Why Students Aren’t All In on AI—And What They Want From Colleges— from insidehighered.com by Colleen Flaherty New Student Voice data reveal students are embracing AI as a learning tool while worrying about dependence, career disruption and inconsistent institutional responses.
Read on for six takeaways from the survey and additional insights—including how institutions can start to close the gap between students’ optimism about AI as a learning tool and their faith in their colleges’ ability to help them navigate change.
Takeaway 1: More students are using AI than ever for coursework, while a significant share—20 percent—remain resisters.
Takeaway 2: “Worried about dependence” is the most common student stance on AI.
Takeaway 3: A majority of all students expect AI to somewhat (39 percent) or very (16 percent) negatively impact their career prospects.
Takeaway 4: Just one in 10 students says that their institution is handling AI’s rise very well, in a thoughtful and proactive way.
The National Microschooling Center just published its latest report, the American Microschools 2026 Sector Analysis, it’s most ambitious yet.
This report comprises the most thorough research published to date on microschools in America, examining 1,000 microschools located in all 50 states, the District of Columbia and Puerto Rico. Most are currently operating, with prelaunch microschools as well as those which have closed their doors also included.
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This 2026 edition of the annual American Microschools Sector Analysis series by the National Microschooling Center includes questions on a number of new topics, including ways microschools are impacted by different regulatory and policy stipulations, specifics of educational, business and operational aspects within the microschooling sector. Other questions revisit topics examined in previous studies, to illuminate trends over time and effects of growth and evolution on the ways microschools operate.
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.
Early data from the 2025-26 academic year shows historically deep tuition discounts getting even deeper at private nonprofit colleges, according to a study released Monday from the National Association of College and University Business Officers.
For first-time undergraduates, the tuition discount rate at these colleges is projected to reach 57.1% in the current academic year. That’s up from 54.5% from the year before, and the highest point in the past decade. For all undergraduates, the discount rate is poised to hit 51.3%, up from 50% last year and above the most recent peak at 50.8% in 2022-23.
However, revenue declines across the undergraduate body pose difficulties for tuition-dependent colleges. It “suggests that retention alone is not enough to eliminate financial strain at many tuition-dependent institutions,” NACUBO said in its report.
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.
We welcome back Sabastian Niles, President and Chief Legal Officer at Salesforce, to discuss his recent “Open Letter to Law Firms.” As the legal industry hits a critical inflection point, Sabastian argues that the era of “AI theater” and small-scale pilots is over.
The conversation dives deep into the Innovator’s Dilemma facing law firms, the shift toward agentic AI, and how firms must reimagine their business models to remain competitive. Sabastian highlights that legal professionals are uniquely positioned to lead the charge in trusted AI transformation, provided they embrace transparency, data integration, and shared efficiency gains with their clients.
Three Realities for the Modern Legal Firm To lead in this landscape, there are three realities every firm leader must understand:
Competition is intensifying: …
Client expectations will reshape the market: Clients are no longer asking whether firms use AI. Rather, they’re expecting to see the benefits of that transformation passed directly to them. They expect more for less but are not simply seeking lower costs – they want more insight, more speed, and more value for every dollar of their budget. And law firms, which operate at the center of data, ethics, and risk, have outsized influence over the structure and deployment of trusted AI across all industries. Some clients, like Salesforce, are even creating agentic tools to improve the law firm’s experience when working with clients. …
Unified client intelligence is at the heart of legal strategy: …
Are AI First Firms a Threat To Biglaw? — from legallydisrupted.com by Zach Abramowitz and Logan Brown Episode 49 features AI first law firm founder Logan Brown
Is Big Law about to become the Yellow Pages? Hey, I didn’t say it, but ex-Cooley lawyer turned AI first law firm Logan Brown did. The question is do I agree?
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Instead of the traditional billable hour, they charge flat fees like $100 for a contract review or $50 to ask a lawyer a quick question via chat. She’s already got over 40 attorneys on the platform. And in a departure from the traditional partnership track, she actually chose to raise venture capital so she could scale the firm like a tech company and tackle the access-to-justice gap.
From DSC: LOVE to hear anything and everything regarding efforts to address the access-to-justice gap here in the United States!!! Along these lines, also see:
“Legal services are out of reach for many people and small businesses, and the gap is widening,” Anthropic said in its announcement. “We’re working with the Free Law Project, Justice Technology Association and other legal aid and public service organizations to help make legal services more affordable and available.”
That makes this the first time that a leading AI company is explicitly naming access to justice as a foundational pillar, JTA says, with Anthropic positioning the initiative as “investing in the premise that AI should expand access to justice — making legal services more affordable and available.”
What AI hallucinations in law actually are
In a legal context, AI hallucinations are one of two things. They’re either citations to cases or statutes that don’t exist, or citations to real authorities for propositions those authorities don’t actually support.
The first kind is the one making headlines. A lawyer or pro se litigant uses a general-purpose chatbot like ChatGPT, Claude, Gemini, Copilot, or Grok to help draft a brief. The model, predicting the statistically likely next word, decides a citation belongs in a particular spot, and produces one. The reporter might be real. The volume number might fall within the right range. The Bluebook formatting is often better than what most associates produce. The case itself just doesn’t exist.
The second kind is older than AI. Lawyers have always occasionally cited a case for a proposition that the case doesn’t stand for. AI has made this kind of error easier to commit and easier to catch.
A dangerous mind — from by Jordan Furlong Generative AI is a tireless genius with no boundaries. Use it carelessly, and it can usurp your voice, overwrite your ideas, and steal your originality. Make sure you safeguard your capacity to think.
Don’t let the genius do the hard work for you. The more incisive and unique your own thinking — the more you battle and struggle and eventually succeed in getting your ideas and insights out — the more you can benefit from the AI’s complementary improvements. The great irony of Gen AI is that it actually makes your own cognitive processes your most valuable asset.
So safeguard your mind. Defend your right to think as only you can. And if you don’t want AI to replace you, then don’t send it a written invitation.
The pilot phase is over. After two years of experimentation for legal departments, 2026 will be the year AI moves from “interesting tool” to “operational infrastructure,” whether they’re ready or not. We surveyed predictions from Gartner, Forrester, McKinsey, and other leading legal tech analysts to identify where expert consensus is forming. The implications for AI governance, outside counsel relationships, and regulatory compliance are significant.
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.
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.
The biggest AI risk that L&D faces isn’t that it gets left behind: it’s that we build more — and flood the organisation with meh-quality content nobody needed in the first place.
In this post, I’ll make the case that:
The L&D job has just split in two — and most of us are still working on the wrong half.
There’s a new operating model coming for the role, and it’s already running inside a lot of the companies you’ve heard of.
The smartest critique of everything I’m about to argue comes from Ethan Mollick — and I think he’s half right.
The question we’ve been asking for the last two years — “how do I get faster at building?” — was the wrong one.
The real question is: can I look at fifteen AI-generated learning assets and decide which three are worth scaling — and put my name to that decision?
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.
Which Jobs Are Most at Risk From AI? New Anthropic Data Offers Clues.— from builtin.com by Matthew Urwin Anthropic set out in its latest study to predict how artificial intelligence could impact the labor market. Instead, its findings raise more questions than answers for tech workers as the U.S. government refuses to regulate the AI industry.
Summary:
In its latest labor market study, Anthropic found that artificial intelligence poses the greatest threat to software jobs, women and younger professionals. As the Trump administration takes a hands-off approach to AI, tech workers may be left to grapple with these findings on their own.
We introduce a new measure of AI displacement risk, observed exposure, that combines theoretical LLM capability and real-world usage data, weighting automated (rather than augmentative) and work-related uses more heavily
AI is far from reaching its theoretical capability: actual coverage remains a fraction of what’s feasible
Occupations with higher observed exposure are projected by the BLS to grow less through 2034
Workers in the most exposed professions are more likely to be older, female, more educated, and higher-paid
We find no systematic increase in unemployment for highly exposed workers since late 2022, though we find suggestive evidence that hiring of younger workers has slowed in exposed occupations
The headline number: About 60% of 18-to-22-year-olds are engaging in sports betting, a figure that climbs to two-thirds among college students specifically, according to an NCAA-commissioned study.
“It’s sort of a learned behavior for them at a very young age,” Clint Hangebrauck, the NCAA’s managing director of enterprise risk management, told us on the latest episode ofFuture U.“I do think this could be the next big public health crisis that we’re facing as a country and particularly within higher ed.”
College-age individuals are 3x more likely to develop problematic gambling behaviors than the general population. Gambling often co-exists with other behaviors now prevalent in colleges, such as sleeplessness, binge drinking, drug use, anxiety and depression.
Gambling among college students isn’t confined to athletes. Rather, it’s embedded across campus life, and with athletes often most visible in Division III, where oversight is lighter. Gambling often coexists with—and can exacerbate—other student challenges, from mental health struggles to substance use. If this is the next public health issue on campus, it’s arriving without the same level of attention.
From DSC: I don’t mean to be self-righteous here. But shame on the older adults who are promoting gambling in any fashion — marketing, advertising, sales, and/or whatever. It’s a cancer in our society, and it’s impacting our youth in a big way (and also older folks as well). I’m not a gambler, but I’m well acquainted with weakness. And the Bible confirms that we all are acquainted with weakness:
We all, like sheep, have gone astray, each of us has turned to our own way; and the Lord has laid on him the iniquity of us all.
The adults out there know it. We are well acquainted with our sins and shortcomings.
Parents want the best for their kids. They don’t want dangerous habits being formed in their children. “Coping skills” that are majorly busted, and can lead to incredibly negative events. And the parents don’t want these habits to be formed at colleges and universities across the nation.
I wish those involved with promoting gambling could be at the dinner tables, or in the bedrooms, or in the living rooms, or in the vehicles out there when a spouse finds out that the other spouse (or significant other) has gambled away a significant amount of the couple’s savings. They no longer have rainy-day funds. They can no longer pay their bills. They no longer have the college funds for their other kids. Emotions erupt, fights begin. Relationships are threatened — and divorces sometimes occur because of this issue/habit.
So if you are involved with promoting gambling, consider reading this article from Jeff Selingo…then go take a long look in the mirror.
From DSC: The types of postings/articles (such as the one below) make me ask, are we not shooting ourselves in the foot with AI and recent college graduates? If the bottom rungs continue to disappear, internships and apprenticeships can only go so far. There aren’t enough of them — especially valuable ones. So as this article points out, there will be threats to the long-term health of our talent pipelines unless we can take steps to thwart those impacts — and to do so fairly soon.
To me…vocational training and jobs are looking better all the time — i.e., plumbers, carpenters, electricians, mechanics, and more.
Can New Graduates Compete With AI? — from builtin.combyRichard Johnson The increasing adoption of AI automation is compressing early-career jobs. How should new graduates get a foothold in the economy now?
Summary: AI is hollowing out entry-level roles by automating routine tasks, eliminating a rung on the career ladder. New graduates face intense competition and a rising skill floor. While firms gain short-term productivity, they risk a long-term talent shortage by eliminating junior training grounds.
Conversations about AI have covered all grounds: hype, fear and slop. But while some roll their eyes at yet another automation headline, soon?to?be graduates are watching the labor market with a very different level of urgency. They’re entering a world where the old paradox of needing experience to get experience is colliding with a new reality: AI is absorbing the standardized, routine tasks that once defined entry?level work. The result isn’t just a shift in job descriptions or skill-requirements, but rather a structural reshaping of the career pipeline.
Entry-level workers face an outsized disruption to their long-term career trajectories. They have the least buffer to adapt given their lack of relevant job market experience and heightened financial pressure to secure a job quickly with the student-debt repayment periods for recent graduates looming.
Momentum early in one’s career matters, and the first job on a resume shapes future compensation bands and opportunities. It also serves as a signal for perceived specialization or, at minimum, interest. Losing that foothold has compounding effects to one’s career ladder.
Anthropic has launched the Anthropic Institute, a new research effort focused on the biggest societal challenges posed by more powerful AI systems.
The institute will study how advanced AI could affect the economy, the legal system, public safety, and broader social outcomes.
Anthropic co-founder Jack Clark will lead the institute in a new role as the company’s head of public benefit.
The new unit brings together Anthropic’s existing red-teaming, societal impacts, and economic research work, while adding new hires and new research areas.
2026 Survey of College and University Presidents — from insidehighered.com, Liaison, & Jenzabar Download and explore exclusive insights from the 2026 Survey of College and University Presidents to see how these campus leaders are responding to financial volatility, political interference, rapid advances in AI, and where they believe the biggest risks and opportunities lie as they look toward 2030.
In this year’s survey, presidents share perspectives on:
How presidents assess the second Trump administration’s impact on higher education
Which emerging or evolving educational models they plan to add or expand in the coming years
How effective they believe higher education has been in shaping national conversations arout AI
The issues presidents expect will have the greatest impact on higher education by 2030
