What’s Happening to Jobs for New Grads — from linkedin.com by Jeff Selingo

No matter where you go to college, the job market math for new graduates is grim right now, as I write in a new article out yesterday in New York magazine.

There were 15% fewer entry-level and internship job postings in 2025 than the year before, according to Handshake, a job-search platform popular with college students; meanwhile, applications per posting rose 26%.

How much AI is to blame for the fragile entry-level job market is unclear. Several research studies show AI is hitting young college-educated workers disproportionately, but broader economic forces are part of the story, too.

As Christine Y. Cruzvergara, Handshake’s chief education strategy officer, told me, AI isn’t “taking” jobs so much as employers are “choosing” to replace parts of jobs with automation rather than redesign roles around workers. “They’re replacing people instead of enabling their workforce,” she said.

Today’s graduates are stuck in an in-between moment. Many started college before AI mattered and graduated into a labor market reshaped almost overnight, where entry-level roles are disappearing faster than students can adapt.

 
 

AI Is Quietly Rewiring the ADDIE Model (In a Good Way) — from drphilippahardman.substack.com by Dr. Philippa Hardman
The traditional ADDIE workflow isn’t dead, but it is evolving

The real story isn’t what AI can produce — it’s how it changes the decisions we make at every stage of instructional design.

After working with thousands of instructional designers on my bootcamp, I’ve learned something counterintuitive: the best teams aren’t the ones with the fanciest AI tools — they’re the ones who know when to use which mode—and when to use none at all.

Once you recognise that, you start to see instructional design differently — not as a linear process, but as a series of decision loops where AI plays distinct roles.

In this post, I show you the 3 modes of AI that actually matter in instructional design — and map them across every phase of ADDIE so you know exactly when to let AI run, and when to slow down and think.


Also see:

Generative AI for Course Design: Writing Effective Prompts for Multiple Choice Question Development — from onlineteaching.umich.edu by Hedieh Najafi

In higher education, developing strong multiple-choice questions can be a time-intensive part of the course design process. Developing such items requires subject-matter expertise and assessment literacy, and for faculty and designers who are creating and producing online courses, it can be difficult to find the capacity to craft quality multiple-choice questions.

At the University of Michigan Center for Academic Innovation, learning experience designers are using generative artificial intelligence to streamline the multiple-choice question development process and help ameliorate this issue. In this article, I summarize one of our projects that explored effective prompting strategies to develop multiple-choice questions with ChatGPT for our open course portfolio. We examined how structured prompting can improve the quality of AI-generated assessments, producing relevant comprehension and recall items and options that include plausible distractors.

Achieving this goal enables us to develop several ungraded practice opportunities, preparing learners for their graded assessments while also freeing up more time for course instructors and designers.

 

Which AI Video Tool Is Most Powerful for L&D Teams? — from by Dr. Philippa Hardman
Evaluating four popular AI video generation platforms through a learning-science lens

Happy new year! One of the biggest L&D stories of 2025 was the rise to fame among L&D teams of AI video generator tools. As we head into 2026, platforms like Colossyan, Synthesia, HeyGen, and NotebookLM’s video creation feature are firmly embedded in most L&D tech stacks. These tools promise rapid production and multi-language output at significantly reduced costs —and they deliver on a lot of that.

But something has been playing on my mind: we rarely evaluate these tools on what matters most for learning design—whether they enable us to build instructional content that actually enables learning.

So, I spent some time over the holiday digging into this question: do the AI video tools we use most in L&D create content that supports substantive learning?

To answer it, I took two decades of learning science research and translated it into a scoring rubric. Then I scored the four most popular AI video generation platforms among L&D professionals against the rubric.
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For an AI-based tool or two — as they regard higher ed — see:

5 new tools worth trying — from wondertools.substack.com by Jeremy Kaplan

YouTube to NotebookLM: Import a Whole Playlist or Channel in One Click
YouTube to NotebookLM is a remarkably useful new Chrome extension that lets you bulk-add any YouTube playlists, channels, or search results into NotebookLM. for AI-powered analysis.

What to try

  • Find or create YouTube playlists on topics of interest. Then use this extension to ingest those playlists into NotebookLM. The videos are automatically indexed, and within minutes you can create reports, slides, and infographics to enhance your learning.
  • Summarize a playlist or channel with an audio or video overview. Or create quizzes, flash cards, data tables, or mind maps to explore a batch of YouTube videos. Or have a chat in NotebookLM with your favorite video channel. Check my recent post for some YouTube channels to try.
 

What AI-Generated Voice Technology Means For Creators And Brands — from bitrebels.com by Ryan Mitchell

Voice has become one of the most influential elements in how digital content is experienced. From podcasts and videos to apps, ads, and interactive platforms, spoken audio shapes how messages are understood and remembered. In recent years, the rise of the ai voice generator has changed how creators and brands approach audio production, lowering barriers while expanding creative possibilities.

Rather than relying exclusively on traditional voice recording, many teams now use AI-generated voices as part of their content and brand strategies. This shift is not simply about efficiency; it reflects broader changes in how digital experiences are produced, scaled, and personalised.

The Future Role Of AI-Generated Voice
As AI voice technology continues to improve, its role in creative and brand workflows will likely expand. Future developments may include more adaptive voices that respond to context, audience behaviour, or emotional cues in real time. Rather than replacing traditional voice work, AI-generated voice is becoming another option in a broader creative toolkit, one that offers speed, flexibility, and accessibility.

 

Major Changes Reshape Law Schools Nationwide in 2026 — from jdjournal.com by Ma Fatima

Law schools across the United States are entering one of the most transformative periods in recent memory. In 2026, legal education is being reshaped by leadership turnover, shifting accreditation standards, changes to student loan policies, and the introduction of a redesigned bar exam. Together, these developments are forcing law schools to rethink how they educate students and prepare future lawyers for a rapidly evolving legal profession.

Also from jdjournal.com, see:

  • Healthcare Industry Legal Careers: High-Growth Roles and Paths — from jdjournal.com by Ma Fatima
    The healthcare industry is rapidly emerging as one of the most promising and resilient sectors for legal professionals, driven by expanding regulations, technological innovation, and an increasingly complex healthcare delivery system. As hospitals, life sciences companies, insurers, and digital health platforms navigate constant regulatory change, demand for experienced legal talent continues to rise.
 

Corporate Training Solutions That Actually Improve Performance — from blog.upsidelearning.com by Unnati Umare

Designing Learning Around Performance in the Flow of Work
Once it becomes clear that completion does not reliably translate into changed behavior, the next question tends to surface on its own. If training is not failing outright, then what it should be designed around becomes harder to ignore.

In most organizations, the answer remains content. Content is easier to define, easier to build, and easier to track, even when it explains very little about how work actually gets done.

Performance-aligned learning design shifts that starting point by paying closer attention to how work unfolds in practice. Instead of organizing learning around topics or courses, design decisions begin with what a role requires people to notice, decide, and act on during real situations.  

 

Nvidia, Eli Lilly announce $1 billion investment in AI drug discovery lab — from finance.yahoo.com by Laura Bratton

AI chipmaker Nvidia (NVDA) and pharmaceutical giant Eli Lilly (LLY) on Monday announced that the two companies would jointly invest $1 billion to create a lab in San Francisco focused on using AI to accelerate drug discovery.

The $1 billion investment will be spent over five years on infrastructure, compute, and talent for the lab. Nvidia’s engineers will work alongside Lilly’s experts in biology, science, and medicine to generate large-scale data and build AI models to advance medicine development. The lab’s work will begin early this year, the companies said.

 

Shoppers will soon be able to make purchases directly through Google’s Gemini app and browser.



Google and Walmart Join Forces to Shape the Future of Retail — from adweek.com by Lauren Johnson
At NRF, Sundar Pichai and John Furner revealed how AI and drones will shape shopping in 2026 and beyond

One of the biggest reveals is that shoppers will be able to purchase Walmart and Sam’s Club products through Google’s AI chatbot Gemini.


 

Work from Home Jobs No Experience — from intelligenthq.com by A.Peyman Khosravani

Work from home jobs with no experience can help you earn money from home, even if you are new and have never done a remote job before. If you are looking for work from home jobs with no experience and aren’t sure which are real (and worth your time), you’re in the right place. In this guide, you will find real, beginner-friendly remote jobs you can do from home, even if you have never worked remotely before.

We will explain the best entry-level options, what they may pay, what you need to get started, and how to avoid scams. I will also share simple tips to help you get work-from-home jobs with no experience and start remote jobs faster.

1) What is the best work from home with no experience?
The best work-from-home jobs with no experience are usually remote customer service, transcription, AI task work, or moderation, since training and guidelines are provided.

2) What jobs can you do online from home with no experience?
You can do online customer support, transcription/captioning, microtasks, paid research studies, and entry-level AI evaluation tasks.

 

Rebuilding The First Rung Of The Opportunity Ladder — from forbes.com by Bruno V. Manno

Two-thirds of employers say most new hires are not fully prepared for their roles, citing “experience,” not technical skill, as the greatest shortfall. At the same time, 61% of companies have raised their experience requirements.

As a result, many so-called entry-level roles now demand two to five years of prior work experience. The first rung of the career ladder has been pulled even farther out of reach for new job seekers. A portfolio—or full-spectrum—model of work-based learning is one promising way to rebuild that rung.

Experience has become what Deloitte calls “the new currency of employability.” But the places where young people once earned that currency are disappearing.

 

How Your Learners *Actually* Learn with AI — from drphilippahardman.substack.com by Dr. Philippa Hardman
What 37.5 million AI chats show us about how learners use AI at the end of 2025 — and what this means for how we design & deliver learning experiences in 2026

Last week, Microsoft released a similar analysis of a whopping 37.5 million Copilot conversations. These conversation took place on the platform from January to September 2025, providing us with a window into if and how AI use in general — and AI use among learners specifically – has evolved in 2025.

Microsoft’s mass behavioural data gives us a detailed, global glimpse into what learners are actually doing across devices, times of day and contexts. The picture that emerges is pretty clear and largely consistent with what OpenAI’s told us back in the summer:

AI isn’t functioning primarily as an “answers machine”: the majority of us use AI as a tool to personalise and differentiate generic learning experiences and – ultimately – to augment human learning.

Let’s dive in!

Learners don’t “decide” to use AI anymore. They assume it’s there, like search, like spellcheck, like calculators. The question has shifted from “should I use this?” to “how do I use this effectively?”


8 AI Agents Every HR Leader Needs To Know In 2026 — from forbes.com by Bernard Marr

So where do you start? There are many agentic tools and platforms for AI tasks on the market, and the most effective approach is to focus on practical, high-impact workflows. So here, I’ll look at some of the most compelling use cases, as well as provide an overview of the tools that can help you quickly deliver tangible wins.

Some of the strongest opportunities in HR include:

  • Workforce management, administering job satisfaction surveys, monitoring and tracking performance targets, scheduling interventions, and managing staff benefits, medical leave, and holiday entitlement.
  • Recruitment screening, automatically generating and posting job descriptions, filtering candidates, ranking applicants against defined criteria, identifying the strongest matches, and scheduling interviews.
  • Employee onboarding, issuing new hires with contracts and paperwork, guiding them to onboarding and training resources, tracking compliance and completion rates, answering routine enquiries, and escalating complex cases to human HR specialists.
  • Training and development, identifying skills gaps, providing self-service access to upskilling and reskilling opportunities, creating personalized learning pathways aligned with roles and career goals, and tracking progress toward completion.

 

 

25 Big Ideas that will define 2026 — from linkedin.com by LinkedIn News
This year’s predictions capture a world in flux, where technology and humanity will press closer than ever, fueling new opportunities and tensions.

Blockchain: Blockchain technology will create new ways for creators to keep more of their revenue by enabling them to host their own content, bypassing traditional social media platforms that take a cut of their earnings.

3.AI: Artificial intelligence will enhance creators’ ability to scale their personal brands exponentially — producing more content, creating virtual influencers and expanding reach in ways we’ve never seen.

Laws around artificial intelligence in mental health care are set to change dramatically in 2026, in the wake of lawsuits alleging harm or “psychosis” linked to AI tools. After years of rapid adoption — and little oversight — regulators will move to treat therapy chatbots more like medical devices than lifestyle apps.

Small businesses — which make up 90% of companies globally — will be the top destination for young jobseekers in 2026.

Generative engine optimization (GEO) is set to replace search engine optimization (SEO) as the way brands get discovered in the year ahead. As consumers turn to AI chatbots, agentic workflows and answer engines, appearing prominently in generative outputs will matter more than ranking in search engines.

 

AI working competency is now a graduation requirement at Purdue [Pacton] + other items re: AI in our learning ecosystems


AI Has Landed in Education: Now What? — from learningfuturesdigest.substack.com by Dr. Philippa Hardman

Here’s what’s shaped the AI-education landscape in the last month:

  • The AI Speed Trap is [still] here: AI adoption in L&D is basically won (87%)—but it’s being used to ship faster, not learn better (84% prioritising speed), scaling “more of the same” at pace.
  • AI tutors risk a “pedagogy of passivity”: emerging evidence suggests tutoring bots can reduce cognitive friction and pull learners down the ICAP spectrum—away from interactive/constructive learning toward efficient consumption.
  • Singapore + India are building what the West lacks: they’re treating AI as national learning infrastructure—for resilience (Singapore) and access + language inclusion (India)—while Western systems remain fragmented and reactive.
  • Agentic AI is the next pivot: early signs show a shift from AI as a content engine to AI as a learning partner—with UConn using agents to remove barriers so learners can participate more fully in shared learning.
  • Moodle’s AI stance sends two big signals: the traditional learning ecosystem in fragmenting, and the concept of “user sovereignty” over by AI is emerging.

Four strategies for implementing custom AIs that help students learn, not outsource — from educational-innovation.sydney.edu.au by Kria Coleman, Matthew Clemson, Laura Crocco and Samantha Clarke; via Derek Bruff

For Cogniti to be taken seriously, it needs to be woven into the structure of your unit and its delivery, both in class and on Canvas, rather than left on the side. This article shares practical strategies for implementing Cogniti in your teaching so that students:

  • understand the context and purpose of the agent,
  • know how to interact with it effectively,
  • perceive its value as a learning tool over any other available AI chatbots, and
  • engage in reflection and feedback.

In this post, we discuss how to introduce and integrate Cogniti agents into the learning environment so students understand their context, interact effectively, and see their value as customised learning companions.

In this post, we share four strategies to help introduce and integrate Cogniti in your teaching so that students understand their context, interact effectively, and see their value as customised learning companions.


Collection: Teaching with Custom AI Chatbots — from teaching.virginia.edu; via Derek Bruff
The default behaviors of popular AI chatbots don’t always align with our teaching goals. This collection explores approaches to designing AI chatbots for particular pedagogical purposes.

Example/excerpt:



 
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