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.

 

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.


 
 

At CES 2026, Everything Is AI. What Matters Is How You Use It — from wired.com by Boone Ashworth
Integrated chatbots and built-in machine intelligence are no longer standout features in consumer tech. If companies want to win in the AI era, they’ve got to hone the user experience.

Beyond Wearables
Right now, AI is on your face and arms—smart glasses and smart watches—but this year will see it proliferate further into products like earbuds, headphones, and smart clothing.

Health tech will see an influx of AI features too, as companies aim to use AI to monitor biometric data from wearables like rings and wristbands. Heath sensors will also continue to show up in newer places like toilets, bath mats, and brassieres.

The smart home will continue to be bolstered by machine intelligence, with more products that can listen, see, and understand what’s happening in your living space. Familiar candidates for AI-powered upgrades like smart vacuums and security cameras will be joined by surprising AI bedfellows like refrigerators and garage door openers.


Along these lines, see
live updates from CNET here.


ChatGPT is overrated. Here’s what to use instead. — from washingtonpost.com by Geoffrey A. Fowler
When I want help from AI, ChatGPT is no longer my default first stop.

I can tell you which AI tools are worth using — and which to avoid — because I’ve been running a chatbot fight club.

I conducted dozens of bot challenges based on real things people do with AI, including writing breakup texts and work emailsdecoding legal contracts and scientific researchanswering tricky research questions, and editing photos and making “art.” Human experts including best-selling authors, reference librarians, a renowned scientist and even a Pulitzer Prize-winning photographer judged the results.

After a year of bot battles, one thing stands out: There is no single best AI. The smartest way to use chatbots today is to pick different tools for different jobs — and not assume one bot can do it all.


How Collaborative AI Agents Are Shaping the Future of Autonomous IT — from aijourn.com by Michael Nappi

Some enterprise platforms now support cross-agent communication and integration with ecosystems maintained by companies like Microsoft, NVIDIA, Google, and Oracle. These cross-platform data fabrics break down silos and turn isolated AI pilots into enterprise-wide services. The result is an IT backbone that not only automates but also collaborates for continuous learning, diagnostics, and system optimization in real time.


Nvidia dominated the headlines in 2025 — these were its 15 biggest events of the year — from finance.yahoo.com by Daniel Howley

It’s difficult to think of any single company that had a bigger impact on Wall Street and the AI trade in 2025 than Nvidia (NVDA).

Nvidia’s revenue soared in 2025, bringing in $187.1 billion, and its market capitalization continued to climb, briefly eclipsing the $5 trillion mark before settling back in the $4 trillion range.

There were plenty of major highs and deep lows throughout the year, but these 15 were among the biggest moments of Nvidia’s 2025.


 

 

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.

 

 

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:



 

7 Legal Tech Trends That Will Reshape Every Business In 2026 — from forbes.com by Bernard Marr

Here are the trends that will matter most.

  1. AI Agents As Legal Assistants
  2. AI As A Driver Of Business Strategy
  3. Automation In Judicial Administration
  4. Always-On Compliance Monitoring
  5. Cybersecurity As An Essential Survival Tool
  6. Predictive Litigation
  7. Compliance As Part Of The Everyday Automation Fabric

According to the Thomson Reuters Future Of Professionals report, most experts already expect AI to transform their work within five years, with many viewing it as a positive force. The challenge now is clear: legal and compliance leaders must understand the tools reshaping their field and prepare their teams for a very different way of working in 2026.


Addendum on 12/17/25:

 

Beyond Infographics: How to Use Nano Banana to *Actually* Support Learning — from drphilippahardman.substack.com by Dr Philippa Hardman
Six evidence-based use cases to try in Google’s latest image-generating AI tool

While it’s true that Nano Banana generates better infographics than other AI models, the conversation has so far massively under-sold what’s actually different and valuable about this tool for those of us who design learning experiences.

What this means for our workflow:

Instead of the traditional “commission ? wait ? tweak ? approve ? repeat” cycle, Nano Banana enables an iterative, rapid-cycle design process where you can:

  • Sketch an idea and see it refined in minutes.
  • Test multiple visual metaphors for the same concept without re-briefing a designer.
  • Build 10-image storyboards with perfect consistency by specifying the constraints once, not manually editing each frame.
  • Implement evidence-based strategies (contrasting cases, worked examples, observational learning) that are usually too labour-intensive to produce at scale.

This shift—from “image generation as decoration” to “image generation as instructional scaffolding”—is what makes Nano Banana uniquely useful for the 10 evidence-based strategies below.

 


 


 

Agents, robots, and us: Skill partnerships in the age of AI — from mckinsey.com by Lareina Yee, Anu Madgavkar, Sven Smit, Alexis Krivkovich, Michael Chui, María Jesús Ramírez, and Diego Castresana
AI is expanding the productivity frontier. Realizing its benefits requires new skills and rethinking how people work together with intelligent machines.

At a glance

  • Work in the future will be a partnership between people, agents, and robots—all powered by AI. …
  • Most human skills will endure, though they will be applied differently. …
  • Our new Skill Change Index shows which skills will be most and least exposed to automation in the next five years….
  • Demand for AI fluency—the ability to use and manage AI tools—has grown sevenfold in two years…
  • By 2030, about $2.9 trillion of economic value could be unlocked in the United States…

Also related/see:



State of AI: December 2025 newsletter — from nathanbenaich.substack.com by Nathan Benaich
What you’ve got to know in AI from the last 4 weeks.

Welcome to the latest issue of the State of AI, an editorialized newsletter that covers the key developments in AI policy, research, industry, and start-ups over the last month.


 
© 2025 | Daniel Christian