Morgan Stanley’s AI WARNING: How to Protect Your Portfolio

According to Morgan Stanley, 90% of jobs are likely to be impacted by AI, whilst the world's biggest companies stand to gain nearly $1 trillion per year in cost reductions and revenues. Meanwhile, industry whistleblowers are issuing grave warnings that the consequences could be far more severe than anyone in power is letting on. Cancer, poverty, climate change, mental health, democracy, universal basic income, cure a bunch of diseases, this cancer and that one, and heart disease, universal extreme wealth for everybody. It's hard to know what to believe and even harder to know how to protect yourself financially. I'm James. I'm a former professional trader turned financial educator, and in this video I'm going to show you how to build a portfolio that replaces your income if the worst happens and still beats the S&P if it doesn't. So social media would have you think that unemployment was already about 20 or 30%. It was like the Great Depression. But in reality, you can see from the point that GPT was released here how the top quartile of jobs, so those that are most exposed to AI, has not risen above those with no exposure. So is it a red herring and is it all overblown? We actually need to look into some of the lead indicators here, which tell a different story. If you look at the percentage of unemployed people who are between 20 and 24 who also have a university degree, these are the guys that are struggling because entry-level jobs requiring intellect are being very easily replaced by machines, just as programmers will tell you. And you can see the chart here. So I've put together the ratio of recent graduates compared to the overall unemployment rate and how in red the ratio's rising. And you might be sat there thinking, well, as much as I wish I was 21 again, I'm glad that I'm not in this mess. Pay attention to this chart. This is released by Anthropic, the maker of Claude. And what this shows is the observed versus the theoretical AI coverage or disruption by industry. We're only seeing the tip of the iceberg in terms of the potential disruption Everybody is affected here. And if you happen to be married, educated, and earning pretty good money, then you are most exposed long-term to the threat of AI. Which raises the obvious question, what do we actually do about it as investors so that when the machines win, we win too? And this is where most investors will go wrong when they start reaching for the obvious names, whether it's the big platforms, the NASDAQ, or going all in on OpenAI when IPOs. So what do we buy? We can't be looking at broad ETFs like the S&P or maybe even the NASDAQ because as much as 72% of the overall market cap is likely to be disrupted by AI, and that's up from just 12% in 2023. So this risk is accelerating, and as much as $20 trillion or half of the S&P 500's market cap could be at risk, just to put that in context. If you look at the divergence between semiconductors and software, for example, the market suddenly realized that AI could do software for free, basically overnight. And these companies lost $300 billion in just one day. And by the end of the month, they were down a trillion in market cap. Semiconductors have continued to rise as beneficiaries of the theme, whereas software has plummeted. So even within tech, you need to be selective. And in order to do this, you can look at the so-called picks and shovels approach, similar to what people did during the gold rush, power infrastructure, grids, that kind of thing. And of course, semiconductors within this, the chip makers. So there'll be a link in the description to a report that I've put together with some of the outstanding names according to each of the categories that I'm about to walk through now and how that has translated into serious outperformance compared to investing even in the Nasdaq. And I think this divergence is set to intensify. So here's the model, the 7 factors that you've probably seen in my other videos before. I won't go through each of the points here, but just a selection of them. Essentially, we get this radar chart, this footprint, and the broader this is, the better quality the stock is according to these 7 parameters. So the first example I want to highlight, you've probably heard of because it became the world's most valuable company earlier this year. Nvidia. It excels especially in efficiency, Profitability is very high and it reinvests a hell of a lot of its cash, which is helping it to scale at the pace that it is. This is the growth in sales. This is profitability. So in terms of free cash flow, and then you've got the return on invested capital, which is the ability for the company to turn $1 of profit into, in this case, $1.78 and continue compounding at a 78% rate internally, which is how these companies become incredibly rich and how you become rich as a shareholder. As this chart demonstrates, with $10K invested 10 years ago turning into $2 million compared to just $35K for the NASDAQ. And that's the NASDAQ, it's still gone up a fair bit. Another example would be ASML. So specialist in lithography machines. They own a niche in this market and they serve the likes of Taiwan Semiconductor, Intel, Samsung, and the rest. And this translates into the earnings as you would expect, growth in sales, growth in profits, and also a high rate of internal reinvestment, which is key to growing profits long-term. The third and final example here is in monolithic power systems, focusing on improving energy efficiency within these technologies and ultimately chip manufacturing. All kinds of industries, surging revenues, surging profits, and very attractive rates of reinvestment. Once again, that's what the share price is doing whilst the rest of the market is doing that. Now, it's one thing knowing what to buy, but what about valuation? Because amidst the hype around AI, there are some genuine fears of a tech bubble rivaling that of the one that we saw in the dot-com bust. But once you understand the fundamentals and what the valuations actually mean, it becomes much easier to navigate. So to put this in perspective, you can see what people are worried about. Nearly 30% of the S&P 500's market cap is concentrated in the so-called Magnificent Seven, which are predominantly tech companies, and that's at an all-time high. But compared to the dot-com bust, those Magnificent Seven companies are all profitable. Back in 2000, less than 15% of them were, and you had the likes of Pets.com, which was only around for one year, because it was valued at nearly $300 million despite being net negative on everything it sold, meaning it lost money, and spending nearly $12 million on advertising to generate revenues of just $600,000. This is the free cash flow of a number of the top semiconductor companies, and it is a very different picture. To what we've just seen. But then people will look at the multiples and go, well, okay, they might not be in a bubble, but surely they're bloody expensive. Just look at the PE ratios. Well, sure, Nvidia's at a PE of nearly 50, similar to ASML, and down at the bottom, Analog Devices at 65 times earnings. But what people are doing is falling into the mistake of comparing apples and oranges. They're not comparing like for like. And in this example, we're comparing Apple, albeit not a semiconductor name, it's kind of a bit tech versus a company in healthcare called Organon, I believe it is, or something like that. They're both in the S&P 500, but they're completely different companies. So the fact that Apple might trade at 35 times earnings doesn't mean that it's expensive compared to a crappy healthcare company that happens to be trading at one-third of that. There is a reason why. and it's based on the company's fundamental prospects. Apples and oranges. But in this case, you can see Nvidia compared to Broadcom, both in the same industry. So apples with apples. But the third way of doing it, which I always like to do at the end, is to look at the stock compared to its own valuation history. And right now, contrary to that headline multiple of 45, 50 times, depending on whether you're looking at cash flow here or earnings as we looked at earlier, you can see that it's actually below its 10-year median. So it's relatively good value according to history using this measure. So in none of those 3 examples have I seen anything to suggest that Nvidia looks historically expensive. There's a famous story going back to the '90s, mid-'90s, where this new kid on the block known as Pepsi, you might have heard of them, Traded at 30 to 40 times earnings, and whilst it was shaking things up and it had some pretty good prospects, a lot of investors shunned it because they felt it looked simply too hot to handle, too expensive, certainly compared to Coke. So let me show you how this played out. At the time, earnings per share were $1 and the price range was $30 to $40, and hence 30 to 40 times multiple. It, however, remained at around that level within that range from the mid-'90s through to the present day. So what this means is that stocks that trade at a premium not only trade at a premium for a reason, because as you can see, the growth transpired for Pepsi and it grew into that valuation, but they can remain in that same range indefinitely. And there you can see the divergence from Coke. And what that translated into is incredible dividend growth with all of that excess cash left over from booming sales and profits that would in fact have repaid your initial investment having received $40 in dividends going back to that price point of $30 to $40 back in 1995. So it would be a free trade now and you'd have still enjoyed all of the price appreciation. So combining the two for total return, you can see how that translated into significant outperformance and how valuation is often looked at in completely the wrong way. But being a great stock picker won't save you unless you're following the right plan. And a lot of people end up completely missing their goals because they don't know how much they should be investing or whether they're still on track. So that's what I'm going to show you next, how to work out exactly how much you need to put in and how quickly you can replace your income before it's too late and the robots are taking our jobs. So here's the tool that I've built to help you do that. So at the top You have your annual income, your starting portfolio, your savings rate, and then down at the bottom, your expected return. And then the disruption horizon. We'll get into this in a minute. It's going to tell us whether or not we will be on track to replace £85,000 a year with savings of £100,000 invested. We're going to be behind the pace looking to replace even just one-third of our current salary, never mind half of it. On all of it. So what we need to do therefore is look to increase the savings rate. And this might sound like a lot, but the point to emphasize here is that we don't have a lot of time left. But what if we bumped that up to say 12.5%? So we get a 2% edge, whether that's afforded by investing in tech or through picking quality stocks within the S&P. Well, again, we're still going to be behind here. So this isn't going to be easy, guys, and the point of this video is not to lull you into a false sense of security here. It's It's emphasizing how important it is to take action now, especially if you don't have a vast amount saved and you're not able to contribute, you know, 30 or 40% of your income. So if you're not having sleepless nights and waking up every day anxious to figure this out, then I might well be on my own. But for the reasons I've laid out here, I hope you can see why you need to act immediately to stand any chance of capitalizing on this and replacing your income sufficiently. I'm honestly not sure I'll be employable 3 years from now, but thankfully I've already followed the right steps. So watch this video next, which explains exactly how I did it. Don't forget to check out the link in the description for the report too.