Stocks to sell

Bubble Trouble: 7 Stocks to Sell Before the AI Bubble Bursts

With the latest wave of “AI mania” in full swing since November, you may not think that now is a time to be thinking about which AI stocks to sell, rather than which AI stocks to buy.

But while adoption of generative AI and other artificial intelligence technology is rising rapidly, suggesting a trend not anywhere close to slowing down, don’t assume that the current bubble among AI stocks is built on solid ground.

Shaky ground is a better way to describe it. The reasons for this are twofold; first, like any investment bubble related to a technological bubble (like the dotcom and EV bubbles), invariably it will end, even as the underlying driver of it (technological innovation) continues.

Second, something else has been driving this latest manic wave: the prospect of lower interest rates, which are a big positive for both tech demand for the valuation of tech stocks. If excitement about rate cuts starts fading, expect it to have a major impact on AI stocks across the board.

That includes higher-quality AI stocks, but for other names in the space, like these seven AI stocks to avoid, the impact could be more severe.

C3.ai (AI)

Source: shutterstock.com/Tex vector

During 2023, C3.ai (NYSE:AI) experienced a sharp run-up in price. The emergence of the generative AI trend, plus this AI software company’s fast move to capitalize on the trend, resulted in a wave of speculative frenzy for shares.

At one point, said frenzy for AI stock (which between 2021 and 2022 fell by over 90%) resulted in a nearly fourfold rally for shares. Over the past six months, however, even with the latest round of mania providing a boost, underwhelming results and walked-back guidance have led to nearly 40% retreat for the stock.

Yet while AI may look relatively cheap compared to last year’s highs, as I recently argued, despite the company’s touting of strong “customer engagement,” it is highly uncertain whether this will fully translate into sales growth/a path to profitability that will help justify its current valuation/send shares back to higher prices.

IBM (IBM)

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When it comes to the top AI stocks to sell, IBM (NYSE:IBM) may not first come to mind. Taking a closer look, though, it’s clear why the venerable “Big Blue” is very vulnerable if the AI bubble bursts.

Much of the strong performance of IBM stock over the past year has to do with growing confidence in the company’s AI-related growth potential.

Yet why many analysts and investors are excited about AI helping International Business Machines finally get out of a more than decade-long slump, one analyst (Jeffries’ Brent Thill) makes a strong counterpoint.

As Brent Thill recently argued, there’s a risk that slow growth from IBM’s legacy consulting business could overshadow higher levels of growth from its budding AI segment. This could limit further multiple expansion for IBM. Or worse, result in a de-rating (from 18 times to earnings, back to a forward multiple in the low-teens).

Lemonade (LMND)

Source: Stephanie L Sanchez / Shutterstock.com

AI is part-and-parcel to the “story” behind insuretech firm Lemonade (NYSE:LMND). Years before “gen AI” became a buzzword, there were high hopes that Lemonade would “disrupt” the sleepy insurance industry, with its use of algorithms and chatbots.

As you may recall, however, said high hopes for LMND stock were quickly dashed, as revenue growth slowed down and net losses accelerated. Poor fiscal results, plus the cycling out of speculative growth stocks during 2021 and 2022, resulted in a massive move lower for shares.

The “AI bubble” has led to only a partial recovery for LMND. However, it may be helping to provide support, by outweighing weak fundamentals.

If an AI sell-off takes shape, however, forecasts calling for persistent net losses could come off the back burner. These weak fundamentals/prospects could drive the stock (at around $16.50 per share today) back to prior lows (around $10 per share).

PROS Holdings (PRO)

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PROS Holdings (NYSE:PRO) operates a SaaS-based profit and revenue optimization platform for business, including for travel economy businesses like airlines and hotels.

Jumping on the gen AI bandwagon, by touting the AI features of its service, sentiment for this formerly beaten-down tech stock has shifted back to bullish in a big way.

But after a more than 50% move higher for PRO stock since last January, consider it now to be one of the AI stocks to sell. AI-related potential notwithstanding, said upside from this trend is arguably well priced-in already into shares. At current prices, PRO sells for 174.7 times estimated 2024 earnings (20 cents per share).

With “AI mania,” plus the market’s cycling back into growth stocks due to anticipated interest rate cuts), driving price action (not fundamentals), any change to either or both of these trends could result in a massive correction for the stock.

Rekor Systems (REKR)

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Last August, I called Rekor Systems (NASDAQ:REKR) one of the most overvalued AI stocks.

Shares in this provider of AI-powered transportation management software did pullback shortly after. However, following the latest AI rally, REKR is back at prior price levels.

Admittedly, there’s more to the bull case for REKR stock besides AI hype. As seen in recent quarterly results, although year-over-year revenue growth has slowed down, the company has materially narrowed operating losses.

This suggests Rekor System is better-positioned than your average “growing fast but still not profitable” early-stage company to move quickly out of the red.

Still, that may not be enough to save the day for REKR, if the AI bubble bursts. Smaller, more speculative names in the space are likely to get hit hard, irrespective of fundamentals. While an AI sell-off could create a solid entry point for a position, sit on the sidelines for now.

Atlassian (TEAM)

Source: T. Schneider / Shutterstock.com

Atlassian (NASDAQ:TEAM) is another example of the one of the “non-AI” AI stocks to sell. That is, while not an artificial intelligence company per se, the software developer has begun integrating generative AI technology into its platforms like Jira and Confluence.

Atlassian’s perceived AI catalyst, plus increased optimism about a continued rebound in tech demand, have both been a factor in sending TEAM stock around 63.2% higher over the past year.

Still, even as forecasts call for steady revenue (around 20.75%) and earnings (around 28%) growth this year, this may not be sufficient to sustain TEAM’s nearly threefold forward earnings multiple (99.9).

If it becomes clear that making Atlassian’s platforms AI-compatible won’t be a growth game-changer, if the AI bubble bursts, and/or if uncertainty over anticipated rate cuts/an economic “soft landing,” TEAM could cough back much of its recent gains, and then some.

Upstart Holdings (UPST)

Source: T. Schneider / Shutterstock.com

As the owner of a platform that uses AI to assess credit risk/underwrite loans, one can say that Upstart Holdings (NASDAQ:UPST) is a hybrid AI/fintech play.

Yet while the stock has exposure to two growth trends, beware. There is a good reason why UPST is one of the AI stocks to avoid.

Why? As noted previously, the risk/return proposition with UPST stock is not very favorable. Shares today trade for a staggering 382.5 times forward earnings. With this valuation, investors are pricing in a potential post-downturn rebound for Upstart Holdings as a near-certainty.

At the same time, there’s big downside risk with Upstart Holdings stock. There’s still the risk that the U.S. economy experiences something more severe than a “soft landing” in 2024. An unforeseen worsening of the downturn could severely affect UPST’s price performance. Until the odds become more favorable, sell/avoid.

On the date of publication, Thomas Niel did not hold (either directly or indirectly) any positions in the securities mentioned in this article. The opinions expressed in this article are those of the writer, subject to the InvestorPlace.com Publishing Guidelines.

Thomas Niel, contributor for InvestorPlace.com, has been writing single-stock analysis for web-based publications since 2016.

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