EQUITY RESEARCH | January 11, 2026 | 5:39PM EST Assuming Software Sector Coverage into the Decade of Agentic Workflow: Buy MSFT, ORCL & NOW; Sell ADBE & DDOG AMERICAS TECHNOLOGY: SOFTWARE We assume coverage of the Software Sector and 12 additional stocks. We are constructive on AI adoption being a positive tailwind to the Software TAM over the next 5-10 years. Datapoints in any given year may be uneven as the ecosystem matures and as competition evolves; nonetheless, we expect signals on uptake will be more ...

Core Viewpoint - Microsoft is expected to deliver impressive results by 2026, focusing on the timing of revenue recognition and normalization of profit margins, which may lead to reasonable stock price increases after a period of stagnation since July 2024 [1]. Group 1: Revenue and Profitability - Microsoft has one of the best forward revenue visibility among large tech peers, with commercial remaining performance obligations (RPOs) growing 51% year-over-year to $392 billion, nearly doubling in two years [5]. - The weighted average duration of RPOs is two years, indicating high visibility compared to other software backlogs, which are often optional or long-term [5]. - Azure's demand remains strong, with a reported growth rate of 40% in the first quarter of fiscal 2026, although actual demand is believed to be higher due to supply constraints [6]. - Operating expenses grew by approximately 5%, while revenue increased by about 18%, demonstrating healthy efficiency in a high-cost AI environment [7]. Group 2: AI and Market Position - Microsoft is building a robust cloud and AI infrastructure, achieving over 30% improvement in GPU token throughput through software optimization, which mitigates risks associated with GPU cycles [8]. - Copilot's monthly active users (MAU) have surpassed 150 million, with overall AI interactions reaching approximately 900 million users, indicating strong adoption trends [10]. - The monetization of Copilot is expected to follow a non-dilutive revenue expansion path, enhancing pricing power without harming existing software revenues [10]. Group 3: Future Expectations - Analysts anticipate that capacity will catch up with demand by late 2026, leading to revenue expansion without the need for new demand creation [11]. - Concerns regarding AI spending excess and commercialization are expected to shift from "if" to "how much" in 2026, as enterprise deployments increase [12]. - The upcoming fiscal 2026 second quarter will be closely monitored for progress in RPO growth and alignment of short-term assets with contract durations [12][13].

此次调查于2025年10月进行，涵盖130家企业的IT高管，平均员工数达8200人，IT预算约8亿美元。调查揭示了企业AI部署面临的核心挑战：59% 的受访者认为投资回报率不明确是最大障碍，这一比例较今年3月的50%显著上升。合规监管担忧(45%)和内部专业人才不足(43%)分列二、三位。 调查还发现，AI应用并未导致大规模裁员。40%的受访企业表示AI将推动员工增长，仅31%预期会减少人员，且只有1%预期大幅裁员。这一发现 对基于席位收费的SaaS企业构成利好，缓解了市场对AI替代人工的担忧。 企业自建AI成主流趋势 尽管人工智能技术持续升温，但企业级AI应用的规模化部署进展缓慢。 据追风交易台，瑞银Karl Keirstead团队最新发布的第五次企业AI调查显示，仅17%的受访企业实现了AI项目的大规模投产，相较今年3月的14% 仅略有提升。 调查结果显示，微软、OpenAI和英伟达继续在企业AI市场占据主导地位。在云基础设施层面，微软Azure保持领先；在大语言模型方面，OpenAI 的GPT系列模型占据前五名中的三席，尽管谷歌Gemini和Anthropic Claude正快速追赶。微软的M365 C ...

Summary of Microsoft 2025 Conference Call Company Overview - **Company**: Microsoft (NasdaqGS: MSFT) - **Date**: December 02, 2025 - **Speaker**: Rajesh, leading Experiences and Devices at Microsoft Key Points Industry and Company Insights - Microsoft operates in the software and technology industry, focusing on productivity tools and cloud services, particularly through its M365 and Azure platforms [3][4][8] Revenue Streams and Growth - The M365 and Office 365 portfolio is a significant revenue driver, growing at 15% year-over-year, with over 400 million paid subscribers [8][9] - Seat growth is reported at 6%, driven by small and medium-sized businesses, despite maturity in the enterprise space [16][9] - Average Revenue Per User (ARPU) growth is attributed to: - Customers opting for the full M365 suite - Increased adoption of the premium E5 offering - The introduction of M365 Copilot [11][18] M365 Copilot and AI Integration - M365 Copilot is becoming a key driver of ARPU growth, with daily active engagement more than doubling over two quarters [26][30] - 90% of Fortune 500 companies are reported to have adopted Copilot, indicating strong market penetration [30] - The integration of AI is seen as an opportunity for growth rather than a threat to seat numbers, with the expectation that organizations will require more digital agents [17][18] Customer Engagement and Support - Microsoft is enhancing customer support through dedicated success teams and analytics tools to measure ROI and usage of Copilot [36][40] - The introduction of Copilot Analytics allows customers to conduct cohort analyses to evaluate the effectiveness of Copilot [40] Governance and Compliance - Agent governance is a significant focus, with Microsoft aiming to provide customers with control over agent deployment and compliance [40][45] - The introduction of Agent 365 is expected to help manage agent sprawl and ensure compliance across various applications [45] Competitive Landscape - Microsoft acknowledges competition from OpenAI and Google but emphasizes its unique capabilities, such as Work IQ, which leverages existing user data to enhance productivity [76][81] - The company is committed to a multi-model approach, allowing users to choose between different AI models based on their needs [84][70] Compute Capacity Challenges - Microsoft is facing compute capacity constraints due to high demand from both first-party applications and third-party commitments [94][100] - The company is actively working on optimizing resource allocation and managing load across different regions and times [100][103] Future Outlook - The integration of AI and digital agents is expected to evolve, with predictions of more agents than humans in the workforce by 2026 [64][85] - Microsoft is focused on enhancing user experiences through improved AI models and workflows, aiming to maintain its competitive edge in the market [49][84] Additional Important Insights - The importance of security and compliance in the adoption of AI tools is highlighted, with a focus on data governance and policy management [18][81] - The potential for AI to transform traditional workflows and enhance productivity is a recurring theme throughout the discussion [56][64]

Summary of Microsoft Corp. (MSFT) Investor Meeting Company Overview - **Company**: Microsoft Corp. (MSFT) - **Current Price**: $487.12 - **12-Month Price Target**: $630.00 - **Upside Potential**: 29.3% [1] Key Topics Discussed 1. **Long-term AI Value Accrual**: - Investors are focused on where AI value will accrue in the long term, beyond short-term supply-demand dynamics. - Microsoft customers value flexibility across technologies and models, preferring larger, integrated solutions over many small components to reduce costs and integration challenges. - Microsoft aims to be model agnostic, as shown by partnerships with Anthropic and OpenAI, providing access to multiple models through its Foundry layer [2][15]. 2. **Emerging Killer Applications for AI**: - Significant productivity improvements are seen in coding and customer support applications. - The healthcare sector has shown strong adoption of Microsoft AI, with over 70% of providers utilizing AI for analytics, exemplified by the partnership with Epic [16]. 3. **ROI Breakthroughs**: - Large Language Models (LLMs) are primarily consumer-focused but can unlock greater ROI when integrated with enterprise applications. - Aiming for higher accuracy in AI tasks (from 80% to 90-95%) is crucial for mainstream adoption, requiring improved model capabilities and data integration [17]. 4. **AI Halo Effect on Azure and M365**: - Increased adoption of AI workloads on Azure is positively impacting other Microsoft products like Microsoft Fabric and Power BI. - Enterprises are recognizing the benefits of M365 Copilot, although implementation requires a learning curve [18]. 5. **Next Generation Data Center**: - Microsoft is developing a distributed network of AI data centers designed for high compute and energy density, capable of handling massive training workloads with lower latency [20][22]. 6. **Capacity Building for Growth**: - Microsoft is strategically increasing capacity while managing supply-demand imbalances, focusing on land, power, and GPU infrastructure. - Future investments in AI capacity are expected to enhance revenue from first-party applications, not just Azure [23]. Financial Projections - **Market Cap**: $3.6 trillion - **Revenue Forecasts**: - FY25: $281.72 billion - FY26E: $326.91 billion - FY27E: $376.69 billion - FY28E: $432.40 billion [3][11] - **EBITDA Forecasts**: - FY25: $162.68 billion - FY26E: $203.84 billion - FY27E: $238.14 billion - FY28E: $274.06 billion [3][11] - **EPS Forecasts**: - FY25: $13.64 - FY26E: $16.05 - FY27E: $19.53 - FY28E: $23.05 [3][11] Investment Thesis - Microsoft is positioned to capitalize on long-term trends such as generative AI, public cloud consumption, and digital transformation. - The company is expected to double its earnings per share from FY24 to FY28, with a projected cloud business run-rate of ~$250 billion by FY27, representing a 22% CAGR [24][25]. - Microsoft’s diverse offerings and strong market presence provide a competitive advantage in the evolving tech landscape [27]. Risks - Key risks include slower public cloud adoption, overall IT spending slowdown, and competitive pressures [30]. This summary encapsulates the critical insights from the investor meeting regarding Microsoft's strategic direction, financial outlook, and market positioning in the context of AI and cloud services.

Core Insights - Microsoft is positioning its AI infrastructure as a "planet-scale token factory," emphasizing the efficiency and modernization of its global AI data centers [1][2] - The company has achieved a 30% improvement in efficiency for serving GPT-4.1 and 5.0 through software optimization across various Nvidia chips [3] - Microsoft's AI strategy is not only focused on infrastructure but also on expanding revenue through AI-enhanced products like M365 Copilot and GitHub Copilot [4] Infrastructure and Efficiency - The "token factory" metaphor represents Microsoft's commitment to continuously modernizing its AI infrastructure rather than relying on a single version of hardware [2] - The goal is to maximize output from every watt, GPU, and dollar invested, reflecting a strong focus on operational efficiency [3] Revenue Growth and Product Expansion - AI products are becoming a new growth engine for Microsoft, with existing software seats being transformed into higher-margin AI subscriptions [4] - The company is exploring hybrid revenue streams by integrating advertising with AI subscriptions, indicating a strategic expansion into new markets [5] Financial Performance - Microsoft's AI infrastructure and product strategy contributed to a significant financial performance, with the company reporting a $77.7 billion quarter [5] - The focus on efficiency at scale is seen as the next big opportunity for Microsoft investors, rather than the pursuit of artificial general intelligence (AGI) [6]

Core Viewpoint - Microsoft emphasizes that its AI platform is generating real business value, with Azure cloud revenue expected to grow approximately 37% in fixed currency for Q2, despite capacity constraints [1][2] Financial Performance - The company projects total revenue guidance for Q2 to be between $79.5 billion and $80.6 billion, representing a growth of 14% to 16% [2] - Expected sales costs are between $26.35 billion and $26.55 billion, with a year-over-year increase of 21% to 22% [2] - Operating expenses are anticipated to be between $17.3 billion and $17.4 billion, reflecting a year-over-year growth of 7% to 8% [2] Customer Concentration Risk - Microsoft believes that the risk of customer concentration is manageable, as its nearly $400 billion remaining performance obligation (RPO) covers a wide range of products and customer sizes [1][4] - The weighted average duration of these contracts is only two years, indicating a focus on short-term consumption and usage [1][4] AI Platform and Systems - The company's competitive advantage lies in building systems like M365 Copilot and GitHub Agent HQ, rather than just the AI models themselves [2][4] - Microsoft is creating a highly interchangeable general AI platform, reducing dependency on any single large customer [2][7] Infrastructure and Demand - Microsoft has not over-invested in infrastructure; instead, demand continues to exceed supply, with a strong focus on fulfilling existing contracts [5][9] - The company is building an efficient, flexible infrastructure to support both first-party and third-party applications, ensuring high utilization rates [6][8] OpenAI Investment - The $4.1 billion loss related to OpenAI is attributed solely to the company's share of OpenAI's operational losses, with no other components included [6][10] Strategic Decision-Making - Microsoft prioritizes building a platform that can flexibly serve various customer needs, rejecting contracts that could disrupt this balance [10] - The company is selective about large-scale AI contracts, ensuring they align with long-term strategic interests and profitability [10]

Investment Rating - The report does not explicitly provide an investment rating for the industry Core Insights - The report focuses on the commercialization progress of AI applications, highlighting significant advancements in various sectors, including large models, AI video, AI programming, and enterprise-level AI software [4][28] - The report emphasizes the rapid growth in token consumption for AI applications, indicating accelerated commercialization and the emergence of new revenue streams [4][15] - Key companies in the AI space are experiencing substantial valuation increases, with several achieving over $1 billion in annual recurring revenue (ARR) [16][21] Summary by Sections 1. AI Application Overview: Acceleration of Commercialization - AI applications are witnessing a significant increase in token consumption, reflecting faster commercialization progress [4] - Major models like OpenAI have achieved an ARR of $12 billion, while AI video tools are approaching the $100 million ARR milestone [4][15] 2. Internet Giants: Recommendation System Upgrades + Chatbot - Companies like Google, OpenAI, and Meta are enhancing their recommendation systems and developing independent AI applications [4][26] - The integration of AI chatbots into traditional applications is becoming a core area for computational consumption [14] 3. AI Programming: One of the Hottest Application Directions - AI programming tools are gaining traction, with companies like Anysphere achieving an ARR of $500 million [17] - The commercialization of AI programming is accelerating, with several startups reaching significant revenue milestones [17][18] 4. Enterprise-Level AI: Still Awaiting Large-Scale Implementation - The report notes that while enterprise AI has a large potential market, its commercialization has been slower compared to other sectors [4][25] - Companies are expected to see significant acceleration in AI implementation by 2026 [17] 5. AI Creative Tools: Initial Commercialization of AI Video - AI video tools are beginning to show revenue potential, with companies like Synthesia reaching an ARR of $100 million [15][21] - The report highlights the impact of AI on content creation in education and gaming [4][28] 6. Domestic AI Application Progress - By mid-2025, China's public cloud service market for large models is projected to reach 537 trillion tokens, indicating robust growth in AI applications domestically [4] 7. Key Company Valuation Table - The report provides a detailed valuation table for key companies in the AI sector, showcasing significant increases in their market valuations and ARR figures [16][22]

Core Viewpoint - Oracle's long-term growth potential may be hindered by power supply issues, necessitating significant investments in energy to meet its ambitious revenue targets for the cloud business by FY30 [2][4]. Group 1: Oracle's Growth and Power Supply - Oracle's guidance includes a projected $145 billion in OCI revenue by FY30, but the sustainability of this growth is questioned due to potential power supply constraints [2][4]. - Competitors like Microsoft are already investing in alternative energy sources, indicating a trend that Oracle may need to follow to secure its growth [3][4]. - The need for a cohesive strategy regarding power sourcing is emphasized, as Oracle's long-term guidance may not account for future energy demands [4]. Group 2: Revenue Quality and Capacity Concerns - Oracle benefits from excess GPU capacity, but there are concerns about future capacity constraints that could impact its competitive position [7][8]. - The quality of revenue growth is under scrutiny, with some margins potentially being negative for certain use cases, raising questions about the overall profitability of Oracle's cloud business [5][8]. - The shift in power dynamics from inferencing to fine-tuning could provide some margin uplift, but evidence is needed to support the notion of a highly profitable business model [8]. Group 3: Competitive Landscape and Alternatives - Microsoft is highlighted as a preferred investment due to its higher quality AI revenue generation across various layers, contrasting with Oracle's current strategy [9][10]. - Other companies like MongoDB, HubSpot, and Intuit are identified as under-the-radar opportunities to capitalize on the AI trend, suggesting a broader competitive landscape beyond Oracle and Microsoft [11][12].

Group 1 - The article emphasizes that AI should be viewed as a collaborative partner rather than a replacement for human skills, highlighting the importance of providing context for effective use [7][84]. - It discusses the author's initial resistance to using AI tools, which changed after realizing their potential in enhancing productivity and efficiency in tasks like writing user stories [4][5]. - The author shares experiences of using AI to streamline complex tasks, demonstrating how AI can transform chaotic thoughts into structured outputs [6][10]. Group 2 - The article outlines a framework for building an AI assistant, which includes hiring the assistant, onboarding it with relevant knowledge, and initiating projects through dedicated chat threads [12][13][35]. - It suggests that the AI assistant can help with strategic decision-making, brainstorming, and even emotional support, thus enhancing overall productivity [10][11]. - The importance of continuous context updates and knowledge sharing with the AI assistant is emphasized to ensure it remains effective and relevant [74][81]. Group 3 - The article provides practical steps for utilizing AI in project management, including creating project knowledge bases and using specific prompts to guide the AI's responses [22][36]. - It highlights the significance of maintaining an ongoing dialogue with the AI to keep it informed about changes and developments within the organization [65][66]. - The potential for AI to evolve into a more proactive and connected tool is discussed, suggesting that future AI assistants could offer reminders and insights based on user activities [83][84].