Advanced Micro Devices (NASDAQ:AMD) top boss Lisa Su is worth investing in, especially for the AI bulls out there who want to bet on the future of a fast-moving AI chip giant that has what it takes to keep up with the likes of the great Nvidia (NASDAQ:NVDA).
With Lisa Su remarking that AI is the “right gamble,” seemingly in response to growing market-wide skepticism over heavy AI spending, I do think that Advanced Micro Devices stands out to be a big winner in the new year, even if times seem a bit uneasy for the AI trade of late.
Can Advanced Micro Devices really grow 35% per year over the next several years amid the AI boom?
As to whether Advanced Micro Devices will be able to clock in 35% in annualized revenue growth over the next five years (on the high end) remains the big question mark. If the next generation of MI300 accelerators sells well and corporate adoption of AI accelerates further, I think there’s still a chance that sales will surprise to the upside. Either way, the bar has been raised rather high, and, like with Nvidia, it might prove tough to keep pole-vaulting the bar by enough to nudge the stock significantly higher from current levels.
In short, the company is firing on all cylinders, but the valuation, at least in my view, has had ample opportunity to catch up, with shares of Advanced Micro Devices currently going for a rather lofty 126 times trailing price-to-earnings (P/E) multiple at the time of this writing.
Looking ahead, the shares go for 40 times forward P/E, making them seem cheaper, but, at this juncture, I think there are better deals to be had in the AI scene as shares begin to enter what appears to be a seasonal rotation out of growth and into some of the more defensive plays.
It still makes sense to own Nvidia and Advanced Micro Devices together
While Nvidia is still comfortably in the lead, I do think that it’s only prudent to own shares of both AI chip darlings, not only because they both can win from the AI revolution, but because the trajectories and expectations might fluctuate wildly over time. In the past year, shares of Advanced Micro Devices have topped those of Nvidia, gaining an outstanding 99% (even with the latest AI pullback considered) compared to Nvidia’s modest 35% gain.
Undoubtedly, I thought Nvidia’s numbers were profoundly strong, while Advanced Micro Devices were robust, but certainly not jaw-dropping. Still, it seemed like expectations were higher for Nvidia while they were relatively tame for Advanced Micro Devices going into the year.
As Advanced Micro Devices’ RDNA architecture looks to pick up ground in gaming (it’s going to be in the next Steam Machines gaming PC/console hybrid), while the next generation of AI accelerators looks to hit a hot market, there’s really no telling how much ground Advanced Micro Devices will gain as shares of Nvidia look to flatline a bit in a move that suggests the name needs a bit of time to digest the meteoric gains from the past five years.
AI spending comes with risks, but the potential rewards are also considerable
In the meantime, Su seems to acknowledge that heavy AI spending comes with a degree of risk. At this juncture, it seems like many investors are re-evaluating those risks by punishing heavier AI spenders, like Meta Platforms (NASDAQ:META), as they begin to question the return such investments will get. Is there a chance that AI overspend leads to sub-optimal returns and significant cash bleed over the medium term?
Most definitely. But for now, AI seems like a “gamble” with the odds favoring the heavy spenders, at least in my view, especially if 2026 sees some of the big spenders provide clarity on growth and profitability prospects at the hands of AI. Given all that there is to gain from AI, I’m with Su in believing that AI spending is the right “gamble” to make, as AI demand looks to become “insatiable.” At the end of the day, Su is an industry visionary whom I wouldn’t dare bet against.
For now, heavier AI spending might entail a high-risk, higher-reward kind of proposition. Though, the timing of such rewards seems highly uncertain right now. At the very least, firms can pivot accordingly by cutting AI spend and another so-called “year of efficiency’ if needed.
Given the potential for AI spending to lead to far greater AI-related cuts in the future, I’d be less concerned about the big spenders, given the brilliance of their leadership and their agility to pivot very rapidly.