Analysts Think These AI Stocks Could Beat Goldman's 2025 S&P 500 Forecast by 400%
Analysts Think These AI Stocks Could Beat Goldman’s 2025 S&P 500 Forecast by 400%

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AI stocks were the straw that broke the camel’s back on Wall Street in 2024 and all indications are that this trend will continue in 2025. Many investors took advantage, but Goldman Analysts I think the S&P 500 index should see slow growth next year. If you’re looking for higher upside potential, analysts estimate that these two stocks could outperform Goldman’s expectations for the S&P 500 by several hundred percent in 2025.

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Advanced Micro Devices was one of the first major chipmakers to set up operations in what would become Silicon Valley. This company has been producing graphics processing units (GPUs) and computer processing units (CPUs) since the late 1960s, when “advanced” computers took up entire rooms. Despite its long history, AMD has been overtaken by several competitors, including Nvidia.

Nvidia’s dominance is largely due to its ability to deliver high-performance chips that enable technology companies to optimize their AI capabilities. However, AI’s appetite for data is so vast that opportunities still exist for AMD. According to Barchart, AMD’s sales have increased by 10% over the past 12 months. AMD continued this momentum with its Q3 2024 results, which saw gross profits increase 19% compared to Q3 2023.

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AMD’s earnings per share (EPS) of $0.47 also far exceeded $0.18 in Q3 2023. AMD shares are currently trading at $120.10, but many analysts see upside potential important. Notably, Goldman Sachs isn’t the only investment firm pegging AMD for a big 2025. Benzinga survey of 30 analysts shows a consensus price target of $195 for AMD, leaving 63% upside potential. This wipes out Goldman’s 7% growth forecast for the S&P 500.

Synopsis is one of many companies that have thrived in the ecosystem created by the emergence of AI as a business and technology force. Rather than making chips like AMD or Nvidia, Synopsis creates technology that allows developers to design and test computer chips. This technology is important because it allows semiconductor manufacturers and chipmakers to ensure that their chips can handle the workload that AI will place on them.