partnership with chip giant Nvidia (NVDA.O), opens new tab whereby Pasqal’s customers would gain access to more tools to develop quantum applications.

Pasqal said it would connect its quantum computing units and cloud platform onto NVIDIA’s open-source platform called CUDA-Q.

Introducing next-generation audio models in the API — from openai.com
A new suite of audio models to power voice agents, now available to developers worldwide.

Today, we’re launching new speech-to-text and text-to-speech audio models in the API—making it possible to build more powerful, customizable, and intelligent voice agents that offer real value. Our latest speech-to-text models set a new state-of-the-art benchmark, outperforming existing solutions in accuracy and reliability—especially in challenging scenarios involving accents, noisy environments, and varying speech speeds. These improvements increase transcription reliability, making the models especially well-suited for use cases like customer call centers, meeting note transcription, and more.

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