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The stats are wild.

AI usage among university students exploded from 66% in 2024 to 92% in 2025—and GenAI usage for assessments jumped from 53% to 88% in the same period. Students aren't waiting for permission. They're using ChatGPT, Khanmigo, and a dozen other AI tools to learn faster, better, and on their own terms.

But here's the thing most people miss: the real skill isn't using AI. It's knowing how to learn with it.

DeepMind CEO Demis Hassabis said it best at the foot of the Acropolis in Athens: "The most valuable human skill ahead is 'learning how to learn.' With AI changing week by week, agility, not static expertise, will define student success."

Welcome to the era of meta-learning—where the ability to adapt, iterate, and teach yourself anything is the only future-proof skill left.

The Problem: Education Is Teaching Yesterday's Skills for Tomorrow's World

Traditional education was built for a world that doesn't exist anymore.

You spent years memorizing facts, mastering specific skills, and training for jobs that might not be there when you graduate. The system assumed knowledge was stable... that what you learned in 2020 would still be relevant in 2030.

AI shattered that assumption.

The global AI in education market is projected to grow from $7.71 billion in 2025 to $32.27 billion by 2030, and it's not just about chatbots answering homework questions. Teachers who use AI tools at least once a week save about 5.9 hours per week. 71% of teachers say AI tools are essential for student success in college and work.

But here's what no one's saying out loud: students are already ahead of their teachers.

A global survey found that 86% of students use AI in their studies, with 54% using it weekly and nearly one in four using it daily. Meanwhile, while 61% of faculty have used AI in teaching, 88% do so minimally.

The gap is real. And it's growing.

How it works:

What "Learning How to Learn" Actually Means

Meta-learning isn't some abstract concept. It's a specific, trainable skill.

Think of it like this: traditional learning is memorizing how to solve one specific type of math problem. Meta-learning is understanding the process of how you learn to solve math problems—so when you encounter a totally new type of problem, you know how to teach yourself.

Hassabis urged education to add meta-skills—how to learn, adapt, and transfer knowledge—alongside math, science, and the humanities.

Here's what that looks like in practice:

1. Learning with AI, not around it

The best students aren't using AI to cheat. They're using it as a thinking partner.

Khanmigo, Khan Academy's AI tutor, doesn't just give answers. Instead, with limitless patience, it guides learners to find the answer themselves. That's the key difference: AI as a Socratic coach, not a shortcut.

2. Building feedback loops

Squirrel AI's system fosters a closed-loop feedback mechanism, integrating assessment, practice, learning, testing, and teaching phases seamlessly. Students learn, get tested, receive instant feedback, adjust, and repeat. Fast iteration = fast learning.

3. Personalization at scale

Squirrel AI's Intelligent Adaptive Learning System can break down knowledge points at the nano-level, refining hundreds of original knowledge points into tens of thousands of smaller and more precise ones, providing targeted guidance for students' weak areas.

Traditional education treats everyone the same. AI-powered meta-learning treats everyone uniquely.

Why this matters now:

The World Is Moving Too Fast for Static Knowledge

Remember when you could learn a skill once and use it for 20 years?

Yeah, that's over.

"It's very hard to predict the future... The only thing you can say for certain is that huge change is coming," Hassabis said. He added that artificial general intelligence could arrive within a decade.

Translation: the half-life of knowledge is shrinking. What you learn today might be obsolete in 18 months.

So what do you do?

You learn how to learn faster than the world changes.

Brisbane Catholic Education allowed students aged 13+ to use Microsoft 365 Copilot Chat for brainstorming and confidence building, which resulted in a 275% boost in their ability to direct their learning.

That stat is insane. Not "275% more knowledge." But 275% better at directing their own learning.

That's the meta-skill in action.

The Business Side:

A $32 Billion Market That's Just Getting Started

Investors are paying attention.

In July 2025, Microsoft planned to invest over $4 billion in AI education, with a focus on training millions of individuals through schools, community colleges, nonprofits, and its newly started Microsoft Elevate Academy.

The companies winning in this space aren't just building better flashcards. They're building systems that teach people how to think, adapt, and iterate.

Who's leading the charge:

Khanmigo (Khan Academy): When rating AI tools for learning, Common Sense Media gave Khanmigo 4 stars, rising above other AI tools like ChatGPT and Bard

Squirrel AI: Trusted in over 3,000 locations worldwide, Squirrel AI is an advanced tutoring system designed to help children excel, whether they're struggling or gifted

Duolingo Max: Offers personalized features like "explain my answer," which gives learners detailed feedback on their responses, or "roleplay," which lets users practice real-life conversations with AI characters

These aren't tutoring services. They're meta-learning engines.

The Concern:

Are We Creating a Generation That Can't Think Without AI?

Not everyone's thrilled.

A 2024 survey by Forbes found that almost two-thirds (65%) of educators believe plagiarism to be the primary issue when it comes to managing the potential negative side effects of AI tools in the classroom.

And that's a valid concern... if we're using AI wrong.

The problem isn't AI. It's treating AI like a crutch instead of a coach.

The solution? Make meta-learning explicit: Teach students how to set learning goals, run short experiments, reflect, and iterate. Turn the learning process into a repeatable system.

In other words: don't ban AI. Teach kids how to use it to become better learners.

What's next

Education Is Being Rebuilt From the Ground Up

This isn't a trend. It's a transformation.

A majority of students worry about their lack of AI expertise, which is perhaps unsurprising considering how few education institutions provide clear guidance on AI use.

The schools and companies that win will be the ones that teach meta-learning as a core skill, not an afterthought.

From a $7.57 billion market in 2025 to students scoring 54% higher on tests, AI is transforming how we learn and what's possible in education.

The future belongs to people who can learn anything, anytime, faster than the world can change.

The question isn't whether you'll use AI to learn.

It's whether you'll learn how to learn with it.

BTW: The term "meta-learning" was actually coined by Donald B. Maudsley in 1979, but it didn't become mainstream until AI researchers started using it to describe how machines "learn to learn" with minimal data. Now, it's coming full circle—humans are using AI to master the same meta-learning techniques that make AI so powerful in the first place. Wild, right?

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The Recap: OpenAI is in talks to raise up to $100 billion in a funding round that could value the ChatGPT maker at up to $830 billion, a 66% jump from its $500 billion valuation in October. The AI lab currently generates about $20 billion in annual run-rate revenue and already has more than $64 billion in its coffers, yet needs staggering new capital as the fundraising push follows an internal "code red" shift after CEO Sam Altman directed staff to focus on improving ChatGPT following Google's release of a model that outperformed OpenAI's software on several benchmarks.

Unpacked:

Bottom line: The move would propel OpenAI's valuation to a staggering $830 billion and test investor appetite for artificial intelligence as the initial market frenzy shows signs of cooling. This isn't a fundraise—it's a stress test for whether AI infrastructure can continue attracting sovereign-scale capital when profitability remains seven years away and competitive pressure from Google, Anthropic, and open-source models intensifies.

OpenAI opened app submissions for ChatGPT and introduced a new app directory within Chat's tools menu dubbed an "app store", transforming ChatGPT into a platform where third-party apps can be built for the chatbot using a beta Apps SDK and proper review pipeline—replicating Apple's platform playbook to monetize third-party developer output while deepening user lock-in exactly when Altman declared code red on Google's competitive threat.

Apple released an updated developer license agreement giving the company permission to recoup unpaid funds by deducting them from in-app purchases it processes on developers' behalf, impacting developers in regions where local law allows them to link to external payment systems, essentially transforming Apple into a debt collector with direct access to developer revenue streams—platform power consolidating financial control beyond transaction fees.

TikTok signed agreements with investors including Oracle, Silver Lake, and MGX to create a new TikTok U.S. joint venture enabling over 170 million Americans to continue using the app, with the investor consortium owning 50% of the joint venture, existing ByteDance investors holding just over 30%, and ByteDance retaining 19.9%—geopolitical pressure forcing the first major platform transfer of control based on sovereignty concerns, establishing precedent for how nationalist digital policy will reshape global tech ownership.

Communities are rising up against datacenter construction and winning battles against AI infrastructure expansion, meaning the bottleneck for AI scaling may shift from capital and talent to community consent and energy grid capacity—local political coalitions becoming the unexpected chokepoint for trillion-dollar AI ambitions.

ChatGPT's mobile app hit a new milestone of $3 billion in consumer spending, monetizing faster than any prior software category including TikTok's timeline—suggesting AI consumer adoption is reaching an inflection where willingness-to-pay significantly exceeds expectations even as investors question long-term business model viability.

British politicians are flocking to American tech giants, with tech companies acquiring political credibility and regulatory access by hiring senior government figures—creating a revolving door that may allow platforms to influence policy before it crystallizes against them.

Cursor acquired Graphite, as consolidation in AI development tools accelerates with integrated platforms acquiring specialized tools to build deeper moats around developer workflow—winner-take-most dynamics emerging even in the picks-and-shovels layer of AI infrastructure.

Amazon will allow ePub and PDF downloads for DRM-free eBooks starting in 2026, signaling that even dominant platforms are yielding on content control as regulatory and consumer pressure on digital rights shifts the economics of platform lock-in strategies.

Best of AI™ Team

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