Tech check: Innovation in motion: How AI is rewiring L&D workflows — from chieflearningofficer.com by Gabrielle Pike
AI isn’t here to replace us. It’s here to level us up.

For today’s chief learning officer, the days of just rolling out compliance training are long gone. In 2025, learning and development leaders are architects of innovation, crafting ecosystems that are agile, automated and AI-infused. This quarter’s Tech Check invites us to pause, assess and get strategic about where tech is taking us. Because the goal isn’t more tools—it’s smarter, more human learning systems that scale with the business.

Sections include:

  • The state of AI in L&D: Hype vs. reality
  • AI in design: From static content to dynamic experiences
  • AI in development: Redefining production workflows
  • Strategic questions CLOs should be asking
  • Future forward: What’s next?
  • Closing thought

American Federation of Teachers (AFT) to Launch National Academy for AI Instruction with Microsoft, OpenAI, Anthropic and United Federation of Teachers — from aft.org

NEW YORK – The AFT, alongside the United Federation of Teachers and lead partner Microsoft Corp., founding partner OpenAI, and Anthropic, announced the launch of the National Academy for AI Instruction today. The groundbreaking $23 million education initiative will provide access to free AI training and curriculum for all 1.8 million members of the AFT, starting with K-12 educators. It will be based at a state-of-the-art bricks-and-mortar Manhattan facility designed to transform how artificial intelligence is taught and integrated into classrooms across the United States.

The academy will help address the gap in structured, accessible AI training and provide a national model for AI-integrated curriculum and teaching that puts educators in the driver’s seat.


Students Are Anxious about the Future with A.I. Their Parents Are, Too. — from educationnext.org by Michael B. Horn
The fast-growing technology is pushing families to rethink the value of college

In an era when the college-going rate of high school graduates has dropped from an all-time high of 70 percent in 2016 to roughly 62 percent now, AI seems to be heightening the anxieties about the value of college.

According to the survey, two-thirds of parents say AI is impacting their view of the value of college. Thirty-seven percent of parents indicate they are now scrutinizing college’s “career-placement outcomes”; 36 percent say they are looking at a college’s “AI-skills curriculum,” while 35 percent respond that a “human-skills emphasis” is important to them.

This echoes what I increasingly hear from college leadership: Parents and students demand to see a difference between what they are getting from a college and what they could be “learning from AI.”


This next item on LinkedIn is compliments of Ray Schroeder:



How to Prepare Students for a Fast-Moving (AI)World — from rdene915.com by Dr. Rachelle Dené Poth

Preparing for a Future-Ready Classroom
Here are the core components I focus on to prepare students:

1. Unleash Creativity and Problem-Solving.
2. Weave in AI and Computational Thinking.
3. Cultivate Resilience and Adaptability.


AI Is Reshaping Learning Roles—Here’s How to Future-Proof Your Team — from onlinelearningconsortium.org by Jennifer Mathes, Ph.D., CEO, Online Learning Consortium; via Robert Gibson on LinkedIn

Culture matters here. Organizations that foster psychological safety—where experimentation is welcomed and mistakes are treated as learning—are making the most progress. When leaders model curiosity, share what they’re trying, and invite open dialogue, teams follow suit. Small tests become shared wins. Shared wins build momentum.

Career development must be part of this equation. As roles evolve, people will need pathways forward. Some will shift into new specialties. Others may leave familiar roles for entirely new ones. Making space for that evolution—through upskilling, mobility, and mentorship—shows your people that you’re not just investing in AI, you’re investing in them.

And above all, people need transparency. Teams don’t expect perfection. But they do need clarity. They need to understand what’s changing, why it matters, and how they’ll be supported through it. That kind of trust-building communication is the foundation for any successful change.

These shifts may play out differently across sectors—but the core leadership questions will likely be similar.

AI marks a turning point—not just for technology, but for how we prepare our people to lead through disruption and shape the future of learning.


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Is graduate employability a core university priority? — from timeshighereducation.com by Katherine Emms and Andrea Laczik
Universities, once judged primarily on the quality of their academic outcomes, are now also expected to prepare students for the workplace. Here’s how higher education is adapting to changing pressures

A clear, deliberate shift in priorities is under way. Embedding employability is central to an Edge Foundation report, carried out in collaboration with UCL’s Institute of Education, looking at how English universities are responding. In placing employability at the centre of their strategies – not just for professional courses but across all disciplines – the two universities that were analysed in this research show how they aim to prepare students for the labour market overall. Although the employability strategy is initialled by the universities’ senior leaders, the research showed that realising this employability strategy must be understood and executed by staff at all levels across departments. The complexity of offering insights into industry pathways and building relevant skills involves curricula development, student-centred teaching, careers support, partnership work and employer engagement.


Every student can benefit from an entrepreneurial mindset — from timeshighereducation.com by Nicolas Klotz
To develop the next generation of entrepreneurs, universities need to nurture the right mindset in students of all disciplines. Follow these tips to embed entrepreneurial education

This shift demands a radical rethink of how we approach entrepreneurial mindset in higher education. Not as a specialism for a niche group of business students but as a core competency that every student, in every discipline, can benefit from.

At my university, we’ve spent the past several years re-engineering how we embed entrepreneurship into daily student life and learning.

What we’ve learned could help other institutions, especially smaller or resource-constrained ones, adapt to this new landscape.

The first step is recognising that entrepreneurship is not only about launching start-ups for profit. It’s about nurturing a mindset that values initiative, problem-solving, resilience and creative risk-taking. Employers increasingly want these traits, whether the student is applying for a traditional job or proposing their own venture.


Build foundations for university-industry partnerships in 90 days— from timeshighereducation.com by Raul Villamarin Rodriguez and Hemachandran K
Graduate employability could be transformed through systematic integration of industry partnerships. This practical guide offers a framework for change in Indian universities

The most effective transformation strategy for Indian universities lies in systematic industry integration that moves beyond superficial partnerships and towards deep curriculum collaboration. Rather than hoping market alignment will occur naturally, institutions must reverse-engineer academic programmes from verified industry needs.

Our six-month implementation at Woxsen University demonstrates this framework’s practical effectiveness, achieving more than 130 industry partnerships, 100 per cent faculty participation in transformation training, and 75 per cent of students receiving industry-validated credentials with significantly improved employment outcomes.


 

How Do You Teach Computer Science in the A.I. Era? — from nytimes.com by Steve Lohr; with thanks to Ryan Craig for this resource
Universities across the country are scrambling to understand the implications of generative A.I.’s transformation of technology.

The future of computer science education, Dr. Maher said, is likely to focus less on coding and more on computational thinking and A.I. literacy. Computational thinking involves breaking down problems into smaller tasks, developing step-by-step solutions and using data to reach evidence-based conclusions.

A.I. literacy is an understanding — at varying depths for students at different levels — of how A.I. works, how to use it responsibly and how it is affecting society. Nurturing informed skepticism, she said, should be a goal.

At Carnegie Mellon, as faculty members prepare for their gathering, Dr. Cortina said his own view was that the coursework should include instruction in the traditional basics of computing and A.I. principles, followed by plenty of hands-on experience designing software using the new tools.

“We think that’s where it’s going,” he said. “But do we need a more profound change in the curriculum?”

 

In A Mega Deal, Clio Buys vLex for $1 Billion, Merging AI, Research and Practice Management — from lawnext.com by Bob Ambrogi

In a landmark deal that will undoubtedly reshape the legal tech landscape, law practice management company Clio has signed a definitive agreement to acquire the AI and legal research company vLex for $1 billion in cash and stock.

The companies say that the acquisition will “establish a new category of intelligent legal technology at the intersection of the business and practice of law, empowering legal professionals to seamlessly manage, research, and execute legal work within a unified system.”

 

The EU’s Legal Tech Tipping Point – AI Regulation, Data Sovereignty, and eDiscovery in 2025 — from jdsupra.com by Melina Efstathiou

The Good, the Braver and the Curious.
As we navigate through 2025, the European legal landscape is undergoing a significant transformation, particularly in the realms of artificial intelligence (AI) regulation and data sovereignty. These changes are reshaping how legal departments and more specifically eDiscovery professionals operate, compelling them to adapt to new compliance requirements and technological advancements.

Following on from our blog post on Navigating eDisclosure in the UK and Practice Direction 57AD, we are now moving on to explore AI regulation in the greater European spectrum, taking a contrasting glance towards the UK and the US as well, at the close of this post.


LegalTech’s Lingering Hurdles: How AI is Finally Unlocking Efficiency in the Legal Sector — from techbullion.co by Abdul Basit

However, as we stand in mid-2025, a new paradigm is emerging. Artificial Intelligence, once a buzzword, is now demonstrably addressing many of the core issues that have historically plagued LegalTech adoption and effectiveness, ushering in an era of unprecedented efficiency. Legal tech specialists like LegalEase are leading the way with some of these newer solutions, such as Ai powered NDA drafting.

Here’s how AI is making profound efficiencies:

    • Automated Document Review and Analysis:
    • Intelligent Contract Lifecycle Management (CLM):
    • Enhanced Legal Research:
    • Predictive Analytics for Litigation and Risk:
    • Streamlined Practice Management and Workflow Automation:
    • Personalized Legal Education and Training:
    • Improved Client Experience:

The AI Strategy Potluck: Law Firms Showing Up Empty-Handed, Hungry, And Weirdly Proud Of It — from abovethelaw.com by Joe Patrice
There’s a $32 billion buffet of time and money on the table, and the legal industry brought napkins.

The Thomson Reuters “Future of Professionals” report(Opens in a new window) just dropped and one stat standing out among its insights is that organizations with a visible AI strategy are not only twice as likely to report growth, they’re also 3.5 times more likely to see actual, tangible benefits from AI adoption.

AI Adoption Strategies


Speaking of legal-related items as well as tech, also see:

  • Landmark AI ruling is a blow to authors and artists — from popular.info by Judd Legum
    This week, a federal judge, William Alsup, rejected Anthropic’s effort to dismiss the case and found that stealing books from the internet is likely a copyright violation. A trial will be scheduled in the future. If Anthropic loses, each violation could come with a fine of $750 or more, potentially exposing the company to billions in damages. Other AI companies that use stolen work to train their models — and most do — could also face significant liability.
 

2025 Learning System Top Picks — from elearninfo247.com by Craig Weiss

Who is leading the pack? Who is setting themselves apart here in the mid-year?

Are they an LMS? LMS/LXP? Talent Development System? Mentoring? Learning Platform?

Something else?

Are they solely customer training/education, mentoring, or coaching? Are they focused only on employees? Are they an amalgamation of all or some?

Well, they cut across the board – hence, they slide under the “Learning Systems” umbrella, which is under the bigger umbrella term – “Learning Technology.”

Categories: L&D-specific, Combo (L&D and Training, think internal/external audiences), and Customer Training/Education (this means customer education, which some vendors use to mean the same as customer training).

 

“Using AI Right Now: A Quick Guide” [Molnick] + other items re: AI in our learning ecosystems

Thoughts on thinking — from dcurt.is by Dustin Curtis

Intellectual rigor comes from the journey: the dead ends, the uncertainty, and the internal debate. Skip that, and you might still get the insight–but you’ll have lost the infrastructure for meaningful understanding. Learning by reading LLM output is cheap. Real exercise for your mind comes from building the output yourself.

The irony is that I now know more than I ever would have before AI. But I feel slightly dumber. A bit more dull. LLMs give me finished thoughts, polished and convincing, but none of the intellectual growth that comes from developing them myself. 


Using AI Right Now: A Quick Guide — from oneusefulthing.org by Ethan Mollick
Which AIs to use, and how to use them

Every few months I put together a guide on which AI system to use. Since I last wrote my guide, however, there has been a subtle but important shift in how the major AI products work. Increasingly, it isn’t about the best model, it is about the best overall system for most people. The good news is that picking an AI is easier than ever and you have three excellent choices. The challenge is that these systems are getting really complex to understand. I am going to try and help a bit with both.

First, the easy stuff.

Which AI to Use
For most people who want to use AI seriously, you should pick one of three systems: Claude from Anthropic, Google’s Gemini, and OpenAI’s ChatGPT.

Also see:


Student Voice, Socratic AI, and the Art of Weaving a Quote — from elmartinsen.substack.com by Eric Lars Martinsen
How a custom bot helps students turn source quotes into personal insight—and share it with others

This summer, I tried something new in my fully online, asynchronous college writing course. These classes have no Zoom sessions. No in-person check-ins. Just students, Canvas, and a lot of thoughtful design behind the scenes.

One activity I created was called QuoteWeaver—a PlayLab bot that helps students do more than just insert a quote into their writing.

Try it here

It’s a structured, reflective activity that mimics something closer to an in-person 1:1 conference or a small group quote workshop—but in an asynchronous format, available anytime. In other words, it’s using AI not to speed students up, but to slow them down.

The bot begins with a single quote that the student has found through their own research. From there, it acts like a patient writing coach, asking open-ended, Socratic questions such as:

What made this quote stand out to you?
How would you explain it in your own words?
What assumptions or values does the author seem to hold?
How does this quote deepen your understanding of your topic?
It doesn’t move on too quickly. In fact, it often rephrases and repeats, nudging the student to go a layer deeper.


The Disappearance of the Unclear Question — from jeppestricker.substack.com Jeppe Klitgaard Stricker
New Piece for UNESCO Education Futures

On [6/13/25], UNESCO published a piece I co-authored with Victoria Livingstone at Johns Hopkins University Press. It’s called The Disappearance of the Unclear Question, and it’s part of the ongoing UNESCO Education Futures series – an initiative I appreciate for its thoughtfulness and depth on questions of generative AI and the future of learning.

Our piece raises a small but important red flag. Generative AI is changing how students approach academic questions, and one unexpected side effect is that unclear questions – for centuries a trademark of deep thinking – may be beginning to disappear. Not because they lack value, but because they don’t always work well with generative AI. Quietly and unintentionally, students (and teachers) may find themselves gradually avoiding them altogether.

Of course, that would be a mistake.

We’re not arguing against using generative AI in education. Quite the opposite. But we do propose that higher education needs a two-phase mindset when working with this technology: one that recognizes what AI is good at, and one that insists on preserving the ambiguity and friction that learning actually requires to be successful.




Leveraging GenAI to Transform a Traditional Instructional Video into Engaging Short Video Lectures — from er.educause.edu by Hua Zheng

By leveraging generative artificial intelligence to convert lengthy instructional videos into micro-lectures, educators can enhance efficiency while delivering more engaging and personalized learning experiences.


This AI Model Never Stops Learning — from link.wired.com by Will Knight

Researchers at Massachusetts Institute of Technology (MIT) have now devised a way for LLMs to keep improving by tweaking their own parameters in response to useful new information.

The work is a step toward building artificial intelligence models that learn continually—a long-standing goal of the field and something that will be crucial if machines are to ever more faithfully mimic human intelligence. In the meantime, it could give us chatbots and other AI tools that are better able to incorporate new information including a user’s interests and preferences.

The MIT scheme, called Self Adapting Language Models (SEAL), involves having an LLM learn to generate its own synthetic training data and update procedure based on the input it receives.


Edu-Snippets — from scienceoflearning.substack.com by Nidhi Sachdeva and Jim Hewitt
Why knowledge matters in the age of AI; What happens to learners’ neural activity with prolonged use of LLMs for writing

Highlights:

  • Offloading knowledge to Artificial Intelligence (AI) weakens memory, disrupts memory formation, and erodes the deep thinking our brains need to learn.
  • Prolonged use of ChatGPT in writing lowers neural engagement, impairs memory recall, and accumulates cognitive debt that isn’t easily reversed.
 
 

How Do You Build a Learner-Centered Ecosystem? — from gettingsmart.com by Bobbi Macdonald and Alin Bennett

Key Points

  • It’s not just about redesigning public education—it’s about rethinking how, where and with whom learning happens. Communities across the United States are shaping learner-centered ecosystems and gathering insights along the way.
  • What does it take to build a learner-centered ecosystem? A shared vision. Distributed leadership. Place-based experiences.  Repurposed resources. And more. This piece unpacks 10 real-world insights from pilots in action.
    .

We believe the path forward is through the cultivation of learner-centered ecosystems — adaptive, networked structures that offer a transformed way of organizing, supporting, and credentialing community-wide learning. These ecosystems break down barriers between schools, communities, and industries, creating flexible, real-world learning experiences that tap into the full range of opportunities a community has to offer.

Last year, we announced our Learner-Centered Ecosystem Lab, a collaborative effort to create a community of practice consisting of twelve diverse sites across the country — from the streets of Brooklyn to the mountains of Ojai — that are demonstrating or piloting ecosystemic approaches. Since then, we’ve been gathering together, learning from one another, and facing the challenges and opportunities of trying to transform public education. And while there is still much more work to be done, we’ve begun to observe a deeper pattern language — one that aligns with our ten-point Ecosystem Readiness Framework, and one that, we hope, can help all communities start to think more practically and creatively about how to transform their own systems of learning.

So while it’s still early, we suspect that the way to establish a healthy learner-centered ecosystem is by paying close attention to the following ten conditions:

 

 

The Memory Paradox: Why Our Brains Need Knowledge in an Age of AI — from papers.ssrn.com by Barbara Oakley, Michael Johnston, Kenzen Chen, Eulho Jung, and Terrence Sejnowski; via George Siemens

Abstract
In an era of generative AI and ubiquitous digital tools, human memory faces a paradox: the more we offload knowledge to external aids, the less we exercise and develop our own cognitive capacities.
This chapter offers the first neuroscience-based explanation for the observed reversal of the Flynn Effect—the recent decline in IQ scores in developed countries—linking this downturn to shifts in educational practices and the rise of cognitive offloading via AI and digital tools. Drawing on insights from neuroscience, cognitive psychology, and learning theory, we explain how underuse of the brain’s declarative and procedural memory systems undermines reasoning, impedes learning, and diminishes productivity. We critique contemporary pedagogical models that downplay memorization and basic knowledge, showing how these trends erode long-term fluency and mental flexibility. Finally, we outline policy implications for education, workforce development, and the responsible integration of AI, advocating strategies that harness technology as a complement to – rather than a replacement for – robust human knowledge.

Keywords
cognitive offloading, memory, neuroscience of learning, declarative memory, procedural memory, generative AI, Flynn Effect, education reform, schemata, digital tools, cognitive load, cognitive architecture, reinforcement learning, basal ganglia, working memory, retrieval practice, schema theory, manifolds

 

“The AI-enhanced learning ecosystem” [Jennings] + other items re: AI in our learning ecosystems

The AI-enhanced learning ecosystem: A case study in collaborative innovation — from chieflearningofficer.com by Kevin Jennings
How artificial intelligence can serve as a tool and collaborative partner in reimagining content development and management.

Learning and development professionals face unprecedented challenges in today’s rapidly evolving business landscape. According to LinkedIn’s 2025 Workplace Learning Report, 67 percent of L&D professionals report being “maxed out” on capacity, while 66 percent have experienced budget reductions in the past year.

Despite these constraints, 87 percent agree their organizations need to develop employees faster to keep pace with business demands. These statistics paint a clear picture of the pressure L&D teams face: do more, with less, faster.

This article explores how one L&D leader’s strategic partnership with artificial intelligence transformed these persistent challenges into opportunities, creating a responsive learning ecosystem that addresses the modern demands of rapid product evolution and diverse audience needs. With 71 percent of L&D professionals now identifying AI as a high or very high priority for their learning strategy, this case study demonstrates how AI can serve not merely as a tool but as a collaborative partner in reimagining content development and management.
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How we use GenAI and AR to improve students’ design skills — from timeshighereducation.com by Antonio Juarez, Lesly Pliego and Jordi Rábago who are professors of architecture at Monterrey Institute of Technology in Mexico; Tomas Pachajoa is a professor of architecture at the El Bosque University in Colombia; & Carlos Hinrichsen and Marietta Castro are educators at San Sebastián University in Chile.
Guidance on using generative AI and augmented reality to enhance student creativity, spatial awareness and interdisciplinary collaboration

Blend traditional skills development with AI use
For subjects that require students to develop drawing and modelling skills, have students create initial design sketches or models manually to ensure they practise these skills. Then, introduce GenAI tools such as Midjourney, Leonardo AI and ChatGPT to help students explore new ideas based on their original concepts. Using AI at this stage broadens their creative horizons and introduces innovative perspectives, which are crucial in a rapidly evolving creative industry.

Provide step-by-step tutorials, including both written guides and video demonstrations, to illustrate how initial sketches can be effectively translated into AI-generated concepts. Offer example prompts to demonstrate diverse design possibilities and help students build confidence using GenAI.

Integrating generative AI and AR consistently enhanced student engagement, creativity and spatial understanding on our course. 


How Texas is Preparing Higher Education for AI — from the74million.org by Kate McGee
TX colleges are thinking about how to prepare students for a changing workforce and an already overburdened faculty for new challenges in classrooms.

“It doesn’t matter if you enter the health industry, banking, oil and gas, or national security enterprises like we have here in San Antonio,” Eighmy told The Texas Tribune. “Everybody’s asking for competency around AI.”

It’s one of the reasons the public university, which serves 34,000 students, announced earlier this year that it is creating a new college dedicated to AI, cyber security, computing and data science. The new college, which is still in the planning phase, would be one of the first of its kind in the country. UTSA wants to launch the new college by fall 2025.

But many state higher education leaders are thinking beyond that. As AI becomes a part of everyday life in new, unpredictable ways, universities across Texas and the country are also starting to consider how to ensure faculty are keeping up with the new technology and students are ready to use it when they enter the workforce.


In the Room Where It Happens: Generative AI Policy Creation in Higher Education — from er.educause.edu by Esther Brandon, Lance Eaton, Dana Gavin, and Allison Papini

To develop a robust policy for generative artificial intelligence use in higher education, institutional leaders must first create “a room” where diverse perspectives are welcome and included in the process.


Q&A: Artificial Intelligence in Education and What Lies Ahead — from usnews.com by Sarah Wood
Research indicates that AI is becoming an essential skill to learn for students to succeed in the workplace.

Q: How do you expect to see AI embraced more in the future in college and the workplace?
I do believe it’s going to become a permanent fixture for multiple reasons. I think the national security imperative associated with AI as a result of competing against other nations is going to drive a lot of energy and support for AI education. We also see shifts across every field and discipline regarding the usage of AI beyond college. We see this in a broad array of fields, including health care and the field of law. I think it’s here to stay and I think that means we’re going to see AI literacy being taught at most colleges and universities, and more faculty leveraging AI to help improve the quality of their instruction. I feel like we’re just at the beginning of a transition. In fact, I often describe our current moment as the ‘Ask Jeeves’ phase of the growth of AI. There’s a lot of change still ahead of us. AI, for better or worse, it’s here to stay.




AI-Generated Podcasts Outperform Textbooks in Landmark Education Study — form linkedin.com by David Borish

A new study from Drexel University and Google has demonstrated that AI-generated educational podcasts can significantly enhance both student engagement and learning outcomes compared to traditional textbooks. The research, involving 180 college students across the United States, represents one of the first systematic investigations into how artificial intelligence can transform educational content delivery in real-time.


What can we do about generative AI in our teaching?  — from linkedin.com by Kristina Peterson

So what can we do?

  • Interrogate the Process: We can ask ourselves if we I built in enough checkpoints. Steps that can’t be faked. Things like quick writes, question floods, in-person feedback, revision logs.
  • Reframe AI: We can let students use AI as a partner. We can show them how to prompt better, revise harder, and build from it rather than submit it. Show them the difference between using a tool and being used by one.
  • Design Assignments for Curiosity, Not Compliance: Even the best of our assignments need to adapt. Mine needs more checkpoints, more reflective questions along the way, more explanation of why my students made the choices they did.

Teachers Are Not OK — from 404media.co by Jason Koebler

The response from teachers and university professors was overwhelming. In my entire career, I’ve rarely gotten so many email responses to a single article, and I have never gotten so many thoughtful and comprehensive responses.

One thing is clear: teachers are not OK.

In addition, universities are contracting with companies like Microsoft, Adobe, and Google for digital services, and those companies are constantly pushing their AI tools. So a student might hear “don’t use generative AI” from a prof but then log on to the university’s Microsoft suite, which then suggests using Copilot to sum up readings or help draft writing. It’s inconsistent and confusing.

I am sick to my stomach as I write this because I’ve spent 20 years developing a pedagogy that’s about wrestling with big ideas through writing and discussion, and that whole project has been evaporated by for-profit corporations who built their systems on stolen work. It’s demoralizing.

 

The 2025 Global Skills Report— from coursera.org
Discover in-demand skills and credentials trends across 100+ countries and six regions to deliver impactful industry-aligned learning programs.

GenAI adoption fuels global skill demands
In 2023, early adopters flocked to GenAI, with approximately one person per minute enrolling in a GenAI course on Coursera —a rate that rose to eight per minute in 2024.  Since then, GenAI has continued to see exceptional growth, with global enrollment in GenAI courses surging 195% year-over-year—maintaining its position as one of the most rapidly growing skill domains on our platform. To date, Coursera has recorded over 8 million GenAI enrollments, with 12 learners per minute signing up for GenAI content in 2025 across our catalog of nearly 700 GenAI courses.

Driving this surge, 94% of employers say they’re likely to hire candidates with GenAI credentials, while 75% prefer hiring less-experienced candidates with GenAI skills over more experienced ones without these capabilities.8 Demand for roles such as AI and Machine Learning Specialists is projected to grow by up to 40% in the next four years.9 Mastering AI fundamentals—from prompt engineering to large language model (LLM) applications—is essential to remaining competitive in today’s rapidly evolving economy.

Countries leading our new AI Maturity Index— which highlights regions best equipped to harness AI innovation and translate skills into real-world applications—include global frontrunners such as Singapore, Switzerland, and the United States.

Insights in action

Businesses
Integrate role-specific GenAI modules into employee development programs, enabling teams to leverage AI for efficiency and innovation.

Governments
Scale GenAI literacy initiatives—especially in emerging economies—to address talent shortages and foster human-machine capabilities needed to future-proof digital jobs.

Higher education
Embed credit-eligible GenAI learning into curricula, ensuring graduates enter the workforce job-ready.

Learners
Focus on GenAI courses offering real-world projects (e.g., prompt engineering) that help build skills for in-demand roles.

 
 


Also relevant/see:


Report: 93% of Students Believe Gen AI Training Belongs in Degree Programs — from campustechnology.com by Rhea Kelly

The vast majority of today’s college students — 93% — believe generative AI training should be included in degree programs, according to a recent Coursera report. What’s more, 86% of students consider gen AI the most crucial technical skill for career preparation, prioritizing it above in-demand skills such as data strategy and software development. And 94% agree that microcredentials help build the essential skills they need to achieve career success.

For its Microcredentials Impact Report 2025, Coursera surveyed more than 1,200 learners and 1,000 employers around the globe to better understand the demand for microcredentials and their impact on workforce readiness and hiring trends.


1 in 4 employers say they’ll eliminate degree requirements by year’s end — from hrdive.com by Carolyn Crist
Companies that recently removed degree requirements reported a surge in applications, a more diverse applicant pool and the ability to offer lower salaries.

A quarter of employers surveyed said they will remove bachelor’s degree requirements for some roles by the end of 2025, according to a May 20 report from Resume Templates.

In addition, 7 in 10 hiring managers said their company looks at relevant experience over a bachelor’s degree while making hiring decisions.

In the survey of 1,000 hiring managers, 84% of companies that recently removed degree requirements said it has been a successful move. Companies without degree requirements also reported a surge in applications, a more diverse applicant pool and the ability to offer lower salaries.


Why AI literacy is now a core competency in education — from weforum.org by Tanya Milberg

  • Education systems must go beyond digital literacy and embrace AI literacy as a core educational priority.
  • A new AI Literacy Framework (AILit) aims to empower learners to navigate an AI-integrated world with confidence and purpose.
  • Here’s what you need to know about the AILit Framework – and how to get involved in making it a success.

Also from Allison Salisbury, see:

 

How To Get Hired During the AI Apocalypse — from kathleendelaski.substack.com by Kathleen deLaski
And other discussions to have with your kids on the way to college graduation

A less temporary, more existential threat to the four year degree: AI could hollow out the entry level job market for knowledge workers (i.e. new college grads). And if 56% of families were saying college “wasn’t worth it” in 2023,(WSJ), what will that number look like in 2026 or beyond? The one of my kids who went to college ended up working in a bike shop for a year-ish after graduation. No regrets, but it came as a shock to them that they weren’t more employable with their neuroscience degree.

A colleague provided a great example: Her son, newly graduated, went for a job interview as an entry level writer last month and he was asked, as a test, to produce a story with AI and then use that story to write a better one by himself. He would presumably be judged on his ability to prompt AI and then improve upon its product. Is that learning how to DO? I think so. It’s using AI tools to accomplish a workplace task.


Also relevant in terms of the job search, see the following gifted article:

‘We Are the Most Rejected Generation’ — from nytimes.com by David Brooks; gifted article
David talks admissions rates for selective colleges, ultra-hard to get summer internships, a tough entry into student clubs, and the job market.

Things get even worse when students leave school and enter the job market. They enter what I’ve come to think of as the seventh circle of Indeed hell. Applying for jobs online is easy, so you have millions of people sending hundreds of applications each into the great miasma of the internet, and God knows which impersonal algorithm is reading them. I keep hearing and reading stories about young people who applied to 400 jobs and got rejected by all of them.

It seems we’ve created a vast multilayered system that evaluates the worth of millions of young adults and, most of the time, tells them they are not up to snuff.

Many administrators and faculty members I’ve spoken to are mystified that students would create such an unforgiving set of status competitions. But the world of competitive exclusion is the world they know, so of course they are going to replicate it. 

And in this column I’m not even trying to cover the rejections experienced by the 94 percent of American students who don’t go to elite schools and don’t apply for internships at Goldman Sachs. By middle school, the system has told them that because they don’t do well on academic tests, they are not smart, not winners. That’s among the most brutal rejections our society has to offer.


Fiverr CEO explains alarming message to workers about AI — from iblnews.org
Fiverr CEO Micha Kaufman recently warned his employees about the impact of artificial intelligence on their jobs.

The Great Career Reinvention, and How Workers Can Keep Up — from workshift.org by Michael Rosenbaum

A wide range of roles can or will quickly be replaced with AI, including inside sales representatives, customer service representatives, junior lawyers, junior accountants, and physicians whose focus is diagnosis.


Behind the Curtain: A white-collar bloodbath — from axios.com by Jim VandeHei and Mike Allen

Dario Amodei — CEO of Anthropic, one of the world’s most powerful creators of artificial intelligence — has a blunt, scary warning for the U.S. government and all of us:

  • AI could wipe out half of all entry-level white-collar jobs — and spike unemployment to 10-20% in the next one to five years, Amodei told us in an interview from his San Francisco office.
  • Amodei said AI companies and government need to stop “sugar-coating” what’s coming: the possible mass elimination of jobs across technology, finance, law, consulting and other white-collar professions, especially entry-level gigs.

Why it matters: Amodei, 42, who’s building the very technology he predicts could reorder society overnight, said he’s speaking out in hopes of jarring government and fellow AI companies into preparing — and protecting — the nation.

 
© 2025 | Daniel Christian