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.
. 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.
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.
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
Summary: Job seekers facing future panic should prioritize agility over information consumption. Build it by focusing on 30-day action experiments, reframing resumes around durable skills like problem-solving and embracing uncertainty through stretch applications and real-world feedback.
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The antidote is what I call AQ — the agility quotient — which is your capacity to face change, disappointment and uncertainty without losing your footing. Unlike IQ, which measures what you know, AQ measures how fast you adapt when the rules change. Right now, it’s the most important career asset you have. Here’s how to build it.
What Is Agility Quotient (AQ)? AQ is a measure of an individual’s capacity to adapt quickly when rules, industries or circumstances change. Unlike IQ, which focuses on existing knowledge, AQ emphasizes the ability to face uncertainty and disappointment without losing one’s footing, prioritizing action and iteration over exhaustive planning.
Characteristics of Strong Culture
Although each organization’s culture is unique, strong cultures share several common traits. They communicate openly, maintain trust across all levels, and reinforce their values through daily actions rather than slogans. Recognition is frequent and meaningful. Collaboration is encouraged over competition, and employees feel psychologically safe expressing ideas or concerns. These cultures evolve as the organization grows, ensuring alignment between stated values and lived behavior.
… How to Strengthen Culture
A thriving environment is built through everyday habits: transparent communication, active listening, constructive feedback, and ensuring employees have the resources to grow. Embedding values into hiring, onboarding, recognition, and decision-making reinforces culture at every level. Sustaining culture requires ongoing attention—listening regularly, adjusting to evolving needs, and ensuring leaders continue to model the behaviors the organization expects.
Across the divide: reimagining faculty-staff collaboration in higher education — from timeshighereducation.com by Saskia van de Gevel Academic units do best when they harness different viewpoints – from field scientists and curriculum designers to extension professionals – to drive innovation and relevance. Saskia van de Gevel offers proactive advice
Universities are not sustained by individual leaders or isolated units. They are sustained by teams of people who bring different kinds of expertise to a shared mission. When faculty and professional staff collaborate as genuine partners – aligned around outcomes, clear about roles and committed to mutual respect – institutions become more resilient, innovative and effective.
Also from timeshighereducation.com, see:
The five levels of learning designer support — from timeshighereducation.com by Daniel Searson Learning designers and academics may have different expectations when it comes to collaborating on course design. Here’s how a five-point scale can help
How employability teams can strengthen academic programmes — from timeshighereducation.com by Hanene Duprat Working like recruitment partners, rather than just career advisers, can help align teaching with industry needs, writes Hanene Duprat Excerpts:
Again, we don’t send them 200 CVs. We might send 20, but they’re meticulously shortlisted. The employer saves time, the student feels they are being taken seriously and trust builds quickly on both sides.
And because we work closely with employers, we learn something universities often struggle to find out early enough: what the market is asking for now.
What academics need to know: we can’t do this without you
If I could say one thing to academic colleagues anywhere, it’s that employability can’t sit next to the curriculum. It has to live with it.
The benefits of engaging third space practitioners in curriculum development — from timeshighereducation.com by Steve Briggs Third space practitioners are often overlooked in the curriculum development process, to everyone’s detriment. Here’s a look at the viewpoints they can offer and how to engage them better
I need to be honest with you. I’ve been running experiments this week with Claude Code and Opus 4.6, and we have reached the precipice in the collapse of time required to produce high-quality text-based ID outputs.
This includes performance consulting reports, learning needs analyses, action mapping, scripts, storyboards, facilitator guides, rubrics, and technical specs.
I just mapped the entire performance consulting process into a multimodal AI integration architecture (diagram image). Every phase. Entry and contracting. Performance analysis. Cause analysis. Solution design. Implementation. Evaluation. Thirty files. System specifications for each. The next step is to vet out each “skill” with an expert performance consultant.
Then I attempted a learning output: an 8-module course built with a cognitive scaffold that moves beyond content delivery to facilitate deliberate practice, meaning-making, and guided reflection within the learner’s own context.
AI adaptive learning can adapt learning in real-time. These tools have the potential to provide a more personalized learning experience, but only if used properly.
The California State University system uses ChatGPT Edu (OpenAI, 2025). Students use it for AI-assisted tutoring, study aids, and writing support. These resources provide 24/7 availability of subject-matter expertise tailored to students’ learning needs. It is not a replacement for professors. Rather, it extends the reach of mentorship by reducing access barriers.
However, we must proceed with intellectual humility and ethical responsibility. Even though AI can customize messages, it cannot replace the encouragement of a teacher or professor, or the social and emotional aspects of learning. It’s at the intersection of humanistic values and knowledge development that education must find its balance.
The Campus AI Crisis — by Jeffrey Selingo; via Ryan Craig Young graduates can’t find jobs. Colleges know they have to do something. But what?
Only now are colleges realizing that the implications of AI are much greater and are already outrunning their institutional ability to respond. As schools struggle to update their curricula and classroom policies, they also confront a deeper problem: the suddenly enormous gap between what they say a degree is for and what the labor market now demands.In that mismatch, students are left to absorb the risk. Alina McMahon and millions of other Gen-Zers like her are caught in a muddled in-between moment: colleges only just beginning to think about how to adapt and redefine their mission in the post-AI world, and a job market that’s changing much, much faster.
“Colleges and universities face an existential issue before them,” said Ryan Craig, author of Apprentice Nation and managing director of a firm that invests in new educational models. “They need to figure out how to integrate relevant, in-field, and hopefully paid work experience for every student, and hopefully multiple experiences before they graduate.”
Business leaders across the world are grappling with a reality that would have seemed like science fiction just a few decades ago: Artificial intelligence systems dubbed AI agents are becoming colleagues, not just tools. At many organizations, HR pros are already developing balanced and thoughtful machine-people workforces that meet business goals.
At Skillsoft, a global corporate learning company, Chief People Officer Ciara Harrington has spent the better part of three years leading digital transformation in real time. Through her front-row seat to CEO transitions, strategic pivots and the rapid acceleration of AI adoption, she’s developed a strong belief that organizations must be agile with people operations.
‘No role that’s not a tech role’ Under these modern conditions, she says, technology is becoming a common language in the workplace. “There is no role that’s not a tech role,” Harrington said during a recent discussion about the future of work. It’s a statement that gets at the heart of a shift many HR leaders are still coming to terms with.
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But a key question remains: Who will manage the AI agents, specifically, HR leaders or someone else?
The Online Education Marketplace Is Increasingly Competitive: …
Alternative Credentials Take Center Stage: …
AI Integration Lacks Strategic Coordination: …
Just 28% of faculty are considered fully prepared for online course design, and 45% for teaching. Alarmingly, only 28% of institutions report having fully developed academic continuity plans for future emergency pivots to online.
Cultural resistance remains strong. Many [Chief Online Learning Officers] COLOs say faculty and deans still believe in-person learning is “just better,” creating headwinds even for modest online growth. As one respondent at a four-year institution with a large online presence put it:
Supportive departments [that] see the value in online may have very different levels of responsiveness compared to academic departments [that] are begrudgingly online. There is definitely a growing belief that students “should” be on-ground and are only choosing online because it’s easy/ convenient. Never mind the very real and growing population of nontraditional learners who can only take online classes, and the very real and growing population of traditional-aged learners who prefer online classes; many faculty/deans take a paternalistic, “we know what’s best” approach.
… Ultimately, what we need is not just more ambition but better ambition. Ambition rooted in a realistic understanding of institutional capacity, a shared strategic vision, investments in policy and infrastructure, and a culture that supports online learning as a core part of the academic mission, not an auxiliary one. It’s time we talked about what it really takes to grow online learning , and where ambition needs to be matched by structure.
From DSC: Yup. Culture is at the breakfast table again…boy, those strategies taste good.
I’d like to take some of this report — like the graphic below — and share it with former faculty members and members of a couple of my past job families’ leadership. They strongly didn’t agree with us when we tried to advocate for the development of online-based learning/programs at our organizations…but we were right. We were right all along. And we were LEADING all along. No doubt about it — even if the leadership at the time said that we weren’t leading.
The cultures of those organizations hurt us at the time. But our cultivating work eventually led to the development of online programs — unfortunately, after our groups were disbanded, they had to outsource those programs to OPMs.
Arizona State University — with its dramatic growth in online-based enrollments.
Here are some incredibly powerful numbers from Mary Meeker’s AI Trends report, which showcase how artificial intelligence as a tech is unlike any other the world has ever seen.
AI took only three years to reach 50% user adoption in the US; mobile internet took six years, desktop internet took 12 years, while PCs took 20 years.
ChatGPT reached 800 million users in 17 months and 100 million in only two months, vis-à-vis Netflix’s 100 million (10 years), Instagram (2.5 years) and TikTok (nine months).
ChatGPT hit 365 billion annual searches in two years (2024) vs. Google’s 11 years (2009)—ChatGPT 5.5x faster than Google.
Above via Mary Meeker’s AI Trend-Analysis — from getsuperintel.com by Kim “Chubby” Isenberg How AI’s rapid rise, efficiency race, and talent shifts are reshaping the future.
The TLDR
Mary Meeker’s new AI trends report highlights an explosive rise in global AI usage, surging model efficiency, and mounting pressure on infrastructure and talent. The shift is clear: AI is no longer experimental—it’s becoming foundational, and those who optimize for speed, scale, and specialization will lead the next wave of innovation.
The Rundown: Meta aims to release tools that eliminate humans from the advertising process by 2026, according to a report from the WSJ — developing an AI that can create ads for Facebook and Instagram using just a product image and budget.
The details:
Companies would submit product images and budgets, letting AI craft the text and visuals, select target audiences, and manage campaign placement.
The system will be able to create personalized ads that can adapt in real-time, like a car spot featuring mountains vs. an urban street based on user location.
The push would target smaller companies lacking dedicated marketing staff, promising professional-grade advertising without agency fees or skillset.
Advertising is a core part of Mark Zuckerberg’s AI strategy and already accounts for 97% of Meta’s annual revenue.
Why it matters: We’re already seeing AI transform advertising through image, video, and text, but Zuck’s vision takes the process entirely out of human hands. With so much marketing flowing through FB and IG, a successful system would be a major disruptor — particularly for small brands that just want results without the hassle.
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.
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.
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.
Anthropic’s “Prompt Engineering Overview” is a free masterclass that’s worth its weight in gold. Their “constitutional AI prompting” section helped us create a content filter that actually works—unlike the one that kept flagging our coffee bean reviews as “inappropriate.” Apparently “rich body” triggered something…
OpenAI’s “Cookbook” is like having a Michelin-star chef explain cooking—simple for beginners, but packed with pro techniques. Their JSON formatting examples saved us 3 hours of debugging last week…
Google’s “Prompt Design Strategies” breaks down complex concepts with clear examples. Their before/after gallery showing how slight prompt tweaks improve results made us rethink everything we knew about getting quality outputs.
Pro tip: Save these guides as PDFs before they disappear behind paywalls. The best AI users keep libraries of these resources for quick reference. .
“To address this, organizations should consider building a sustainable AI governance model, prioritizing transparency, and tackling the complex challenge of AI-fueled imposter syndrome through reinvention. Employers who fail to approach innovation with empathy and provide employees with autonomy run the risk of losing valuable staff and negatively impacting employee productivity.”
Key findings from the report include the following:
Employees are keeping their productivity gains a secret from their employers. …
In-office employees may still log in remotely after hours. …
Younger workers are more likely to switch jobs to gain more flexibility.
AI discovers new math algorithms— from by Zach Mink & Rowan Cheung PLUS: Anthropic reportedly set to launch new Sonnet, Opus models
The Rundown: Google just debuted AlphaEvolve, a coding agent that harnesses Gemini and evolutionary strategies to craft algorithms for scientific and computational challenges — driving efficiency inside Google and solving historic math problems.
… Why it matters: Yesterday, we had OpenAI’s Jakub Pachocki saying AI has shown “significant evidence” of being capable of novel insights, and today Google has taken that a step further. Math plays a role in nearly every aspect of life, and AI’s pattern and algorithmic strengths look ready to uncover a whole new world of scientific discovery.
At the recent HR Executive and Future Talent Council event at Bentley University near Boston, I talked with Top 100 HR Tech Influencer Joey Price about what he’s hearing from HR leaders. Price is president and CEO of Jumpstart HR and executive analyst at Aspect43, Jumpstart HR’s HR?tech research division, and author of a valuable new book, The Power of HR: How to Make an Organizational Impact as a People?Professional.
This puts him solidly at the center of HR’s most relevant conversations. Price described the curiosity he’s hearing from many HR leaders about AI agents, which have become increasingly prominent in recent months.
DC: THIS could unfortunately be the ROI companies will get from large investments in #AI — reduced headcount/employees/contract workers. https://t.co/zEWlqCSWzI
Duolingo will “gradually stop using contractors to do work that AI can handle,” according to an all-hands email sent by cofounder and CEO Luis von Ahn announcing that the company will be “AI-first.” The email was posted on Duolingo’s LinkedIn account.
According to von Ahn, being “AI-first” means the company will “need to rethink much of how we work” and that “making minor tweaks to systems designed for humans won’t get us there.” As part of the shift, the company will roll out “a few constructive constraints,” including the changes to how it works with contractors, looking for AI use in hiring and in performance reviews, and that “headcount will only be given if a team cannot automate more of their work.”
Something strange, and potentially alarming, is happening to the job market for young, educated workers.
According to the New York Federal Reserve, labor conditions for recent college graduates have “deteriorated noticeably” in the past few months, and the unemployment rate now stands at an unusually high 5.8 percent. Even newly minted M.B.A.s from elite programs are struggling to find work. Meanwhile, law-school applications are surging—an ominous echo of when young people used graduate school to bunker down during the great financial crisis.
What’s going on? I see three plausible explanations, and each might be a little bit true.
The new workplace trend is not employee friendly. Artificial intelligence and automation technologies are advancing at blazing speed. A growing number of companies are using AI to streamline operations, cut costs, and boost productivity. Consequently, human workers are facing facing layoffs, replaced by AI. Like it or not, companies need to make tough decisions, including layoffs to remain competitive.
Corporations including Klarna, UPS, Duolingo, Intuit and Cisco are replacing laid-off workers with AI and automation. While these technologies enhance productivity, they raise serious concerns about future job security. For many workers, there is a big concern over whether or not their jobs will be impacted.
Key takeaway: Career navigation has remained largely unchanged for decades, relying on personal networks and static job boards. The advent of AI is changing this, offering personalised career pathways, better job matching, democratised job application support, democratised access to career advice/coaching, and tailored skill development to help you get to where you need to be.Hundreds of millions of people start new jobs every year, this transformation opens up a multi-billion dollar opportunity for innovation in the global career navigation market.
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A.4 How will AI disrupt this segment? Personalised recommendations: AI can consume a vast amount of information (skills, education, career history, even youtube history, and x/twitter feeds), standardise this data at scale, and then use data models to match candidate characteristics to relevant careers and jobs. In theory, solutions could then go layers deeper, helping you position yourself for those future roles. Currently based in Amsterdam, and working in Strategy at Uber and want to work in a Product role in the future? Here are X,Y,Z specific things YOU can do in your role today to align yourself perfectly. E.g. find opportunities to manage cross functional projects in your current remit, reach out to Joe Bloggs also at Uber in Amsterdam who did Strategy and moved to Product, etc.
No matter the school, no matter the location, when I deliver an AI workshop to a group of teachers, there are always at least a few colleagues thinking (and sometimes voicing), “Do I really need to use AI?”
Nearly three years after ChatGPT 3.5 landed in our lives and disrupted workflows in ways we’re still unpacking, most schools are swiftly catching up. Training sessions, like the ones I lead, are springing up everywhere, with principals and administrators trying to answer the same questions: Which tools should we use? How do we use them responsibly? How do we design learning in this new landscape?
But here’s what surprises me most: despite all the advances in AI technology, the questions and concerns from teachers remain strikingly consistent.
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In this article, I want to pull back the curtain on those conversations. These concerns aren’t signs of reluctance – they reflect sincere feelings. And they deserve thoughtful, honest answers.
This week, in advance of major announcements from us and other vendors, I give you a good overview of the AI Agent market, and discuss the new role of AI governance platforms, AI agent development tools, AI agent vendors, and how AI agents will actually manifest and redefine what we call an “application.”
I discuss ServiceNow, Microsoft, SAP, Workday, Paradox, Maki People, and other vendors. My goal today is to “demystify” this space and explain the market, the trends, and why and how your IT department is going to be building a lot of the agents you need. And prepare for our announcements next week!
DeepSeek has quietly launched Prover V2, an open-source model built to solve math problems using Lean 4 assistant, which ensures every step of a proof is rigorously verified.
What’s impressive about it?
Massive scale: Based on DeepSeek-V3 with 671B parameters using a mixture-of-experts (MoE) architecture, which activates only parts of the model at a time to reduce compute costs.
Theorem solving: Uses long context windows (32K+ tokens) to generate detailed, step-by-step formal proofs for a wide range of math problems — from basic algebra to advanced calculus theorems.
Research grade: Assists mathematicians in testing new theorems automatically and helps students understand formal logic by generating both Lean 4 code and readable explanations.
New benchmark: Introduces ProverBench, a new 325-question benchmark set featuring problems from recent AIME exams and curated academic sources to evaluate mathematical reasoning.
The need for deep student engagement became clear at Dartmouth Geisel School of Medicine when a potential academic-integrity issue revealed gaps in its initial approach to artificial intelligence use in the classroom, leading to significant revisions to ensure equitable learning and assessment.
From George Siemens “SAIL: Transmutation, Assessment, Robots e-newsletter on 5/2/25
All indications are that AI, even if it stops advancing, has the capacity to dramatically change knowledge work. Knowing things matters less than being able to navigate and make sense of complex environments. Put another way, sensemaking, meaningmaking, and wayfinding (with their yet to be defined subelements) will be the foundation for being knowledgeable going forward.
That will require being able to personalize learning to each individual learner so that who they are (not what our content is) forms the pedagogical entry point to learning.(DSC: And I would add WHAT THEY WANT to ACHIEVE.)LLMs are particularly good and transmutation. Want to explain AI to a farmer? A sentence or two in a system prompt achieves that. Know that a learner has ADHD? A few small prompt changes and it’s reflected in the way the LLM engages with learning. Talk like a pirate. Speak in the language of Shakespeare. Language changes. All a matter of a small meta comment send to the LLM. I’m convinced that this capability to change, transmute, information will become a central part of how LLMS and AI are adopted in education.
… Speaking of Duolingo– it took them 12 years to develop 100 courses. In the last year, they developed an additional 148. AI is an accelerant with an impact in education that is hard to overstate. “Instead of taking years to build a single course with humans the company now builds a base course and uses AI to quickly customize it for dozens of different languages.”
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