Back in 2024, OpenAI CEO Sam Altman sent Wall Street into a frenzy with a single blog post.
He made the boldest claim about AI’s future yet: “We believe that, in 2025, we may see the first AI agents join the workforce and materially change the output of companies.”
He didn’t stop there.
He also told the press that entry-level positions would soon be handled by AI interfaces working behind the scenes – completing tasks that mere humans might take hours to do.
He even fueled another big AI dream: That artificial general intelligence (AGI) – where AI surpasses human ability – was right around the corner.
You can connect the dots from there. Beyond-human intelligence permeating every aspect of business. That’s when humans (seemingly) become obsolete.
Back in 2024, the sky certainly looked to be the limit. Investors were sizing up the AI competition. And they all appeared to agree on one thing…
2025 was supposed to be the year AI finally took over. The year every small and large task we can think of gets the AI treatment.
Well, it hasn’t quite been the watershed year that transforms everything in AI’s image (more on that below).
But if you’ve been following Masters in Trading, you know AI’s market momentum is nothing to sneeze at .
Over the last eight months alone, I’ve put several massive opportunities on your radar – including five of the biggest AI stocks I’m watching right now.
And we haven’t been sitting on the sidelines this year.
I’ve helped viewers collect double- and triple-digit gains from some of the biggest AI players around.
Just last year, we banked gains of more than 200% and 400% trading C3.ai – one of the biggest AI startups in the game.
We’ve also managed massive triple-digit winners on stocks that are fueling AI on the supply side. That includes pure metals plays like The Metals Company (TMC) and MP Materials (MP) helping us stay right on the pulse of the AI build-out.
So yes, AI is certainly no flash in the pan, but the technology is in the middle of some serious growing pains.
And it’s critical that investors move with caution through the industry to avoid getting sucked into a hype trap.
A Lesson for Early Investors
Look, Sam Altman isn’t entirely off the mark. I believe the future truly belongs to AI.
Over the last few weeks, I’ve been putting trends like AI smart glasses on your radar because the opportunity here is simply too big to ignore. (You can read all about my favorite investments in AI smart glasses right here.)
But if 2025 has proven anything, it’s that AI is a long way from replacing the human touch.
Take finance startup Klarna.
Klarna is one of the largest suppliers of “buy now, pay later” microloans – basically tiny cash advances for purchases that don’t need to go through a bank.
Over the last year, Klarna made a risky bet on its future with AI.
The Swedish company was an early adopter of “AI agents” – machine learning software supposedly capable of handling complex tasks on its own.
The problem? Even the best AI agents remain extremely inefficient.
Researchers at Carnegie Mellon University recently found that even the best-performing AI agent, Google’s Gemini 2.5 Pro, failed to complete real-world office tasks 70% of the time. It could only partially handle tasks like responding to colleagues, web browsing, and even coding.
And those competing AI agents? They all did significantly worse when it came to completing similar tasks:
- OpenAI’s GPT-4 had a 91.4% failure rate
- Meta’s Llama-3.1-405b failed 92.6% of the time
- Amazon’s Nova-Pro-v1 earned a near-100% failure rate
Most might be put off by those numbers. But Klarna certainly wasn’t fazed by the data.
So they opted for OpenAI’s model – and predictably, the results were less than satisfactory.
Rather than introducing tech that could “replace 700 agents” as Klarna’s CEO had claimed, the AI was failing to complete almost any task handed to it.
Customers flooded the lines with complaints about unanswered queries. New products were being added to customers’ subscriptions without their consent.
A laundry list of problems suddenly became the norm – and it was totally unsustainable.
It’s no surprise what happened next. Klarna CEO Sebastian Siemiatkowski did a complete about-face.
Source: The Verge
Back in May, Klarna started scrambling to rehire the full-time workers and contractors they’d axed.
But rehiring a whole department is a lot harder than firing them.
Klarna’s recruitment drive is ongoing as I write to you.
It’s safe to say they’ve learned a painful – and financially unpleasant – lesson. And now other companies are starting to dial back their AI-everything plans.
A recent Gartner survey found that out of 163 business executives, half said their plans to “significantly reduce their customer service workforce” would be abandoned by 2027.
If we take a deeper look at AI in 2025, it becomes even clearer just why these implementations keep failing…
Just look at the Gartner’s “Hype Cycle” chart below. The model that shows us how new technologies typically progress from early excitement to realistic adoption. It’s used to visualize where a given technology stands in terms of maturity, visibility, and real-world usefulness.
Source: Gartner
AI Agents – the exact tech Klarna bet on – are sitting at the “Peak of Inflated Expectations.” That’s the danger zone where reality hasn’t caught up to the promises yet.
Meanwhile, technologies like Foundation Models and Cloud AI Services are already moving through the “Trough of Disillusionment” toward the “Slope of Enlightenment.” That’s where real, practical value starts emerging.
This chart tells us everything we need to know about where we are. We are still very early in this game.
Some technologies won’t reach their productivity plateau for years to come. Others are obsolete before they get there…
So as investors and traders, it’s our job is to identify which players will survive the trough and climb to the plateau.
The Real Future of AI
None of this means that AI isn’t working. Far from it.
But we need to align our expectations for where we are in the cycle.
In the immediate future, the best use cases for AI look a lot like what we’re already doing with it – but better.
AI is revolutionizing diagnostics by detecting cancers, analyzing X-rays, and identifying patterns human doctors might miss.
Companies building AI-powered diagnostic tools are saving lives and improving efficiency in healthcare systems worldwide.
And all that AI-powered insight is trickling down to the wearables as well.
From real-time translation to augmented reality navigation, AI-powered wearables are enhancing how we interact with the world…
This isn’t about replacing human interaction — this is about amplifying it.
Just consider how AI can overhaul the way we learn.AI tutoring systems are personalizing learning at scale. They’re helping to address individual student needs in ways traditional classrooms can’t. This isn’t replacing teachers – it’s giving them superpowers.
It’s the same in the creative space.AI is helping artists, writers, and designers work faster and explore ideas they couldn’t reach alone. It’s collaboration, not replacement.
These aren’t pie-in-the-sky promises. These are real applications delivering measurable value today.
That brings me back to OpenAI. Many of you probably know the firm is essentially headquartered within Microsoft.
And even as Sam Altman has been outspoken about AI’s future use cases, the fact is their biggest product, ChatGPT, isn’t replacing “all human work as we know it” yet.
It’s enhancing what we can already do.
For some time now, AI has been an integral part of the various tools I’ve built out for members of Masters in Trading.
It’s an invaluable helper — an assistant that can help me speed up tasks, transforming tasks that once took weeks and days to just a few hours.
Back in July, I built out a tool that lets me see in real time how much ETH a whole range of stocks are adding to their corporate treasuries. If you’re interested in learning more about how I put that tool together – and my whole ETH trading approach – you can check it out right here.
I did a lot of the legwork. But getting it all working and finished for my viewers? That was sped up by AI.
And think about my Unusual Options Activity Scanner . I came up with the basic concept years ago and built a lot of it from scratch.
But recently AI has been there to help me map out tweaks the UOA Scanner work more efficiently to uncover spikes in options trading volume.
In fact, I put together a whole video recently showing viewers what big plans I have in store for the software. And it’s all fueled by AI.
The Hedge Fund Advantage — Without the Hedge Fund
And speaking of where AI making us better — not in theory, but in practice — I want to put something powerful on your radar.
Earlier this week, my close colleague and TradeSmith CEO, Keith Kaplan hosted one of the biggest events in our corporate partner’s history with nearly 10,000 investors in attendance.
has quietly been building a “Super AI” system that’s already rewriting how everyday investors approach the markets.
For decades, hedge funds like Citadel and Renaissance Technologies have used advanced algorithms to stay on top of the markets. Citadel alone made $16 billion in profits in 2022 — the largest one-year haul in hedge fund history.
And now Keith and his 74-person research team has found a way to put that same level of data science into your hands.
If you missed the broadcast, you can watch the full replay here before it goes offline and find out how this new form of AI could quadruple your portfolio by foreseeing the future prices of 2,334 different stocks, to the penny, with 85% backtested accuracy.
The Supercharging Potential of AI
This is the key to understanding where AI sits right now. It’s not about taking humans out of the equation.
Any good assistant or staffer always needs insights from the boss. There’s an exchange happening. Your expertise is always part of the equation.
And the biggest players already understand this…
As regular readers know, my confidence in the big players – Microsoft, Amazon, Google – hasn’t wavered.
These are the best-positioned companies to succeed because:
- They’re the best capitalized
- They have the resources to acquire startups (which is likely what’ll happen to most AI companies)
- And they’re building broad toolsets for individuals and enterprises – not pure replacements
The biggest incumbents are the ones taking AI to the next level.
And they’re the ones really driving AI’s big moment…
AI has been dominating Wall Street since the launch of Microsoft and OpenAI’s ChatGPT in November 2022.
That’s the point here. The biggest players have the greatest chance of success.
True, there are a lot of startups fueling the hype cycle right now. And like I mentioned at the top, we’ve managed some big wins trading some of those names.
But just like the dot-com boom, only the incumbents and a handful of disruptive companies will become the kingmakers in the AI race.
That means the AI hype train is leaving the station where most of those startups are concerned.
And even the most well-capitalized players won’t necessarily represent the biggest winners.
The truth is, we have go even deeper to find the biggest opportunities.
Don’t Get Caught in the Hype
The most reliable names are still the best. The ones who are regulatory-compliant, already have massive consumer bases, and have resources to keep iterating without worrying about funding – those are the ones who’ll succeed long-term.
There are a handful of AI stocks I’m watching that could make serious strides and become the next Microsoft – or at least get acquired by the incumbents.
But just like I’ve told you in the past, the big names aren’t where the opportunity truly lies. It all comes down to the key suppliers driving the boom in chips, data centers, and more.
These are the stocks I’m watching with the biggest potential: NVIDIA (NVDA), Broadcom (AVGO), Marvell (MRVL), AMD (AMD). Each one represents the muscle behind the AI build-out.
They’re the players supplying chips to GOOGL, MSFT, and many more. And they’ll continue to set the key benchmarks for the global AI race.
I want every investor to keep this megatrend on their radar.
And if you’re looking for exposure while avoiding the hype, one of the best places we can look to is institutional options flow. These are the type of objective signals I teach my members how to spot inside the Masters in Trading Options Challenge. If you’ve ever wanted to learn how to read the market the way I do and leverage these signals for outsized gains — this is where you start.
If you’ve been keeping up over the last few weeks, you know AI has been a huge part of our trading approach.
Today, I want to make it clear: The efficiencies and gains AI will drive are not to be underestimated.
We’re just at the earliest stages. That means it’s far too early to consider automating entire positions out of existence.
For traders? It’s even better. We’re on the ground floor watching AI take off.
Now is the time to strike.
You can find the top AI stocks I’m watching and recommending daily on Masters in Trading LIVE.
Remember, the creative trader wins.
