Microsoft Corporation (MSFT) Stock Forecast

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Which of the market dominates and so-called “magnificent 7” stocks could be the best investment? In the first stage of unlimited AI enthusiasm, their opportunities seemed almost unlimited, as everything in the MAG 7 was loved. The market is now more skeptical of perceived AI winners, which has led to a natural tendency to rank groups in their future prospects. Amazon has seen it rise in ranks, but Nvidia continues to order it to top position. All Mag 7 names have something in common. They all dominate in at least one core competency. And they leveraged the immense cash flow thrown out by their core competencies to invest and develop generative AI opportunities. Thus, a medium-term prospect “ranking” 7 involves assessing each company’s ability to advocate and nurture its core business while using its strength within the AI ​​ecosystem to gain share. This week’s list will analyze and rank the apparent mid-term outlook MAG 7 (top to bottom). We expect the Mag 7 ranking to be fluid, but don’t foresee any movement in the first or last place. Unlike the other six names, Nvidia’s core competency is artificial intelligence. The establishment of Nvidia, a GPU-based game, the need for realistic rendering in the business has laid the foundation for accelerating applications and large-scale parallel computing, the basis for training large-scale language models (LLMS) and enabling inference. We are ranked NVIDIA as a star based on evidence of the company’s own growth numbers. In the recent fiscal year of 4Q25, revenues increased by 78% by $39 billion per year. At the GTC event in March 2025, NVIDIA predicts that data-centric revenues will exceed $1 trillion per year in the coming years, with the global industrial infrastructure projecting $50 trillion opportunities for AI renewal. Nvidia also offers much more industry-leading GPUs, including the CUDA software library, and “turbocharged” agent AI development with open rear models, platforms and partnerships. The best evidence of Nvidia’s momentum is the growth of enterprise infrastructure companies using NVIDIA solutions to support AI mainstreaming. Micron’s data center revenue tripled year-on-year, and now exceeds 50% of the company’s total revenue. Micron increased its high-bandwidth memory (HBM) opportunity to $35 billion in 2025 as of March 2025, up from $20 billion about six months ago. Among the leading US GPU server providers, Dell Technologies recorded $10 billion in AI Sever revenue in 2025, and is projected to reach $15 billion in 2026. Hewlett-Packard Enterprise has left fiscal 1Q25 with a $8.3 billion cumulative AI system and services order. Leaders at Data Center Interconnection (DCIS), Broadcom and Marvell both report explosive growth in these categories. *MetaPlatform (META): MetaPlatform is the most successful in leveraging core competency (social media) in the role of leadership in building LLMs, including multimodal models. SNAP has limited opportunities, and X is caused by self-harm and perceived musk transmission. Only Asian-based companies such as Bytedance (Tiktok) represent the real threat. We see some risk in the core business from the seemingly endless opposition of the EU and US Congress. Meta’s social media corner tones (Facebook, Instagram and WhatsApp) could also be neatly carved in three. But we don’t think that’s happening. Meta has succeeded in the more practical and rapidly developing AI opportunities due to Zuckerberg’s expensive obsession with the metaverse. Unlike AWS, Microsoft Azure and Google Cloud, Meta is not a leading provider of hybrid cloud services, but has successfully enabled and advanced LLM to its major LLMS. Meta is deploying AI internally to improve operational efficiency and personal targeting to optimize the social media user base of over 3.3 billion companies. Facebook Reality Labs, which houses Meta’s Gen AI Business, recorded revenue of $2.1 billion in 2024. This was just 1% of total meta revenue. Currently, this is primarily a hardware-based business (Quest VR headset, Ray-Ban AR glasses), but as Meta’s Lama LLM becomes mainstream, there are opportunities for long-term growth. Just as Apple capitalizes the base with its vast IOS installed and targets individuals using Icloud, Meta can offer personalized AI products to over 3 billion users. *Amazon.com (AMZN): Amazon is in third place. Amazon’s online retail business, especially its major businesses, does not have global peers. The overall operating income (Americas and International) for 4Q24 was 6.1%, which could be traced back to the company’s establishment. Prime media is currently comparable to Netflix in terms of content quality and volume. AWS is the leading CSP worldwide, and its rising margins and cash flow funds the company’s AI Gen AI opportunities. Amazon quickly replaced AWS chief in May 2024. The board recognized the company was behind Gen AI. AWS is $110 billion in revenue travel fees per year, with margins at or near record highs. AI produces a bedrock market where clients can choose from over 100 LLMs, both internally and artificially, and others, both in partnerships. Trainium and Trainium 2 accelerators. Amazon Nova is a broad family of basic models. *Apple (AAPL): 4th place goes to Apple. Apple’s core competency is global leadership in technology devices and services. Apple is somewhat disappointed by its early efforts in AI. The company even has a normal reliance on internal capabilities to seek support from companies such as Openai. But for a long time, we have seen Apple as the perfect person for its products, not the pioneer of its products. Early iteration phones like Dynatac and Startac are shocked, but they’ve been gone for a long time while the iPhone has gained the advantage. Investors are also concerned about Apple’s decline in China sales. However, in the most correct accounting 1Q25, Apple made money in all other regions. The company’s large IOS installed base is over 2.2 billion, providing fertile ground for the continued growth of its services. * Microsoft (MSFT): The fifth spot is Microsoft. Microsoft leverages Azure’s second CSP, Enterprise Software core competency. Like all the companies listed above that are not named Nvidia, Microsoft is challenging to get a sufficient supply of Advanced Blackwell products to build and execute the smartest models. Microsoft’s cloud business was not as profitable as AWS, but this may be partly because assets are allocated to the cloud department. Microsoft has several missteps when deploying Gen AI models.