What do China’s primary school curriculum, Shopify’s hiring strategy, and Trump’s tariffs have in common?

They all point to the same truth:

The future of talent isn’t about having more people—it’s about having the right people, equipped with the right skills for an AI-first world.

Let’s be real. We’re not preparing for the future anymore. We’re already living in it.

“Is AI a bubble?”

“Will it really take my job?”

“Can we wait and see how things work out?”

Honestly, those questions are no longer valid. While the answers might not be 100% right (then again, how often can we have a perfect answer anyway?), the right question now should be “How fast can you catch up?”

In fact, last week when I was conducting an AI Enablement workshop for the leaders of a wholesale grocery chain store, the CEO kickstarted the session with a powerful statement.

“We can either ride the AI wave, or we can wait it out.”

When I took the stage, I jokingly said that “Actually, we’re already all wet, so we better learn how to swim.”

Laughter is a good way to start any session, but that’s the reality, isn’t it? 

In boardrooms and classrooms alike, the pressure is mounting.

AI isn’t just another tech wave—it’s a total paradigm shift in how work gets done, how decisions are made, and how value is created. Companies that once prided themselves on operational efficiency are now being outpaced by leaner, AI-savvy competitors. Schools that once emphasized STEM are now revamping entire syllabi to prepare students not just to understand AI, but to work with it.

And let’s not sugarcoat it: some countries are sprinting. Others? Still tying their shoelaces.

Some corporate leaders are already revamping the entire L&D systems. Others are waiting for budgets to “free up.” But time isn’t slowing down. AI adoption curves are steepening, not plateauing.

There’s no “new era of work”. We’re already in it.

And in this article, we’re going to look at two indicators and one accelerant of this new era.

Oh by the way… Welcome to the Age of Augmented Talent.

Never too young to learn a future skill.

Education Rebooted

In China, children as young as six years old will start learning artificial intelligence as part of their national curriculum starting September 1, 2025. Not just coding. Not digital literacy. AI.

It’s a bold move—and a calculated one. China isn’t just teaching kids how to use technology. It’s shaping how they’ll think with it. This is about building a generation that doesn’t fear AI, but flows with it. One where AI fluency becomes as natural as learning a second language.

Israel is doing something equally radical. A sweeping nationwide initiative will train 70,000 teachers in AI integration. To support them, 3,000 mentors from over 400 tech companies are stepping in. From my perspecitve, calling it an “upskilling” is an understatement. That’s infrastructure overhaul for the knowledge economy. And it signals a new era where teachers aren’t just educators—they’re AI collaborators.

Estonia, often called the digital pioneer of Europe, is embedding ChatGPT across classrooms. But it’s not just about access—it’s about application. Students are learning how to co-write essays, generate project ideas, and challenge assumptions with AI in real time. On the surface, it’s like Estonians are changing the way skills are taught. Dig deeper, and you’ll realize that its changing the way thoughts are formed!

Globally, the International Telecommunication Union (ITU) has launched an AI Skills Coalition with AWS, Microsoft, and the East Africa Community. The goal? Make AI education open, accessible, and inclusive—particularly in regions where tech literacy has long lagged behind. It’s a reminder that AI upskilling isn’t just about national competitiveness. It’s about global equality.

The message is loud and clear: The new global divide won’t be between rich and poor countries—it’ll be between the AI-literate and the AI-left-behind.

And if you’re not investing in education now, you’re betting against your own future.

By the way, closer to home (Malaysia), AI will only be introduced to primary school starting 2027. That two years wait might be ok two decades ago, but in the age of AI, that two years could easily set us back by two decades!

Rewriting the rules of hiring.

Recruitment Redefined

While countries look to the classroom, companies are looking in the mirror—and the reflection is jarring. What they see isn’t just inefficiency or bloated operations. It’s missed opportunities. Redundant tasks. Slow decision cycles. And massive potential locked behind old workflows.

One of the most headline-grabbing statements recently came from Shopify’s CEO, Tobi Lütke, who declared: “Before hiring a new employee, managers must demonstrate that AI can’t do the job better.”

Let’s pause there. That’s not a clever one-liner. That’s a seismic shift in how modern companies think about scaling. It flips the traditional growth equation on its head.

Translation? If your workflow doesn’t integrate AI—or if it could—your job might not need a human. Or at least not in the same way.

And this isn’t just Shopify. It’s not just tech companies. It’s a growing movement—across industries—toward a leaner, smarter workforce that maximizes AI not just as a tool, but as a teammate. It’s a shift in the corporate mindset.

Amazon has already trained over 2 million people in AI—a year ahead of schedule. That includes frontline workers, marketers, data analysts, and customer support teams. They aren’t treating AI as a siloed function. They’re treating it as a language every team should speak. It’s no longer about building an AI team. It’s about making AI every team’s superpower.

IBM SkillsBuild and Google’s learning programs are also making AI upskilling accessible across all functions—not just for engineers. Think sales teams writing smarter proposals using GPT copilots. HR teams screening resumes with LLM-assisted bias filters. Ops teams forecasting demand with predictive models instead of clunky spreadsheets.

Sounds like something from the future? The fact that there are already positive ROI from the investments means it has been going on for a while behind closed doors.

AI isn’t about job replacement—it’s about job reimagination.

Don’t look at it as digitalizing tasks. We’re literally reinventing roles.

And companies that embrace that mindset are creating a future where their people do less grunt work and more high-impact thinking. Because in an AI-first world, the human edge isn’t speed—it’s judgment.

The Tariffs opened a floodgate of change.

Trump’s Tariffs Might As Well Be The Kerosene to this Wild Fire

So where does politics fit into all this?

In April 2025, the latest wave of Trump-era tariffs reignited global trade tensions. Headlines focused on the usual suspects—supply chain disruptions, inflation, import-export struggles—but beneath the economic noise, a deeper narrative was unfolding: the race for self-sufficiency.

Governments and corporations alike are being forced to ask a hard question: “What happens if we can’t access the tools, platforms, or people we rely on today?”

Suddenly, talent development isn’t just an economic priority—it’s a matter of national resilience.

If importing innovation is no longer an option, you’ll have no choice but to grow it.

And we all know the best time to plant a tree is ten years ago. And the second best time is today. Which is what countries around the world are waking up to this realization, some later than others.

Countries that once outsourced digital infrastructure are now insourcing talent strategy. It’s not just about independence from goods—it’s about independence from intellectual capital pipelines.

Suddently, the quesiton shifted from “Can we afford to invest in AI upskilling?” to “Can we afford not to?”

This mindset shift is quietly transforming national strategies across Asia, Europe, and the Americas. AI upskilling programs are being written into economic recovery plans, national security strategies, and even diplomatic positioning.

In 2025, in a world of trade wars, talent becomes the new oil.

And those who control it? They don’t just survive—they lead the innovation economy.

If you can’t guarantee access to the world’s top AI platforms or engineering labor, then your next best bet is to build it at home. Upskilling isn’t just good for GDP. It’s now a defense strategy.

The days of “cowboying” around are numbered!

Regulation Is Catching Up (and Cranking the Pressure)

If the market won’t force change fast enough, governments will.

The European Union’s AI Act, which entered into force on 1 August 2024, and will be fully applicable by 2nd August 2026, had some exceptions weaved in: prohibitions and AI literacy obligations entered into application from 2 February 2025.

It is now mandatory for any organization using AI to ensure their staff is literate in how those systems work. This includes understanding how AI makes decisions, managing associated risks, and even knowing when not to use it. This isn’t just legal fine print—it’s a wake-up call for every leader whose team is already touching AI but doesn’t yet fully grasp it.

Singapore is already ahead of the curve. Their revamped SkillsFuture 2.0 program now includes government-subsidized GenAI courses, covering everything from writing SEO content and data storytelling to creating smart workflows for productivity. They’ve even rolled out initiatives for SMEs, encouraging grassroots adoption of AI skills—not just at the top but across the entire org chart.

In Malaysia, forward momentum is growing too. National budget allocations are being funneled into AI upskilling programs for the public and private sectors alike. There’s a rising urgency to equip industries—from palm oil to pharmaceuticals—with AI capabilities that go beyond buzzwords and into actual bottom-line results.

And let’s not forget the ripple effect of regulatory influence. As global frameworks tighten—especially in tech-exporting regions—countries and companies that don’t align risk being cut off from key markets or partnerships.

The future of compliance includes capability.

Fail to build literacy, and you don’t just fall behind—you risk becoming unqualified to participate in the global AI economy.

Are leaders still having wishful thinking?

The Upskilling Gap Is A Widening Chasm

Here’s the part that stings:

A BCG study found that while 89% of executives agree their workforce needs stronger AI skills, only 6% have started taking meaningful action.

And no, that’s not a knowledge gap. It looks more like a leadership gap.

The problem is not about tech, though. It’s around trust.

Many leaders still don’t feel confident enough in their own AI understanding to champion change. They’re waiting for a “perfect” framework, a clearer ROI, or maybe just someone else to go first.

Meanwhile, McKinsey reports that AI could contribute $4.4 trillion in annual productivity—if, and only if, organizations stop dabbling in pilots and start embedding AI across daily workflows.

AI transformation isn’t just about tools. It’s about transformation of mindset.

Successful AI Enablement isn’t about upgrading platforms. It’s about upgrading people.

The real threat isn’t that your competitors are experimenting with AI—it’s that they’re building teams who can work, think  and learn with it.

The sad truth? Most companies are still playing catch-up, running training like it’s a tick-the-box compliance task rather than a strategic lever for growth.

The question isn’t “Do we need AI training?” The question is, “How far behind are we already?”

A mentor told me this a while back, and I thought it to be relevant today: “Imagine you’re still doing math by hand, while your opponents have access to calculators. Do you still want to take pride in your mental capabilities when you’re the only one left in the room with the wrong answer?”

New times. New tools. New training methods.

The New AI Learning Playbook: Shift from Static to Strategic

The way we teach AI can’t look like how we taught Excel.

That’s because while there are periodic changes to Excel, Word or PowerPoint, the capability updates of AI models and AI tools, are at a pace that most can’t even catch up.

For example, just take a look at the rapid evolution of one of the world’s most widely used AI tools—ChatGPT. Below is a timeline grouped by key categories to make the pace and focus of innovation easier to grasp:

Core Model Releases

• Nov 2022 – ChatGPT Launch

• Mar 2023 – GPT-4 Integration

• Nov 2023 – GPT-4 Turbo Released

• May 2024 – GPT-4o (“Omni”) Released

• July 2024 – GPT-4o Mini Introduced

• Sept 2024 – o1 and o1-mini Models Released

• Jan 2025 – o3-mini and o3-mini-high Models Released

• Feb 2025 – GPT-4.5 Released

Expanded Capabilities

• Mar 2023 – Plugin Support Introduced

• Oct 2023 – DALL·E 3 Integration

• Dec 2024 – Advanced Voice Mode Enhanced

• Mar 2025 – GPT-4o Audio Models Introduced

• Apr 2025 – New GPT-4o Image Generation

User Tools & Personalization

• Nov 2023 – Custom GPTs Introduced

• Jan 2024 – GPT Store Launched

• Dec 2024 – Tasks Feature Introduced (Beta)

• Apr 2025 – Persistent Memory Upgrade

Workflow & UI Enhancements

• Oct 2024 – Canvas Feature Introduced

• Apr 2025 – Enhanced Memory Feature Rolled Out

Each of these upgrades unlocked new possibilities for users and teams. And again, this is just one tool. Multiply this pace across other platforms—Perplexity, Claude, Canva, Replit—and you start to see the real challenge:

AI literacy isn’t about learning one platform. It’s about learning how to adapt, continuously.

And this is just ONE AI tool. What about Perplexity, or Claude, or Replit, or Canva (and the list goes on).

Traditional one-off workshops or static slide decks just don’t cut it anymore. That model might have worked for tools like Excel or PowerPoint, where updates were slow and predictable. But in the AI space—where tools evolve monthly and capabilities leap forward quarterly—learning needs to be agile, contextual, and built into everyday work. We’re dealing with a skill set that evolves every month.

That means AI upskilling needs to be adaptive, interactive, and embedded into real work. Because when tools like ChatGPT evolve monthly—with major feature rollouts every few weeks—training can’t be static. It needs to move at the speed of innovation, equipping people not just to catch up, but to keep up. That requires a different kind of mindset when it comes to learning.

Today’s workforce needs:

• Cohort-based learning to create shared accountability and momentum

• Role-specific use cases that show how AI boosts productivity in marketing, finance, sales, HR, and beyond

• Hybrid skill models, combining prompt literacy with critical thinking, creativity, and communication

• Microlearning sprints that evolve as tools evolve (because let’s face it—AI tools change monthly)

• “Prompt gyms” where employees can train in safe environments to improve their prompt design, tool selection, and output evaluation

Some organizations are going even further by embedding AI assistants into daily operations, acting as just-in-time learning buddies. Imagine a junior executive using a GPT-powered co-pilot to plan presentations, or a procurement officer checking AI recommendations before placing high-stakes orders.

Lenovo’s internal research highlights a key truth: infrastructure alone isn’t enough. Even companies with decent tools still struggle to unlock full productivity gains because their teams lack confidence in how—and when—to use those tools effectively.

Your employees don’t need more dashboards. They need confidence.

And confidence doesn’t come from policy documents or learning portals. It comes from experience, from experimenting, and from knowing someone’s got your back while you figure it out.

This is what modern L&D must look like: contextual, communal, and continuously evolving.

Does your workforce have what it takes to ride this AI wave?

Closing Thought: Literacy Is the New Leverage

Let’s get real—AI isn’t hype anymore. It’s here, it’s accelerating, and it’s changing everything faster than we’ve ever seen before. And if remember the timeline of ChatGPT’s updates in the previous section? That all started in November 2022. As of the time of writing, that means it’s not even 3 years old!

But in the last 3 years, we’ve seen so much advancement—more than 20 major feature updates in ChatGPT alone—that if you just woke up from a 3-year slumber, the digital world might feel completely alien. It’s not just a step forward—it’s like stepping into the future, jet-lagged and unprepared.

But the changes are not happening tomorrow. It anything, it happened yesterday.

Countries are restructuring education. CEOs are rewriting hiring playbooks. Governments are baking AI literacy into legislation.

And yet, many organizations are still waiting for a “perfect time” to begin.

But there is no perfect time. There is only now.

Waiting to upskill is like waiting to fix a leaky roof until it rains. By the time the urgency hits, it’s already too late.

AI won’t replace you. But a person who knows how to use AI just might.

And even as I write this statement, I know I’ll likely be proven wrong—because once AI agents go full force, our roles may be reinvented all over again.

This isn’t fear-mongering. I wish it is. When companies and countries are taking massive action around a groundbreaking technology, we simply can’t ignore the facts.

The organizations and nations that thrive in the AI era will be the ones who understand this truth: the only sustainable competitive edge is human capability, amplified by AI.

So what does that mean for you, the leader? The manager? The HR strategist? The learning designer?

It means rethinking the role of training from something that happens after onboarding to something that fuels daily performance. Imagine this: instead of a single onboarding module, teams go through monthly AI micro-sprints tailored to their roles—customer service reps practice with GPT-based scripts, marketers test prompt templates, and ops leads co-create automations with their AI assistant. It’s not just L&D—it’s live and direct enablement. It means treating AI literacy like digital hygiene: basic, expected, and non-negotiable.

The future of talent isn’t about having the most people. It’s about having the most prepared people.

So the question isn’t:

“Is your workforce ready for AI?”

The real question is:

“What’s stopping you from preparing them?”

Because while others are still debating AI’s impact, the smartest organizations are already building their next-gen workforce.

And in the age of AI, readiness isn’t a luxury. It’s leverage.

1️⃣ Data Privacy Issues

As AI tools sneak into our workplaces, the potential for data leaks is real. Imagine employees plugging their favorite AI apps into your company’s systems. Sounds great for innovation, but if these tools aren’t vetted, they could open the floodgates to data breaches and compliance headaches.

Capital One’s massive data breach in 2019 was a wake-up call. A simple misconfiguration allowed unauthorised access to millions of customer records. This wasn’t directly about BYOAI, but it shows how easily things can go wrong without proper oversight.

⭐ Quick Recommendations

1. Set the Ground Rules Establish clear policies about which AI tools can be used. Think of it as creating a “bouncer” at the gate of your data to keep out unwanted guests.
2. Regular Security Checks Conduct regular audits to catch vulnerabilities before they become disasters. Think of it like a routine health check for your IT systems.
3. Educate Your Team Train your employees on data privacy best practices. Make sure they know the risks and how to keep your data safe while leveraging AI.