Addendum:

AI Budgets in Education Show No Sign of Decline — from campustechnology.com by Rhea Kelly

Key Takeaways

  • Education AI budgets are holding steady or increasing: Wasabi found that 98% of education organizations expect AI infrastructure budgets to increase or remain steady, with 46% planning increases.
  • Storage costs are the top AI implementation challenge: Half of education respondents cited data storage issues, including storage and access costs, as the No. 1 challenge for AI projects.
  • Cloud security and ROI remain pressure points: Only 47% feel confident keeping data unaltered and operational after a cyberattack, 44% lost access to public cloud data after an attack, and 37% of AI projects currently show positive ROI.
 

What AI-Enabled Education Actually Looks Like When It’s Working for Workforce Students — from gettingsmart.com by Stephen Griffin

Key Points

  • Institutions can use AI to make skills, pathways, and job outcomes visible to students and employers in ways traditional transcripts cannot.
  • Academic affairs, workforce development, career services, and employers need a shared definition of readiness and competency before tools can deliver meaningful value.

The second is portable competency records. Learning and employment records — AI-enabled documentation of what a student knows and can do, expressed in language employers recognize — are the infrastructure that makes credentials legible across the education-to-employment continuum. When a student can show an employer not just “completed Supply Chain Management 101” but “demonstrated proficiency in inventory optimization, route planning, and logistics software at the industry-recognized level,” the credential stops being abstract. It becomes evidence. Building these records requires investment in tools, yes — but more importantly, it requires faculty, workforce development staff, and employer partners to agree on what competency actually looks like before the technology is ever purchased.


 

 

Workplace Readiness: Can Higher Education Develop AI-Ready Students? — from learningguild.com by Eddie Lin and Roshan Bharwaney

For higher education to remain relevant, curricula must evolve. Here are some overarching recommendations for directions in higher education to bridge the skills gaps between universities and workplaces:

  • AI ethics and safety: Prepare students to navigate issues of fairness, bias, privacy, and societal impact.
  • Tackling complex questions: Emphasize open-ended challenges that blend structured and unstructured skills and reduce reliance on standardized tests and repetitive drills.
  • Critical thinking: Develop new assessments for judgment, creativity, and metacognition—essential to supervise AI outputs.
  • Human-AI synergy: Embed AI fluency across all disciplines, encouraging students to find the niches where human value is maximized.
  • Industry connection: Maintain close industry partnerships and collaborations including open innovation opportunities and collective intelligence approaches (Bharwaney & Sleeva, 2024).

Experiential learning and communities of practice are central to this vision. Internships, simulations, and cross-disciplinary projects can help students practice human-AI collaboration, resilience, and decision-making in environments that mirror the workplace’s ambiguity and complexity.

Universities that condemn the use of AI by students risk isolating themselves from the realities of today’s workplace, where interns and new hires are expected to be or quickly become adept at using AI for routine tasks and complex projects. 

 

Can colleges still deliver in the age of AI? One Ivy League school is investing $30 million to improve career outcomes — from cnbc.com by Jessica Dickler

Key Points

  • College students are increasingly worried about what an AI-driven jobs apocalypse could mean for their employment prospects.
  • To that end, many colleges and universities are racing to recalibrate.
  • Even at nation’s most elite schools, the focus is shifting to career readiness.
 

Autistic students who make it through college face a bigger challenge: getting jobs — from hechingerreport.org by Kelly Field
Colleges now offer career readiness classes and one-on-one coaching for students with autism

Recognizing these strengths, some major companies — including tech giants SAP and Microsoft, and financial institutions Wells Fargo and J.P. Morgan Chase — began building neurodiverse hiring programs roughly a decade ago.

Those efforts have yielded significant revenue for companies, some of them say, with EY, one of the big four accounting firms, reporting in 2023 that its neurodiverse employees have generated nearly $1 billion in business value. A study by J.P. Morgan Chase found that its autistic employees were much more productive than its neurotypical ones.

Consumer finance company Synchrony, which plans to hire 15 neurodivergent interns this year, says the program has changed how teams work across the company.


Also on a somewhat-related note and also from Kelly Field at The Hechinger Report, see:

 

Connecting the Tangled Systems of Reentry Training and Employment — from workshift.com by Matthew Arrojas; via Paul Fain

After release, formerly incarcerated people must navigate a maze of government systems, workforce programs, and parole requirements. They are rarely prepared to do this, and as a result, nearly half (45%) report no earnings within the first year of their release, according to research from the Brookings Institution.

The Big Idea: Reducing those barriers has become an increasing focus for a number of philanthropies and colleges. It’s also a growing labor market imperative.

There’s also an incentive for many states to help this population of potential workers land jobs. According to the U.S. Chamber of Commerce, formerly incarcerated individuals who are unable to maintain employment experience a recidivism rate of 52% over three years, while those who are employed for one year post-release experienced a recidivism rate of just 16%. 

 

Why universities must become flexible lifelong partners, not one-time providers — from timeshighereducation.com by Sankar Sivarajah
As careers become increasingly non-linear and shaped by rapid change, universities must evolve beyond traditional degree provision, says Sankar Sivarajah. Here, he outlines strategies

From programmes to learning ecosystems
These pressures point towards a broader redefinition of higher education. Rather than viewing education as a one-time experience culminating in a degree, universities increasingly need to see themselves as partners in professional development across an entire career.

This means moving from a model centred on programmes to one focused on learning ecosystems that allow individuals to enter, leave and re-engage with higher education as their needs evolve.

Business schools may be particularly well placed to lead this shift because of their close engagement with employers and their long tradition of educating professionals at different stages of their careers.

But success will depend on more than introducing new modules or certificates. Universities must confront a fundamental question. Are the systems, structures and cultures that define higher education capable of supporting genuinely flexible learning?

The sector has already embraced the language of lifelong learning – the next step is ensuring that universities themselves are built to deliver it.


From DSC:
Long-time readers of this blog have seen this graphic of mine posted over the last 12+ years:
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Also relevant/see:

What if the undergraduate journey were a four-year internship? — from timeshighereducation.com by Michelle Seref
Treating work placements and co-curricular programmes as optional or supplementary misses deeper questions about whether traditional degrees prepare students for careers. Michelle Seref explains

Attending workshops or polishing a résumé in their final semester does not make students career-ready. They need to practise how to work – how to collaborate, navigate ambiguity, manage projects and apply knowledge in context – throughout their academic experience. The reality is that career readiness is not a co-curricular programme; it is an essential part of an integrated curriculum.

To be clear, employers do not expect classrooms to become training centres. What they are asking for – implicitly and explicitly – is graduates who can function in complex environments from day one. That means graduates who can work in teams, communicate professionally with stakeholders, adapt when plans change, apply theory to real constraints and learn continuously on the job.

These capabilities do not develop through passive learning. But experiential learning is often misunderstood as a single, high-impact activity: an internship, a capstone project or study abroad. In reality, its power comes from repetition and progression. One experience introduces exposure. A sequence of experiences builds competence.

We are proposing a paradigm shift: repositioning the undergraduate journey as a four-year professional internship rather than a continuation of the K-12 classroom environment. 

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From DSC:

The problem with this innovative idea is that faculty often are not out in the “real world.” The best chance higher ed has to deliver on this idea is via the adjunct faculty members out there. Often, they are the ones practicing what they are teaching. They are constantly pulse-checking — and actively involved with — their industries and have more up-to-date, practical knowledge.

But this is a problem for traditional institutions of higher education, which have treated their adjunct faculty members poorly through the years. Adjunct faculty members hardly make minimum wage, have no benefits, no retirement plans, etc. — plus they have little to no say in faculty senates. 

Organizational change would be a requirement.

 

I Was a University AI Czar. I’m Not Equipped to Teach in the Age of AI. — from jgellers.substack.com by Josh Gellers, PhD

The reason that I claim I am not well-suited to thrive as an instructor in the age of AI is because both AI Enthusiasts and AI Resisters put a lot of thought and energy into completely redesigning their classes in response to AI. This is the one takeaway that I don’t think the Exhausted Majority has fully accepted yet—to excel as a teacher in this AI era, you need to totally revise how you teach and how you assess what students learn in your classes.

I can say this much—whatever solution our industry comes up with, it’s likely to emerge from teaching and learning centers. Contrary to what Paul Schofield  wrote in the Chronicle of Higher Education, pedagogy experts are the best hope we have to equip today’s faculty with the tools required to succeed in this uncertain educational environment. As I always tell my students, “I was trained for 7 years to become a researcher and 2 days to become a teacher.” The idea that only disciplinary experts know how to teach and have nothing to learn from so-called “nonscholars” is so laughable that one has to wonder whether an AI agent jokingly wrote that sad opinion piece to troll the whole academe.

Also from Dr. Gellers, see:

The Worst AI Policy in Higher Ed
How Berkeley Law Boalt-ed From Expertise in Favor of Abstinence

Last week, one of the top law schools in the United States, the University of California, Berkeley School of Law, released its final policy on artificial intelligence, effective summer 2026. In the span of a breezy 1.5 pages, the school outlined the challenge AI poses to legal education and how it plans to address this problem. Despite these intentions, this AI policy is, in my estimation, the worst AI policy in higher education I have seen.


From AI Tutors to AI Study Mates— from drphilippahardman.substack.com by Dr Philippa Hardman
New research reveals how AI can enable real learning — not just productivity gains


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The point isn’t that AI is inherently bad for learning — it’s that the meta-analyses showing that LLMs improve assignment and performance scores are measuring the wrong thing. They’re measuring performance with the AI present, not learning that persists once it’s gone.

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From DSC:
Notice that when an AI-based learning system can remember what you’ve worked on and how you are doing — where you are struggling or doing well — it can have a positive impact on your longer-term learning. That, to me, is where long-term based learner profiles come in.

Later in the article, Dr. Hardman points out that “if we want to deliver AI tooling which supports substantive learning, we need to intentionally create a new category of AI tool for ‘learning at work’ which prioritises learning and development over productivity.” While I agree with that, I do wonder if businesses will care, so long as the work gets done and gets done well. But this calls into mind the word “experience” — something that traditionally has been hard fought to get in the corporate world. But the corporate realm often doesn’t like to pay for experience (beyond key AI-based jobs) when they perceive it’s getting too expensive. Ask all those 50 and over who had or have a target on their backs.

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Job Scams Are Everywhere. Here’s How to Spot Them Before It’s Too Late. — from builtin.com by Alex Chepovoi
As people face increasing economic pressure, scammers are using fake job ads to harvest your data. Our expert explains the warning signs.

Summary: Scammers are flooding hiring platforms like LinkedIn with AI-generated fake remote jobs to steal data. Nearly 80 percent of these scams target low-skill roles, using inflated pay and vague requirements as bait. Platforms should adopt AI-driven detection to protect vulnerable job seekers.

Market desperation has become a growth engine for fraud. People invest their hope, time and personal data into an opportunity that doesn’t exist and could use their information for financial gains, identity theft or espionage. 

Until hiring platforms take greater responsibility for vetting the roles they host, the burden of staying safe falls on job seekers. Once you understand the motives and patterns scammers rely on, however, spotting them becomes much easier.

But a combination of vague descriptions, inflated pay, minimal requirements and subtle urgency is exactly what makes the system so effective.

 

LinkedIn Grad’s Guide 2026: Starting your career in the AI era — from linkedin.com by Gianna Prudente
To help you head off in the right direction, we’ve identified where those starting their careers are finding opportunity, based on data from millions of LinkedIn member profiles.

While all of this is happening, colleges are still catching up. Many students are graduating without having spent much time learning how AI actually fits into day-to-day work — even as employers seek out those exact skills.

“Colleges are moving into an era of, we’ll let the faculty decide, which leads to a very uneven experience for students because some faculty are really into AI and other faculty are not,” says Jeff Selingo, a higher education strategist. “Employers are the same; they don’t really know how to act around early careers.”

Taken together, new grads are entering a uniquely challenging environment: fewer traditional entry points, slower turnover and a workplace that’s evolving faster than the systems preparing people for it.

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I knew my writing students were using AI. Their confessions led to a powerful teaching moment — from theguardian.com by Micah Nathan
The problem wasn’t just the perfectly polished, yet mediocre prose. It’s what’s lost when we surrender the struggle to translate thought into words

For a few moments, all was quiet except the classroom’s ticking radiators. Then, a teary-eyed confession: one of the ostensible authors said she only used AI because she was scared of looking stupid, of being criticized for bad writing. She said she loved writing stories and hated having used AI. But she couldn’t stop herself, recounting a sequence similar to an addict’s descent: at first she fed her story into AI for a grammar check, it suggested line edits and she accepted, then it asked if she wanted structural edits, then it offered to rewrite the entire piece.

The other would-be author admitted he had never written a short story before and he had an idea but didn’t know where to start. I asked him why he didn’t reach out to me for help. He shrugged.

One of the other students raised her hand, saying she didn’t understand why it was bad for AI to write stories as long as the stories are based on their ideas. More students spoke: one wanted to know how using AI was any different from using a human editor. Another wanted me to answer why, at a university that launched one of the world’s first AI research programs in 1959, were we even having this debate? Isn’t AI meant to make everyone’s life easier? Less stressful? Isn’t the point of AI to free humans from the tedium of rote tasks?

The conversation that followed their confessions was one of the most productive teaching moments of my eight years at MIT. Writing, I told them, isn’t supposed to be easy, and of course it can be tedious but that doesn’t make it rote. Writing isn’t just the production of sentences – it’s the training of endurance by way of sustained attention. It’s a way of learning what one thinks by attempting to say it. 


This $10K AI School Promises to Future-Proof Your Career — from builtin.com by Matthew Urwin
Khan Academy, TED and ETS are starting a new program to equip students and professionals with the skills to thrive in an increasingly AI-driven economy. Here’s what you need to know.

Summary: The Khan TED Institute is a higher-education program that will teach students and workers how to use AI through interactive learning. The program’s AI-centric curriculum is an unproven approach, though, casting doubt on whether it will actually improve learning outcomes and career prospects.


 

Let AI Interview You — from wondertools.substack.com by Jeremy Caplan & Jay Dixit
A smarter way to get past the blank page

There’s nothing wrong with using AI to get answers to your questions. But there’s another mode of interacting with AI that many people never consider — one I find much more useful for my creative process.

Here’s what I do instead: I flip the script and let the AI ask the questions. Instead of prompting AI, I get the AI to prompt me.

 

6 Reasons Universities Are Building Media Labs Now — from edtechmagazine.com by Brad Grimes
Digital production centers help institutions close the gap between academic training and professional practice.

Higher education is undergoing a significant transformation in how it prepares the next generation of media professionals. Across the country, universities are investing in state-of-the-art media labs — facilities built not around traditional classroom instruction, but around the tools, workflows and collaborative environments that define today’s professional production landscape. These spaces represent a fundamental rethinking of what it means to train students for careers in film, animation, gaming and digital storytelling.

 

The TalentLMS 2026 Annual L&D Benchmark Report — from talentlms.com
From year-over-year training benchmarks to learner–leader gaps, see the data that defines the new era of learning. To turn insight into action, the report lays out 10 evidence-backed interventions to hardwire development. Plus, lift the lid on Learning Debt: What it is and how to spot it.

Executive summary
The skills economy is being rewritten in real time. AI is reshaping what people need to know, do, and deliver, faster than organizational structures can adapt. The result is a workplace caught between acceleration and inertia. Companies are racing to reskill for an AI-driven future while relying on structures built for yesterday’s world.

This TalentLMS 2026 L&D Benchmark Report captures that inflection point. Based on data collected through 2025, and compared with earlier findings from 2022 to 2024, it explores how learning is evolving and what’s holding it back.

Our research integrates two vantage points: HR leaders overseeing learning initiatives and employees receiving formal training. Together, they offer a dual perspective on how learning is managed and how it’s experienced.

The analysis also draws on insights from external research and leading L&D practitioners, anchoring the report in both evidence and practice.

Combined, the findings point to a structural fault line: Learning is expanding in scope but contracting in space. Organizations are multiplying programs, tools, and ambitions, yet the conditions for learning — time, focus, and cognitive bandwidth — keep shrinking.

The data from this report underscores this critical conflict: According to half of the surveyed employees and learning leaders, high workloads leave little room for training, even when it’s needed.

Employees work inside a permanent sprint, where attention is fragmented and reflection is sidelined. The space for learning is collapsing under the weight of doing. Sixty-five percent of employees say performance expectations have risen this year, yet lack of time remains the biggest barrier to learning.

The numbers confirm what employees and learning leaders both feel: Technology can advance overnight. But people and cultures can’t.

 

FutureFit AI Announces Strategic Investment to Help Governments and Industries Navigate AI’s Impact on People & Jobs — from prnewswire.com; via Ryan Craig

NEW YORKApril 13, 2026 /PRNewswire/ — FutureFit AI, a global leader in AI-powered workforce development technology, today announced an investment from Achieve Partners, led by investor and author Ryan Craig,  to accelerate its mission of helping more people navigate to better jobs faster and cheaper at scale.

“For too long, the U.S. workforce system has relied on disparate and disconnected systems to try to bridge the gap between the skills workers bring to the table, and the jobs available in a fast-changing labor market. In the age of AI, the need for a better approach has only become more urgent,” said Ryan Craig, co-founder and managing director of Achieve and author of Apprentice NationA New U, and College Disrupted. “FutureFit AI is solving that problem by helping workforce organizations create clearer paths to career opportunity for workers and solve pressing talent gaps that hinder economic growth. Their work around the country has already demonstrated the ability to help more people get good jobs faster.”

“A mission that began with a simple question of ‘What if everyone had a GPS for their career’ has turned into years of working closely with government and industry leaders to respond to – and solve for – the impacts of digital transformation and AI on jobs and people,” added Ekhtiari. “Our partnership with Achieve will accelerate our work to build and scale the missing workforce transition infrastructure that our country and the world so badly need at this moment.”

 

AI for Your Next Career Move — from wondertools.substack.com by Jeremy Caplan
Free tools to explore, research, and interview better

AI tools can serve as patient assistants when you’re looking for a job. Use them to organize your search. Or to challenge your assumptions about potential jobs. They can also help you present your strengths more persuasively. When you’re changing fields, or trying to move up, AI can help you stand out.

1. Visualize Your Career Options
Try: Google’s
Career Dreamer

What it is: A free tool for exploring jobs adjacent to yours. See a map of professional fields related to your interests.

How to use it: Start by typing in a current or previous role. Or name a job that interests you. Use up to five words. You can also name a specific organization or industry, if you have one in mind.

Career Dreamer asks what work activities interest you, then maps related career paths. Pick one at a time to explore.

You can then browse actual job openings. Refine the search based on location, company size, or other factors you care about.

 
© 2025 | Daniel Christian