AI stocks are taking off. Here's everything you need to know before investing in this emerging technology sector.
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00:00 AI is expected to boom into a trillion dollar industry in less than 10 years, and stocks
00:07 in that sector are already taking off.
00:10 If you had invested $1,000 in NVIDIA five years ago, it would have been roughly worth
00:15 $20,000 today.
00:17 I'm Laila Maidan, and I cover all things finance.
00:20 So let's talk about how you can invest in AI.
00:23 AI is disruptive technology.
00:26 This means it's an innovation that comes to market and changes everything, the way we
00:30 live, work, and do business.
00:33 Some past examples include electricity, the internet, and smartphones.
00:38 These shifts don't happen often, but when they do, they create incredible investment
00:43 opportunities, and those who understand that can make smart bets and reap exponential benefits.
00:49 In the past, it was mainly Wall Street that benefited from this, but with the creation
00:53 of investment apps, it allows you to buy stock right from your phone, so now anyone can jump
00:58 in.
00:59 So what stocks should you be investing in for AI?
01:02 Well, we can ask ChatGPT, but I've also done the research.
01:06 The development of AI itself has different types of technologies that actually go into
01:11 it.
01:12 This creates a lot of subsectors of AI that we can invest in, one of which is quantum
01:17 computing, which solves complex problems faster than a regular computer.
01:22 Sectors under this include Wipro, MediaTek, Nokia, and Mitsubishi.
01:29 Another sector is machine learning.
01:30 This is the part where we train AI to have human intelligence so it can solve problems
01:35 like we do.
01:36 Here we have ASML, Lam Research, and Onto Innovation.
01:41 AI chips is another sector you can invest in.
01:43 These are little pieces of hardware that can process large amounts of data.
01:48 Sectors in this area include Advanced Micro Devices, Marvel Technology, NVIDIA, and Tower
01:53 Semiconductor.
01:54 Then there's the sector that makes GPUs.
01:57 This is the kind of hardware that creates the graphics, the videos, and the effects.
02:01 In this area, we've got names like Applied Materials, Qualcomm, and Microsoft.
02:07 The next sector is big data and cloud computing.
02:10 This is where data is stored, processed, analyzed, and accessed over the internet.
02:15 Here we have names like MicroStrategy, Juniper Networks, and Micron Technology.
02:21 And then there are the really big players in AI.
02:24 For example, take Microsoft that invested $10 billion in OpenAI, which is the company
02:29 that built ChatGPT.
02:31 And then Google's developing a bunch of its own versions of AI to plug into various products
02:36 that it offers.
02:37 You should also be paying attention to a few of the under-the-radar stocks, like Adobe,
02:42 which is one of the companies that's integrating AI's capability into its programs so that
02:47 you can create images from just a text prompt.
02:50 And then there's a small database and cloud company called MongoDB, which feeds data into
02:55 the AI.
02:56 And a lot of fund managers like this one.
02:59 If you don't want to get into the nitty-gritty of picking and choosing stocks, exchange-traded
03:04 funds, or ETFs, are one way to go.
03:06 They're a basket of stocks that are pooled together for a particular sector.
03:10 It could be AI, and they're managed by professionals.
03:13 Everyone wants a piece of the AI pie, or so it seems.
03:16 But actually, we could still be in the very early stages of adopting this technology.
03:22 Let me show you where we are along what's called the S-curve of adoption.
03:26 These are five stages which represent how technology is adopted by the population.
03:32 Adoption happens slowly at first, with the innovator stage being the early stage.
03:37 This is where people are taking the technology and working with it to create applications.
03:43 And then there are the early adopters.
03:45 These are people that catch on to this technology and they're curious, so they start experimenting
03:49 with it.
03:50 Chances are, if you're watching this video, you could be an early adopter.
03:54 The three stages that come after that are the early majority, the late majority, and
03:59 the laggards.
04:00 These are people that didn't want to adopt the technology, but they had no choice.
04:04 While there's a lot of discrepancy for where we might be along the curve for AI, a lot
04:08 of experts believe we're still in the innovator stage, very early on.
04:12 This means there's still a lot of time to invest in AI.
04:15 But it's an innovative technology, which makes it highly speculative, and that could make
04:19 it really risky.
04:21 So ideally, it should be a small percentage of your portfolio.
04:25 Let's go back to the dot-com boom.
04:27 A lot of excited investors threw a lot of cash at companies that pegged themselves to
04:32 dot-com.
04:33 Kind of like the AI hype now.
04:36 But many of these companies failed.
04:37 They went bankrupt, they got beat out by competitors, and we ended up with the dot-com bubble.
04:43 The Nasdaq, which is an index that tracks technology names, fell by 77 percent, and
04:48 it took it 15 years to get back to that peak.
04:51 But the companies that were successful went on to be some of the biggest in the country.
04:56 Now AI might be even bigger than the internet.
04:59 It's expected to boom to $1.3 trillion in 10 years from where it was in 2022, when it
05:07 was at $40 billion.
05:09 And we may be in the same predicament today as we were during the dot-com years.
05:13 We're not 100 percent sure who the winners will be, but we have some idea of who's innovating
05:18 and developing the grounds for this technology.
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