J.P. Morgan assesses that the AI market may regain strength after stock decline
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J.P. Morgan assesses that the AI market may regain strength after stock decline

J.P. Morgan analysts suggest that the global artificial intelligence market has the potential to recover its strength after the recent decline in the sector's stocks. For the bank, this retraction has resulted in better positioning for investors and made valuations more attractive.

The institution identifies notable opportunities, especially in the semiconductor segment. Even in the face of concerns regarding AI implementation costs and the time required for these investments to generate returns, analysts predict that capital injections will remain robust, driven by advancements in monetization and corporate results from the technology.

Although AI-related stocks started the year on an upward trend, they lost momentum due to uncertainties about capital expenditures and the recovery period for these investments. At the beginning of this month, the sector's titles also suffered declines following warnings issued by executives of AI companies about the inherent risks of rapid technological development.

Mislav Matejka, Global Equities Strategist at J.P. Morgan, commented that the market correction has made valuations more inviting and could reignite interest in the sector. He stated that although the technology may not reach previous peaks of success, the fundamentals remain solid and there are numerous opportunities within the AI ecosystem.

The outlook is particularly positive for semiconductors. J.P. Morgan points to healthy fundamentals, projected price growth until 2027, and constrained supply and demand conditions that may persist until 2028.

Regarding software companies, the assessment is more cautious. J.P. Morgan perceives greater long-term instability, especially due to increased competition generated by AI progress. However, the analyst does not advise avoiding the software segment in isolation, given the significant reduction in valuations; he suggests that the trading pair between semiconductors and software should be reestablished.

This performance disparity between segments illustrates the current scenario: the MSCI World Semiconductors and Semiconductor Equipment index registered a gain of approximately 48% over the year, while the MSCI World Software and Services advanced only 1.3%. For J.P. Morgan, the combination of strong results, lower valuations, and lower volatility may favor a resurgence of investor interest in the global AI market.

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Goldman Sachs analysis warns that AI investment returns may take years to materialize
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Goldman Sachs analysis warns that AI investment returns may take years to materialize

According to an analysis by Goldman Sachs, the large financial investments made in artificial intelligence by technology companies may require several years to start generating profits. Before this period, these companies must reach the break-even point, the moment when the revenue obtained is sufficient to cover the costs of the investments made.

Strategist Ryan Hammond estimates that cloud computing giants, such as Amazon, Oracle, and Microsoft, will need to generate approximately US$ 300 billion (equivalent to BRL 1.55 trillion) from AI in the coming years to reach this break-even phase.

It is observed that the cloud computing revenues of hyperscalers showed acceleration this year. In the second quarter of 2026, the annualized rate exceeded the previous trend for AI expansion by about US$ 70 billion (BRL 364 billion).

Already announced future contracts from the group exceed the mark of US$ 1.5 trillion (BRL 7.8 trillion). However, for Hammond, these figures do not yet indicate that the investments are close to paying off.

The strategist emphasized that it is expected that AI users will spend about US$ 1 trillion (BRL 5.19 trillion) annually on AI applications for hyperscalers to be able to generate solid returns on invested capital. This projection is conditional on a significant increase in spending on AI applications, which, according to Hammond, would also help the application layer achieve robust profit margins relative to computing costs.

This warning comes at a time when investors are resuming interest in the shares of large technology corporations, motivated by optimism regarding AI. The analysis points out that a crucial step before large investments begin to yield consistently is converting the growing demand for computing and applications into revenue capable of sustaining the inherent costs of the process.

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