The world is experiencing an unprecedented surge in artificial intelligence (AI) investments, as governments, corporations, and individuals flock to be part of the potential revolution that AI promises.

However, history is riddled with stories of investment bubbles that exploded spectacularly, leaving many in financial crisis.

To navigate the AI boom and protect investments, there are valuable lessons that can be learned from the industry’s pioneers and the cautionary tales of past bubbles. Here are 5 such lessons:

1. Understand the Technology and its Limitations

Before engaging in any AI investment, it is crucial to understand the underlying technology and its limitations. AI is a field where advancements occur rapidly, but it is equally important to identify areas where the technology is still nascent.

“I marvel at how confident and flippant so many ‘talking heads’ are about the likely application and road to the profitability of artificial intelligence adoption — without any real understanding of the subject and with knowledge bases miles long but only inches deep,” Doug Kass, president of Seabreeze Partners Management, said in an interview with the Financial Times.

Therefore, it is essential to conduct thorough research before investing in an AI company to ascertain that it has tangible value, a solid track record, and is scalable.

2. Diversify Investments

Diversification is a golden rule in investment and holds true for AI as well. Instead of betting the farm on a single AI company, consider spreading investments across different sectors, technologies, and geographical regions.

This approach mitigates the risk of any single investment failure and allows investors to gain exposure to a broad range of AI opportunities.

“This is why ETFs are so useful as they offer access to whole sectors and do away with the risk of selecting the wrong individual stocks, either on their way up or on their way down,” Andrew Merricks, portfolio manager at IDAD Funds, said.

3. Don’t Fear Failure

Investing in innovative and emerging technologies such as AI requires a mindset that embraces failures as valuable learning experiences. The industry is so nascent that there will be a higher chance of an investment failing in the long run than in other, more entrenched sectors.

“Lots of industries go through this pattern of winter, winter, and then an eternal spring,” former Google Brain leader and Baidu chief scientist Andrew Ng told ZDNet.

Numerous AI pioneers faced setbacks and failures before reaching success, like any other sector.

By understanding that not all AI investments may yield immediate returns, investors can overcome the fear of failure and stay focused on the long-term potential. Of course, the higher potential for failure in AI investments shouldn’t be flippantly disregarded either. You can work out your preferred risk tolerance first and then choose investments accordingly.

4. Know the Risks of Speculative Hype and Excessive Valuations

AI’s potential has sparked immense excitement among investors, leading to sky-high valuations for some companies.

While optimism is generally a good thing, it is an important skill to be able to differentiate between realistic expectations and speculative hype.

Evaluating a company’s core business fundamentals, revenue generation, and growth prospects is a proven strategy to avoid investing solely based on headline-grabbing AI claims or inflated valuations. While these kinds of investments certainly can work out, such as Tesla’s incredible growth leading the EV industry, it’s vital to know the risks that they incur.

James Penny, senior investment manager at TAM Asset Management, noted that “companies that even mention the word AI in their earnings are seeing boosts to their share price.”

“I think the market has got a little bit over its skis. I’d put much larger odds on it coming down from here,” he told Bloomberg.

5. Keep Emotions in Check

Investment bubbles are often fueled by emotions like fear of missing out (FOMO) or excessive greed.

Emotional decision-making can cloud judgment and lead to poor investment choices.

Therefore, it is crucial to keep emotions in check, follow a well-defined, rational investment strategy, and avoid impulse decisions.

Steady and disciplined investing through extensive research and analysis is often key to success in the AI sector.

“I think that we’re seeing just one fad after another. It’s FOMO [fear of missing out], and more and more stocks are moving to ridiculous heights…Investors just have to be really careful,” David Trainer, founder of investment research firm New Constructs, said.

Is AI The Next Dot-Com Bubble?

The dot-com bubble of the late 1990s serves as a classic example of an investment bubble.

Countless investors poured their funds into internet-based companies that promised revolutionary, groundbreaking technology.

However, when the bubble burst in 2000, many investors suffered significant losses.

Some market pundits, including veteran economist David Rosenberg and experts from Wall Street names such as Bank of America, UBS and TAM Asset Management have likened the surge in AI tech shares to the boom in internet-related stocks.

“This type of corporate behavior is not too different from what took place in the dot-com bubble, with company after company satisfying investors’ appetite for news on how it plans to incorporate the internet into its business — or boosting stocks just because they added ‘.com’ to the name,” veteran economist David Rosenberg wrote.

On the other hand, some market experts have noted that there are a number of distinct differences between the dot-com bubble and the surge in AI stocks that is currently happening.

Jeremy Siegel, a Wharton finance professor, mentioned that during the dot-com era, there were “tremendous valuations from companies that had no earnings.”

“In 1999, company valuations and crazy P/E ratios were based on completely unproven theories of immediate realizations around the internet by companies that never materialized,” Dan Raju, CEO at fintech and brokerage firm Tradier said.

By contrast, “in 2023, we are seeing the realizations of AI benefits “right-here, right-now” by companies, he added.

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