Reflecting on Education in 2025 — from by Dr. Rachelle Dené Poth
Educators have become more discerning about initiatives to invest in, tools to explore, and expectations to set. The question “Can we do this?” shifted to “Should we do this? And “Why?” Which then led to the “How” part.
This shift showed up in conversations around curriculum, assessment, technology use, and student well-being. Schools began reducing or being more selective rather than layering, which helped educators to adjust better to change. Leaders focused more on coherence instead of compliance. And in some conversations I had or articles I read, I noticed respectful pushback on practices that added complexity without improving learning.
I think this is why the recalibration mattered.
AI has become less about “cheating” and more about helping students and others learn how to think, evaluate, and create responsibly in an AI-infused world.
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Educators have become more discerning about initiatives to invest in, tools to explore, and expectations to set. The question “Can we do this?” shifted to “Should we do this? And “Why?” Which then led to the “How” part.
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.
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).
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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.
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.
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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.
People Watched 700 Million Hours of YouTube Podcasts on TV in October — from bloomberg.com (this article is behind a paywall)
- That’s up from 400 million hours a year ago as podcasts become the new late-night TV.
- YouTube Wins Over TV Audience With Video Podcasts.
- YouTube is dominating in the living room.
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:
- Not Your Default Chatbot: Five Teaching Applications of Custom AI Bots
Agile Learning
derekbruff.org/2025/10/01/five-teaching-applications-of-custom-ai-chatbots/
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.
- AI Agents As Legal Assistants
- AI As A Driver Of Business Strategy
- Automation In Judicial Administration
- Always-On Compliance Monitoring
- Cybersecurity As An Essential Survival Tool
- Predictive Litigation
- 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:
- Top 10 legal tech episodes in 2025 — from lawyersweekly.com.au
With AI and legal technology at the forefront of the profession’s mind now more than ever, The Lawyers Weekly Show and our special series LawTech Talks delivered in-depth explorations of these game-changing topics. Now, we’re highlighting the 10 most downloaded episodes that sparked conversation across the legal tech community. - eCourtDate Winner Of “LegalOps Platform of the Year” In 2025 LegalTech Breakthrough Awards Program — from globenewswire.com
Prestigious Annual Awards Program Recognizes Companies and Products Driving Innovation in the Global Legal Industry
Higher education faces ‘deteriorating’ 2026 outlook, Fitch says — from highereddive.com by Laura Spitalniak
A shrinking pipeline of students, uncertainty about state and federal support, and rising expenses could all hurt college finances, according to analysts.
Dive Brief:
- Fitch Ratings on Thursday issued a “deteriorating” outlook for the higher education sector in 2026, continuing the gloomy prediction the agency issued for 2025.
- Analysts based their forecast on a shrinking prospective student base, “rising uncertainty related to state and federal support, continued expense escalation and shifting economic conditions.”
- With its report, Fitch joins Moody’s Ratings and S&P Global Ratings in predicting a grim year for higher ed — Moody’s for the sector overall and S&P for nonprofit colleges specifically.
Yale expects layoffs as leaders brace for $300M in endowment taxes — from highereddive.com by Ben Unglesbee
The Ivy League institution’s tax bill starting next year will be higher than what it spends on student aid, university officials said.
Dive Brief:
- Yale University is bracing for layoffs as it prepares to pay the government hundreds of millions of dollars in endowment income taxes.
- In a public message, senior leaders at the Ivy League institution said that Yale’s schools plan to take steps such as delaying hiring and reducing travel spending to save money. But they warned workforce cuts were on the horizon.
- “Layoffs may be necessary” in some units where cutting open positions and other reductions are insufficient, the university officials said. They expect to complete any downsizing by the end of 2026 barring “additional significant financial changes.”
Education Department adds ‘lower earnings’ warning to FAFSA — from highereddive.com by Natalie Schwartz
The agency will warn students when they’ve indicated interest in a college whose graduates have relatively low incomes.
The U.S. Department of Education has launched a new disclosure feature that warns students who fill out the Free Application for Federal Student Aid if they’re interested in colleges whose graduates have relatively low earnings, the agency said Monday.
“Families deserve a clearer picture of how postsecondary education connects to real-world earnings, and this new indicator will provide that transparency,” U.S. Education Secretary Linda McMahon said in a Monday statement. “Not only will this new FAFSA feature make public earnings data more accessible, but it will empower prospective students to make data-driven decisions before they are saddled with debt.”
Also from highereddive.com, see:
- College costs grew 3.6% in fiscal 2025, HEPI shows
Faculty salaries rose 4.3%, the highest recorded rate since the Higher Education Price Index began in 1998. - Martin University to ‘pause’ operations at the end of the month
The board of the private Indianapolis university is working to find a path toward economic viability, it said in a Tuesday press release. - Willamette University and Pacific University seek to merge
The two private nonprofits in Oregon said Thursday that they intend to create “the University of the Northwest,” with one state official voicing support. - University of Nebraska regents approve cutting 4 programs at flagship
The university’s governing board voted in favor of the plan despite sustained faculty objections over the eliminations and the process for determining them.
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.
Why Parents Aren’t Reading to Kids, and What It Means for Young Students — from the74million.org by Jessika Harkay
A recent study found less than half of children are read to daily. The consequences are serious for early learners who enter school unprepared.
For children not getting the benefits of being read to at home, the opportunity gap has widened, with those young students entering school unprepared compared to those who have been read to.
“The gap really begins very, very early on. I think we underestimate how large a gap we’re already seeing in kindergarten,” said Susan Neuman, professor of childhood and literacy education at New York University, adding she recently visited a New York City kindergarten classroom and saw some children who only knew two letters compared to others who were prepared to read phrases.
A 2019 Ohio State University study found a 5-year-old child who is read to daily would be exposed to nearly 300,000 more words than one who isn’t read to regularly.
Beyond ChatGPT: Why In-House Counsel Need Purpose Built AI (Cecilia Ziniti, CEO – GC AI) — from tlpodcast.com
This episode features a conversation with Cecilia Ziniti, Co-Founder and CEO of GC.AI. Cecilia traces her career from the early days of the internet to founding an AI-driven legal platform for in-house counsel.
Cecilia shares her journey, starting as a paralegal at Yahoo in the early 2000s, working on nascent legal issues related to the internet. She discusses her time at Morrison & Foerster and her role at Amazon, where she was an early member of the Alexa team, gaining deep insight into AI’s potential before the rise of modern large language models (LLMs).
The core discussion centers on the creation of GC AI, a legal AI tool specifically designed for in-house counsel. Cecilia explains why general LLMs like ChatGPT are insufficient for professional legal work—lacking proper citation, context, and security/privilege protections. She highlights the app’s features, including enhanced document analysis (RAG implementation), a Word Add-in, and workflow-based playbooks to deliver accurate, client-forward legal analysis. The episode also touches on the current state of legal tech, the growing trend of bringing legal work in-house, and the potential for AI to shift the dynamics of the billable hour.
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:
- The state of AI in 2025: Agents, innovation, and transformation — from mckinsey.com
Almost all survey respondents say their organizations are using AI, and many have begun to use AI agents. But most are still in the early stages of scaling AI and capturing enterprise-level value.
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.
4 Simple & Easy Ways to Use AI to Differentiate Instruction — from mindfulaiedu.substack.com (Mindful AI for Education) by Dani Kachorsky, PhD
Designing for All Learners with AI and Universal Design Learning
So this year, I’ve been exploring new ways that AI can help support students with disabilities—students on IEPs, learning plans, or 504s—and, honestly, it’s changing the way I think about differentiation in general.
As a quick note, a lot of what I’m finding applies just as well to English language learners or really to any students. One of the big ideas behind Universal Design for Learning (UDL) is that accommodations and strategies designed for students with disabilities are often just good teaching practices. When we plan instruction that’s accessible to the widest possible range of learners, everyone benefits. For example, UDL encourages explaining things in multiple modes—written, visual, auditory, kinesthetic—because people access information differently. I hear students say they’re “visual learners,” but I think everyone is a visual learner, and an auditory learner, and a kinesthetic learner. The more ways we present information, the more likely it is to stick.
So, with that in mind, here are four ways I’ve been using AI to differentiate instruction for students with disabilities (and, really, everyone else too):
The Periodic Table of AI Tools In Education To Try Today — from ictevangelist.com by Mark Anderson
What I’ve tried to do is bring together genuinely useful AI tools that I know are already making a difference.
For colleagues wanting to explore further, I’m sharing the list exactly as it appears in the table, including website links, grouped by category below. Please do check it out, as along with links to all of the resources, I’ve also written a brief summary explaining what each of the different tools do and how they can help.
Seven Hard-Won Lessons from Building AI Learning Tools — from linkedin.com by Louise Worgan
Last week, I wrapped up Dr Philippa Hardman’s intensive bootcamp on AI in learning design. Four conversations, countless iterations, and more than a few humbling moments later – here’s what I am left thinking about.
Finally Catching Up to the New Models — from michellekassorla.substack.com by Michelle Kassorla
There are some amazing things happening out there!
An aside: Google is working on a new vision for textbooks that can be easily differentiated based on the beautiful success for NotebookLM. You can get on the waiting list for that tool by going to LearnYourWay.withgoogle.com.
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Nano Banana Pro
Sticking with the Google tools for now, Nano Banana Pro (which you can use for free on Google’s AI Studio), is doing something that everyone has been waiting a long time for: it adds correct text to images.
Introducing AI assistants with memory — from perplexity.ai
The simple act of remembering is the crux of how we navigate the world: it shapes our experiences, informs our decisions, and helps us anticipate what comes next. For AI agents like Comet Assistant, that continuity leads to a more powerful, personalized experience.
Today we are announcing new personalization features to remember your preferences, interests, and conversations. Perplexity now synthesizes them automatically like memory, for valuable context on relevant tasks. Answers are smarter, faster, and more personalized, no matter how you work.
From DSC :
This should be important as we look at learning-related applications for AI.
For the last three days, my Substack has been in the top “Rising in Education” list. I realize this is based on a hugely flawed metric, but it still feels good. ?
– Michael G Wagner
I’m a Professor. A.I. Has Changed My Classroom, but Not for the Worse. — from nytimes.com by Carlo Rotella [this should be a gifted article]
My students’ easy access to chatbots forced me to make humanities instruction even more human.






