Dan Ives says Microsoft and Meta are being treated like 'bear market' stocks
Microsoft Corp. and Meta Platforms Inc. are facing significant investor pressure despite spending hundreds of billions on AI infrastructure. Wedbush analyst Dan Ives describes the market as being in a "Twilight Zone" where investors reward immediate beneficiaries like Micron Technology Inc. while punishing hyperscalers funding the development. Ives notes that $700 billion in Big Tech cap-ex is fueling the AI buildout, but investors are frustrated by the lack of immediate returns, treating Microsoft and Meta like "bear market names." Despite this, Ives maintains a positive long-term outlook, calling the current weakness "short-term pain for long-term gain" and emphasizing that the AI revolution is only in its third year of a projected decade-long buildout.

*this image is generated using AI for illustrative purposes only.
Microsoft Corp. and Meta Platforms Inc. are spending hundreds of billions of dollars to build the artificial intelligence infrastructure powering the next generation of computing. Yet, according to Wedbush analyst Dan Ives, investors are rewarding the companies selling the picks and shovels while punishing those footing the bill. This dynamic has become especially evident following Micron Technology Inc.'s recent earnings, which reignited enthusiasm for AI memory stocks even as Microsoft and Meta continue to face heavy selling pressure.
Ives described the current market as a "Twilight Zone," arguing that investors have become increasingly impatient with hyperscalers waiting for their massive AI investments to translate into meaningful revenue growth. He noted that $700 billion of Big Tech capital expenditure this year is fueling the AI buildout, causing frustration among investors regarding the patience required for Microsoft and Meta to see returns. The analyst stated that these companies are being treated "like they are bear market names that cannot be owned," even though they remain central to the Fourth Industrial Revolution.
Market Rotation Favors Immediate Beneficiaries
Instead of buying the companies building AI platforms, investors have rotated into beneficiaries such as Micron and other AI infrastructure names that are already seeing stronger demand and earnings momentum. Ives believes the divergence reflects timing rather than fundamentals. Memory suppliers and infrastructure companies are benefiting immediately from the AI buildout as hyperscalers race to expand data centers and computing capacity.
Meanwhile, companies such as Microsoft, Meta, Amazon.com Inc. and Alphabet Inc. are still waiting for those investments to generate the next wave of monetization. "Meta is essentially looking to transform its business and that requires massive investments that will take some time to hit numbers," Ives said. That gap has encouraged investors to favor companies with more immediate AI revenue catalysts, even as hyperscalers continue to finance the industry's expansion.
Long-Term Outlook Remains Positive
Despite the recent divergence, Ives believes investors are becoming too focused on short-term uncertainty. The analyst argues the current weakness in Microsoft and Meta represents "short-term pain for long-term gain," reiterating his view that the AI revolution remains in its early stages. "We believe this is Year 3 of a 10-year AI buildout," Ives wrote, adding that the recent bearish narratives surrounding Big Tech have overshadowed what he sees as "future massive growth prospects." For investors willing to look beyond near-term monetization concerns, Ives believes today's "Twilight Zone" market could ultimately create some of the biggest buying opportunities in the AI trade.
What specific catalysts are needed to convince investors that the massive capital expenditures by hyperscalers are translating into tangible revenue growth?
How long can the current divergence between immediate beneficiaries like Micron and infrastructure builders like Microsoft and Meta persist before market sentiment shifts?
What potential risks could arise if the monetization of AI investments by hyperscalers takes longer than the anticipated 10-year buildout timeline?

































