THE 5 BIGGEST BOTTLENECKS POWERING THE AI ECONOMY
The way I'm thinking about AI winners today is that the market is moving beyond the simple question of which mega-cap company spends most on AI and has been rewarding the companies that control the scarce inputs, contracted capacity, data movement, power infrastructure, edge compute and workflow layers that make the AI economy function.
These are the five bottlenecks I'm watching most:
• Memory | $Micron Technology(MU)$, Samsung, SK Hynix
Memory is the clearest scarce input because HBM feeds the accelerator, only a few companies can make it at volume and buyers are locking in supply through long-term agreements that create revenue visibility through the end of the decade.
• Connectivity | $Broadcom(AVGO)$, $Marvell Technology(MRVL)$, $Astera Labs, Inc.(ALAB)$, $Credo Technology Group Holding Ltd(CRDO)$, $Applied Optoelectronics(AAOI)$, $Arista Networks(ANET)$
Connectivity determines whether AI clusters can move data fast enough because training runs span tens of thousands of chips that need to act like one machine. Once copper runs out of reach that causes the cluster depends on optics, retimers, switches and custom silicon to keep the system moving.
• Power | $Constellation Energy Corp(CEG)$, $Vistra Energy Corp.(VST)$, $GE Vernova Inc.(GEV)$, $Forgent Power Solutions, Inc.(FPS)$, $Vertiv Holdings LLC(VRT)$, $Navitas Semiconductor Corp(NVTS)$, $Talen(TLN)$,$ON Semiconductor(ON)$
Power determines whether new AI data centers can actually come online because the binding constraint is shifting from getting chips to getting megawatts so the value flows to the companies that control generation, grid equipment, power delivery, thermal management and efficiency.
• Compute | $NEBIUS(NBIS)$, $Cipher Mining Inc.(CIFR)$, $IREN Ltd(IREN)$, $APPLIED DIGITAL CORP(APLD)$,
$TeraWulf Inc.(WULF)$, $Core Scientific, Inc.(CORZ)$, $CoreWeave, Inc.(CRWV)$
Compute capacity is overflow layer when hyperscalers are sold out. Capital alone doesn't guarantee GPU access which is why buyers are signing multi-year contracts for clusters before they are even fully built.
• CPU | $NVIDIA(NVDA)$, $Advanced Micro Devices(AMD)$, $Intel(INTC)$, $ARM Holdings(ARM)$, $Qualcomm(QCOM)$
On-device CPU (edge compute) becomes next bottleneck as AI moves into inference, agents, PCs, phones, vehicles and physical devices.
Disclaimer: Investing carries risk. This is not financial advice. The above content should not be regarded as an offer, recommendation, or solicitation on acquiring or disposing of any financial products, any associated discussions, comments, or posts by author or other users should not be considered as such either. It is solely for general information purpose only, which does not consider your own investment objectives, financial situations or needs. TTM assumes no responsibility or warranty for the accuracy and completeness of the information, investors should do their own research and may seek professional advice before investing.
