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Generative AI is having a blazing moment in the sun. Microsoft (MSFT) ignited the spark in November, when ChatGPT captured more than one million users just five days after launching—a benchmark that took Netflix (NFLX) over three years to achieve.

What’s more, the ChatGPT juggernaut shows no signs of abating. Nine months in, 100 million-plus people have logged onto this technology to access the highly detailed, personalized content it offers in real time. They’re embracing the service at a dizzying rate—three times faster than they did TikTok, 10 times faster than Instagram. And buoyed by that overwhelming response, Microsoft is reportedly sinking $10 billion into ChatGPT’s parent firm, OpenAI.

Now, the floodgates have been breached: Alphabet (GOOG, GOOGL), Meta Platforms (META), Alibaba (BABA) and other major names are muscling in on Microsoft’s territory, competing on the basis of tweaks, broader reach or different audiences. And by one calculation, 500 startups plan to release some form of generative AI, attracting a hefty $11 billion so far for their efforts. It’s too soon to say if there’s a maverick out there building a better product, but what is certain: Copycats without something original to offer won’t cut it.

All this frenzy raises burning questions for investors: How will the state of play unfold? Is this a crypto moment, fraught with nausea-inducing ups and downs? Or is it an iPhone moment, an inflection point in tech that can pay off big time for those who get in on the ground-floor?

Skeptics and optimists face off

The jury’s still out. Cynics see good cause for comparing generative AI to crypto. For example, both technologies are massive power hogs. In fact, some estimates suggest that one million ChatGPT queries daily tax the energy grid to the tune of $3 million a month. That’s a major downside in an era focused on sustainability.

Also, Open AI is facing ethical issues and legal quagmires that make the faint-hearted wary. Comedian Sarah Silverman and others have already filed a class action lawsuit against the company and Meta for copyright infringement. Similar challenges may follow touching on questions of privacy and accountability.

Generative AI evangelists, for their part, dismiss these concerns. They cite the tech’s game-changing ability to write code, reshape marketing and permanently alter the way we work. They acknowledge the fad factor but also point out that strong science is backing the phenomenon and that its impact—immediate and dramatic—is likely to last. They see great potential for commercialization as long as legal and other hurdles can be resolved. And they channel Barclays, the international bank, which predicts that generative AI will be embedded in every consumer app within three years.

Certainly, for accredited investors with a healthy appetite for risk, there are some intriguing options, such as Synthesia, a private firm that uses generative AI to conjure up videos from scratch. Another is Soundraw, which uses masses of data to produce royalty-free music.

The right-sized gamble: spin-offs, accessories and accelerators

But not everyone can stomach uncertainty. A good strategy for cautious investors waiting for the buzz to die down? Look to enterprises with the props, products and underpinnings that support the proven winners in generative AI today and that will help the technology improve. They fall into several broad categories and you’ve likely heard of them before:

• Chip wizards: Firms that stand to do well are leaders developing chips and other hardware with the juice to handle Gen AI’s massive computational demands in an energy-efficient way. One name that frequently comes up: Nvidia (NVDA).
• Cybersecurity innovators: Crooks and scoundrels can manipulate Gen AI to ruin reputations, steal identities and defraud unsuspecting victims. Companies helping the systems stay one step ahead of these threats will do much to help them flourish. Those with a track record include Palo Alto (PANW), Fortinet (FTNT) and CrowdStrike (CRWD).
• Data mavens: ChatGPT is by no means infallible, occasionally producing embarrassing errors. Case in point: During the product launch, it famously fabricated some numbers in Gap and Lululemon earnings reports. It’s going to take the heft of firms like IBM (IBM) that have dealt in massive datasets for decades to help generative AI companies avoid such awkward and possibly litigious mistakes. Informatica (INFA) is another enterprise with experience in verifying documents and sources.
• Cloud purveyors: Generative AI needs a lot of elbow room in the cloud to thrive. Amazon (AMZN) is building its own generative AI machine, but it’s also prepping the cloud for an onslaught from others in the field. The company is investing mightily in its AWS Generative AI Innovation Center designed to help others in the business succeed.

The big takeaway here: It’s difficult to identify a gamechanger while the game is still in play. So think hard before picking Gen AI winners or losers if you’re uncertain of the odds. On the other hand, every game needs equipment. Investing in the gear that keeps the players on the field may well be the way to go.