Core Thesis - IBM is positioned as an underappreciated beneficiary of the enterprise AI wave, leveraging its scale and longstanding customer relationships to capture corporate AI contracts through its Watsonx platform [2][4]. Company Positioning - IBM commands a strong foothold with global enterprises, providing an advantage in execution and adoption compared to newer entrants in the AI space [3]. - The company is characterized as a blue-chip stock that has been dormant for years, offering a different risk profile with reliable dividends [3][4]. Financial Metrics - As of September 12th, IBM's share was trading at $253.44, with trailing and forward P/E ratios of 40.88 and 21.88 respectively [1]. - The stock price has appreciated approximately 10.67% since previous coverage in December 2024, reflecting ongoing optimism around AI adoption [5]. Risk and Opportunity - IBM's diversified operations, stable cash flows, and strong balance sheet create resilience, limiting downside risk compared to more volatile AI peers [4]. - The potential upside from IBM's AI initiatives coincides with favorable macro conditions, such as expected Federal Reserve rate cuts, which could lead to a re-rating of value-oriented tech stocks [4].

Core Insights - Palantir Technologies has emerged as a significant player in the stock market, particularly after launching its Artificial Intelligence Platform (AIP) in 2023, leading to substantial stock performance [1][2] - BigBear.ai is being compared to Palantir as a potential investment opportunity in the AI space, but it faces challenges in scaling its business and revenue [4][6] Company Performance - Palantir's stock surged 340% in 2024, making it the best-performing stock in the S&P 500, with a 118% gain in 2025 so far [2] - An investment of $1,000 in Palantir three years ago would now be worth $21,000 [2] - Palantir reported $2.27 billion in total contract value sales in Q2, a 140% increase year-over-year, with a 43% growth in customer count [7] - BigBear.ai's revenue was $32.4 million in Q2, down 18% from the previous year, primarily due to reduced U.S. Army program volumes [8] Contract and Revenue Analysis - Palantir's revenue growth has escalated from approximately $460 million per quarter to $1 billion per quarter over three years [7] - BigBear.ai's largest contract is a $165 million deal with the U.S. Army, which poses a risk if the Army's projects slow down [8] - Palantir closed 157 deals in Q2 valued at $1 million or more, with 66 deals exceeding $5 million and 42 over $10 million [10] Competitive Landscape - IBM is highlighted as a strong competitor in the AI space, leveraging its $34 billion acquisition of Red Hat to enhance its hybrid cloud offerings and AI products [12] - IBM's software revenue reached $7.4 billion in Q2, with hybrid cloud revenue increasing by 16% year-over-year [13] - Amazon Web Services (AWS) leads the global cloud computing market with a 30% share, generating $30.87 billion in revenue and $10.16 billion in operating income [15][16] - Amazon's advertising revenue also saw a significant increase, reaching $15.6 billion in Q2, up 22% from the previous year [17] Future Outlook - The AI sector is expected to shape future business landscapes, with established companies like Palantir, IBM, and Amazon positioned for growth, while BigBear.ai may struggle to keep pace [18]

Core Insights - The performance of AI products increasingly relies on data quality and freshness rather than just model size [1][2][3] - Companies like Salesforce and IBM are acquiring data infrastructure firms to enhance their AI capabilities with real-time, structured data [2][5][6] - The definition of "good data" includes being domain-specific, continuously updated, structured, deduplicated, and real-time actionable [4][5][6] Data Infrastructure Importance - Data collection is now seen as a critical infrastructure rather than a secondary task, emphasizing the need for reliable, real-time access to data [2][9][22] - The modern AI data stack has evolved into a value chain that includes data acquisition, transformation, organization, and storage [10][22] - Effective data retrieval quality surpasses prompt engineering, as outdated or irrelevant data can hinder model performance [7][19] Strategic Data Collection - Data collection must be strategic, providing structured and immediate data for AI agents [12][13] - It should handle dynamic user interfaces, CAPTCHAs, and mixed extraction methods to ensure comprehensive data gathering [14][15] - Data collection infrastructure should be scalable and compliant with legal standards, moving beyond fragile scraping tools [16][22] Future of AI Systems - The future of AI performance will depend more on knowledge acquisition speed and context management rather than just model size [23][24] - Companies that view data collection as a foundational capability will likely achieve faster and more cost-effective success [25]

Core Insights - Unisys Corporation is strategically repositioning itself in the AI-driven IT services sector through its ClearPath Forward 2050 strategy, focusing on AI, automation, and data-driven intelligence across its offerings [1][11] - The company is addressing enterprise challenges such as data fragmentation and low productivity by leveraging AI technologies, exemplified by its Service Experience Accelerator [2][11] - Unisys is developing agentic-AI frameworks to enhance decision-making and service delivery, creating new revenue opportunities in endpoint management and AI-enabled infrastructure [3][11] AI Innovations - The Service Experience Accelerator utilizes generative AI and workflow automation to improve service desk operations, gaining traction among clients [2] - The intelligence accelerator connects siloed datasets, providing secure and real-time insights, which enhances service delivery [3] Industry Positioning - Unisys is recognized as a "disruptor" in the AI Services sector and is investing in post-quantum cryptography and threat detection solutions [4] - The company competes with major players like C3.ai, Palantir Technologies, and IBM, each with unique AI strategies [6] Financial Performance - Unisys shares have increased by 12% over the past three months, while the industry has grown by 20.1% [9] - The stock has risen by 22.4% in three months, with projected earnings per share (EPS) growth of over 120% for 2026 [11] - The current valuation shows a forward price-to-earnings ratio of 4.73X, indicating a discount compared to industry peers [12] Earnings Estimates - The Zacks Consensus Estimate predicts a year-over-year earnings increase of 28.9% for 2025 and 120.7% for 2026 [14] - Current estimates for EPS in 2025 and 2026 are 0.58 and 1.28, respectively, reflecting significant growth potential [16]

Core Viewpoint - IBM's stock has increased over 60% in the past year, driven by successful cloud and AI strategies, leading to consistent revenue and free cash flow growth, with expectations for continued acceleration in revenue growth [1][12]. Financial Performance - IBM's revenue grew by 3% in 2024 when adjusted for currency, with projections of at least 5% growth in 2025 despite economic uncertainties [1]. - The company anticipates generating approximately $13.5 billion in free cash flow by 2025, resulting in a price-to-free cash flow ratio of 19, which is considered reasonable given its AI success [10]. Analyst Insights - An analyst from Wedbush raised the price target for IBM stock from $300 to $325, indicating a potential 16% upside from the recent closing price, labeling IBM as an "AI winner" and expecting a continued growth renaissance [3][12]. AI Strategy - IBM's AI strategy focuses on solving real problems for enterprise customers rather than competing with other tech giants in AI infrastructure [4][9]. - The AI business comprises two main components: software, including the Watsonx platform for managing AI models, and consulting services, which are crucial for implementation and guidance [5][7]. AI Product Offerings - IBM's Watsonx platform allows enterprises to train, deploy, and manage AI models with advanced governance features, essential for companies with sensitive data [5]. - The Granite family of AI models, designed for cost efficiency and specific tasks, includes models that can run on consumer-grade hardware, making AI more accessible [6]. Market Positioning - IBM has secured over $6 billion in generative AI-related business, primarily through its consulting services, which help clients deploy AI workloads effectively [7]. - Watsonx is compatible with third-party clouds like AWS and Azure, allowing clients to utilize IBM's AI services regardless of their existing cloud commitments [8]. Future Growth Opportunities - Beyond AI, IBM is exploring long-term growth in quantum computing, with plans to develop a fault-tolerant quantum computer by 2029, which could unlock significant market opportunities [11].

Financial Performance & Growth Drivers - IBM's rally initially stemmed from its free cash flow performance, particularly after a significant beat five to six quarters prior to the report [3] - Revenue growth is expected to be in the low to mid single-digit percentages in the coming years [6] - Software growth is the primary focus for investors, followed by GenAI consulting and infrastructure [9] - IBM saved $500 million (three half billion) in run rate costs by deploying Gen AI [11] GenAI & Technology - IBM is positioning itself to enable the "Magnificent 7" through its hybrid cloud and GenAI infrastructure [4] - IBM's GenAI consulting business currently accounts for approximately 80% of its book of business [11] - IBM's Granite models are small, open-source language models focused on enterprise cost efficiency [11] - IBM has 75 quantum computers, with 13 currently running in production, and anticipates this becoming a significant part of their business by the end of the decade [16] Risks & Considerations - A shift in competitive positioning, especially concerning GenAI, could pose a risk to IBM's stock [18] - Sentiment around GenAI and hybrid cloud is driving multiple expansion [18]

Industry Overview - The AI industry is facing an uncertain macroeconomic environment, with signs indicating a potential cooling in demand for AI infrastructure [1] - Super Micro Computer has reduced its guidance due to delayed purchasing decisions from customers, and some tech giants are scaling back on data center expansions [1] Investment Focus - Investors are still interested in AI, with a recommendation to avoid AI hardware companies like Super Micro and Nvidia, as well as hyperscalers like Microsoft [2] - The focus should be on companies specializing in AI inference and efficient, specialized AI models, with IBM and Cloudflare highlighted as top picks [2] IBM's AI Strategy - IBM has secured $6 billion in generative AI-related business, with $1 billion added in the first quarter, primarily from its consulting business [3] - The Watsonx AI platform is central to IBM's AI efforts, enabling enterprises to build, test, deploy, and manage AI models, with potential cost reductions of up to 98.5% by using specialized models [4] - IBM's upcoming z17 mainframe, launching in June, can perform 450 billion AI inferencing operations daily, making it suitable for real-time tasks like credit card fraud detection [6] Cloudflare's AI Capabilities - Cloudflare focuses on speed, allowing developers to perform fast computations on user requests, covering various use cases including AI inference tasks [8] - The platform supports over 50 open-source AI models and integrates with Cloudflare Workers for programmatic access [9] - By focusing on AI inference with smaller models, Cloudflare can utilize older, less expensive AI accelerators, reducing costs while maintaining performance [10] - Cloudflare's revenue grew by 27% year over year in Q4 2024, with a record number of large customers spending over $1 million annually [11]

Core Insights - IBM is rapidly capitalizing on the generative AI market, with significant growth projected in its Watsonx platform's book of business [1][4][7] Group 1: Watsonx Overview - Watsonx was launched in May 2023, following the introduction of ChatGPT and Alphabet's Gemini tool [2] - The platform is designed for large-scale business adoption, offering robust data security and the ability to audit AI-generated statements [3] Group 2: Financial Projections - IBM's generative AI book of business is expected to grow from "low hundreds of millions of dollars" in Q3 2023 to "over $5 billion" by Q4 2024 [4] - The growth trajectory indicates a doubling of the book of business from Q3 to Q4 2023, with projections exceeding $1 billion in Q1 2024 and $2 billion in Q2 2024 [4] Group 3: Revenue Recognition - The book of business metric reflects long-term subscriptions and contracts rather than immediate software sales, similar to deferred revenue [5] - Only 20% of the contracts are directly related to Watsonx software, with the majority stemming from consulting services [6]

Group 1: IBM's AI Strategy and Growth - IBM is a leading player in business-class artificial intelligence (AI) and is expected to see significant stock growth driven by AI advancements [2][10] - The company launched the Watsonx platform for generative AI tools aimed at corporate clients shortly after the release of ChatGPT, differentiating itself from consumer-focused models [3][4] - IBM's Watsonx business has rapidly grown, with contracts increasing from over $1 billion in Q1 2024 to over $5 billion by the end of the year [6][10] Group 2: Consulting Services as a Competitive Advantage - Approximately 80% of IBM's generative AI order book consists of consulting contracts, highlighting the importance of consulting services in its business model [7][9] - Unlike competitors such as Microsoft, Alphabet, and Amazon, IBM places significant emphasis on consulting services, which are integral to its AI offerings [8][9] Group 3: Financial Performance and Valuation - IBM reported $62.8 billion in total revenue last year, generating $12.7 billion in free cash flow, with the AI-driven segment growing rapidly [10] - The stock trades at modest valuation ratios, suggesting potential for significant appreciation compared to peers like Amazon and Microsoft [11][12]