Oracle Corp (ORCL) Stock Analysis and Metrics

Oracle

NYSE: ORCL

$139.26 ▼ -2.35 (-1.66%)

At close: Jul 8, 2026 · 2:52 PM UTC

Financial Ratios

Market Cap408.21 Bn

P/E23.92

P/S6.06

Div. Yield0.01

ROIC (Qtr)0.00

Total Debt (Qtr)122.34 Bn

Revenue Growth (1y) (Qtr)20.63

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About

Oracle Corporation provides products and services that address enterprise information technology needs. The company develops and delivers enterprise applications and infrastructure offerings through on premise, cloud based, and hybrid deployment models. Its core activities include licensing software, providing cloud subscriptions, selling hardware systems, and offering professional support services. With a global workforce of approximately 162,000 employees and a presence in more than 175 countries, Oracle serves a broad range of industries from finance to healthcare.

Oracle generates revenue from the sale of software licenses and cloud subscriptions for its applications and infrastructure technologies. It also earns income from hardware products such as engineered systems, servers, and storage, and from professional services including consulting and advanced customer support. Additionally, customers frequently purchase license support and hardware support contracts, which provide recurring revenue streams. Cloud services revenues accounted for 43% of total revenues in fiscal 2025, reflecting the growing shift to subscription based models. In fiscal 2025, the company invested $9.9 billion in research and development to enhance its existing portfolio and develop new technologies.

The company operates through the following segments: cloud and license, hardware, and services.

• Cloud and License: This segment offers Oracle Cloud Applications such as Fusion Cloud ERP, EPM, SCM, HCM and NetSuite, Oracle Cloud Infrastructure services including compute, storage, networking and Autonomous Database, and related license and support offerings for applications, database, middleware and Java technologies, while providing flexible deployment options for public cloud, private data center or hybrid environments, and integrating emerging technologies such as artificial intelligence and machine learning into its portfolio.

• Hardware: This segment provides Oracle Engineered Systems, enterprise servers, storage solutions, and industry specific hardware products, along with hardware support contracts that deliver maintenance, repairs and technical assistance, while enabling seamless integration with Oracle Cloud services and offering deployment flexibility for on premise, cloud based, and hybrid environments.

• Services: This segment delivers consulting services, advanced customer services, Oracle Cloud Operations, and other professional services that help customers implement, manage and optimize Oracle applications and infrastructure, while assisting customers in migrating to the cloud, optimizing performance, and leveraging Oracle's expertise in enterprise software, hardware and cloud infrastructure.

Oracle holds a strong position in the enterprise software market, competing with companies such as Microsoft, Amazon, International Business Machines, SAP, and Salesforce. Its competitive advantages stem from a broad portfolio of integrated cloud and on premise products, flexible deployment models, significant investment in research and development, and a global sales and partner network. The company’s scale, deep expertise in database and middleware technologies, and ability to offer end to end solutions from applications to infrastructure further differentiate it from rivals.

Oracle serves a diverse customer base that includes businesses of various sizes, government agencies, educational institutions, and resellers. Specific customers mentioned in the filing include an AI product company using OCI for generative AI models, a global technology company relying on OCI for logistics and mobile applications, a multinational financial institution running banking applications on Oracle Exadata Cloud@Customer, and a global consumer products company utilizing Oracle Fusion Cloud ERP for accounting, risk management, supply chain, and financial planning. The company’s customer base spans North America, Europe, Asia Pacific, Latin America, and the Middle East, reflecting its global reach.

Investment Thesis

▲ Bull case

Oracle Corporation is building a powerful moat through its multicloud database strategy, which allows customers to run Oracle Database services in AWS, Azure, and Google Cloud—turning years of single-cloud limitations into a global backlog of pent-up demand. The company reported 33 live regions with Microsoft and 14 with Google, while expanding AWS coverage from two to eight regions in Q3 FY26 with plans to reach 22 by Q4. This infrastructure is not merely reactive but is being accelerated by AI workloads requiring colocated data and models, with management noting that customers are moving valuable private data to cloud environments specifically to leverage Oracle’s AI capabilities. Crucially, Oracle is not just selling compute; it is embedding high-margin database services (60%-80% gross margin range) into multicloud deals, turning what could be a commoditized infrastructure play into a recurring revenue engine with pricing power. The unspoken strength here is that Oracle’s database remains the system of record for mission-critical enterprise workloads, and by making it available wherever the customer chooses—without requiring re-architecture or data migration—Oracle is capturing upgrade and expansion cycles that competitors cannot replicate. This is not a temporary feature but a structural shift in how enterprise data is managed, positioning Oracle to benefit from long-term cloud sprawl rather than suffer from it.
The company’s AI infrastructure business is demonstrating exceptional capital efficiency through innovative financing models that reduce Oracle’s direct cash outlay while accelerating deployment. Clay McGouyrk highlighted that over $29 billion in contracts have been signed since the last earnings call using a bring-your-own-hardware and upfront customer payment model, enabling expansion without negative cash flow from Oracle Corporation. This approach de-risks the capital-intensive nature of AI data centers by shifting funding burden to partners and customers, while Oracle retains control over design, integration, and service delivery. More than 400 megawatts were delivered to customers in Q3 FY26 with 90% on or ahead of schedule, and gross margin for AI infrastructure remained above guidance at 32%—a figure that improves when factoring in higher-margin adjacent services like networking and storage (10%-20% of total spend) and the multicloud database layer. The operating model leverages standardized designs, tripled manufacturing sites, and 4x increased rack output to drive down costs while scaling rapidly. This is not just about building data centers; it is about creating a proprietary, scalable, and profitable engine for AI workloads that competitors relying on traditional capex models cannot match in speed or capital efficiency.
Oracle’s applications business is undergoing a quiet but profound transformation through AI agent embedding, which is turning its SaaS suite from a system of record into an intelligent automation platform that competitors like Salesforce cannot replicate without sacrificing depth and integration. Mike Cecilia detailed the launch of three brand-new CX applications—lead generation, sales orchestration, and website generator—built entirely using AI coding tools and deployed internally to power oracle.com, demonstrating rapid product innovation. Over 1,000 AI agents are already embedded across horizontal and industry applications, including a live AI-powered EHR in healthcare reducing administrative overhead and enabling clinicians to see more patients. These are not superficial AI features but deep integrations into workflows like order-to-cash, procure-to-pay, and financial close, where Oracle’s decades of domain expertise and regulatory compliance create unbeatable switching costs. The AI Agent Studio in Fusion allows customers to build custom agents on top of Oracle’s prebuilt library, all tied to mission-critical data governed by Oracle’s security and compliance framework. This turns Oracle’s applications into an AI agent factory—where the platform itself becomes the development environment for enterprise AI—making it far harder to displace than point-solution AI tools that lack access to governed data and embedded processes.
Project Jupiter in New Mexico represents a strategic inflection point in Oracle’s ability to build sustainable, community-aligned AI infrastructure that mitigates ESG and regulatory risks while securing long-term locational advantages. The project will use up to 2.45 GW of Bloom Energy fuel cells—eliminating combustion, reducing NOₓ emissions by ~92%, and using negligible water through closed-loop cooling—directly addressing community concerns about air quality, water stewardship, and electricity rates. Oracle is承担 all energy costs, ensuring no impact on residential electricity, while committing $50 million to water systems, $360 million to schools and infrastructure, and $6.9 million to workforce development. This is not altruism; it is de-risking future expansion by turning potential opposition into advocacy. The campus will create 4,000 construction jobs and 1,500 ongoing roles, generating $113 million in annual economic impact post-construction. By securing clean power, water sovereignty, and community buy-in early, Oracle avoids the delays, protests, and retrofits that have plagued competitors’ data center builds. This model is replicable and positions Oracle to win sovereign and regulated workloads where competitors face permitting hurdles—turning ESG from a cost center into a competitive advantage in infrastructure siting.

Oracle Corporation is building a powerful moat through its multicloud database strategy, which allows customers to run Oracle Database services in AWS, Azure, and Google Cloud—turning years of single-cloud limitations into a global backlog of pent-up demand. The company reported 33 live regions with Microsoft and 14 with Google, while expanding AWS coverage from two to eight regions in Q3 FY26 with plans to reach 22 by Q4. This infrastructure is not merely reactive but is being accelerated by AI workloads requiring colocated data and models, with management noting that customers are moving valuable private data to cloud environments specifically to leverage Oracle’s AI capabilities. Crucially, Oracle is not just selling compute; it is embedding high-margin database services (60%-80% gross margin range) into multicloud deals, turning what could be a commoditized infrastructure play into a recurring revenue engine with pricing power. The unspoken strength here is that Oracle’s database remains the system of record for mission-critical enterprise workloads, and by making it available wherever the customer chooses—without requiring re-architecture or data migration—Oracle is capturing upgrade and expansion cycles that competitors cannot replicate. This is not a temporary feature but a structural shift in how enterprise data is managed, positioning Oracle to benefit from long-term cloud sprawl rather than suffer from it.
The company’s AI infrastructure business is demonstrating exceptional capital efficiency through innovative financing models that reduce Oracle’s direct cash outlay while accelerating deployment. Clay McGouyrk highlighted that over $29 billion in contracts have been signed since the last earnings call using a bring-your-own-hardware and upfront customer payment model, enabling expansion without negative cash flow from Oracle Corporation. This approach de-risks the capital-intensive nature of AI data centers by shifting funding burden to partners and customers, while Oracle retains control over design, integration, and service delivery. More than 400 megawatts were delivered to customers in Q3 FY26 with 90% on or ahead of schedule, and gross margin for AI infrastructure remained above guidance at 32%—a figure that improves when factoring in higher-margin adjacent services like networking and storage (10%-20% of total spend) and the multicloud database layer. The operating model leverages standardized designs, tripled manufacturing sites, and 4x increased rack output to drive down costs while scaling rapidly. This is not just about building data centers; it is about creating a proprietary, scalable, and profitable engine for AI workloads that competitors relying on traditional capex models cannot match in speed or capital efficiency.
Oracle’s applications business is undergoing a quiet but profound transformation through AI agent embedding, which is turning its SaaS suite from a system of record into an intelligent automation platform that competitors like Salesforce cannot replicate without sacrificing depth and integration. Mike Cecilia detailed the launch of three brand-new CX applications—lead generation, sales orchestration, and website generator—built entirely using AI coding tools and deployed internally to power oracle.com, demonstrating rapid product innovation. Over 1,000 AI agents are already embedded across horizontal and industry applications, including a live AI-powered EHR in healthcare reducing administrative overhead and enabling clinicians to see more patients. These are not superficial AI features but deep integrations into workflows like order-to-cash, procure-to-pay, and financial close, where Oracle’s decades of domain expertise and regulatory compliance create unbeatable switching costs. The AI Agent Studio in Fusion allows customers to build custom agents on top of Oracle’s prebuilt library, all tied to mission-critical data governed by Oracle’s security and compliance framework. This turns Oracle’s applications into an AI agent factory—where the platform itself becomes the development environment for enterprise AI—making it far harder to displace than point-solution AI tools that lack access to governed data and embedded processes.
Project Jupiter in New Mexico represents a strategic inflection point in Oracle’s ability to build sustainable, community-aligned AI infrastructure that mitigates ESG and regulatory risks while securing long-term locational advantages. The project will use up to 2.45 GW of Bloom Energy fuel cells—eliminating combustion, reducing NOₓ emissions by ~92%, and using negligible water through closed-loop cooling—directly addressing community concerns about air quality, water stewardship, and electricity rates. Oracle is承担 all energy costs, ensuring no impact on residential electricity, while committing $50 million to water systems, $360 million to schools and infrastructure, and $6.9 million to workforce development. This is not altruism; it is de-risking future expansion by turning potential opposition into advocacy. The campus will create 4,000 construction jobs and 1,500 ongoing roles, generating $113 million in annual economic impact post-construction. By securing clean power, water sovereignty, and community buy-in early, Oracle avoids the delays, protests, and retrofits that have plagued competitors’ data center builds. This model is replicable and positions Oracle to win sovereign and regulated workloads where competitors face permitting hurdles—turning ESG from a cost center into a competitive advantage in infrastructure siting.

▼ Bear case

Oracle Corporation’s aggressive AI infrastructure expansion is creating a mounting financial strain that threatens long-term profitability despite strong revenue growth, as evidenced by escalating capital expenditures and deteriorating free cash flow. The company spent $55.66 billion in capex during FY26—exceeding its $50 billion target—and now forecasts up to $95 billion for FY27, with $70 billion expected to be Oracle’s own spending and another $20–$25 billion reliant on uncertain customer repayments. Free cash flow deteriorated to a deficit of $23.7 billion in FY26 from just $394 million in FY25, a worsening trend that raises serious questions about the sustainability of its growth model. Management’s reliance on future customer repayments to offset capex introduces significant execution risk, as these are contingent on project completion, customer creditworthiness, and market demand holding—factors that are unproven at this scale. While Oracle highlights innovative financing models like bring-your-own-hardware, the sheer magnitude of spending suggests that even with partner funding, the company is absorbing substantial balance sheet risk. The gross margin for AI infrastructure, while above 30% guidance at 32%, is notably lower than the 60%-80% range claimed for database services, and the overall OCI margin profile remains under pressure as lower-margin infrastructure scales faster than higher-margin software. This capital intensity could force Oracle to choose between sacrificing growth, taking on more debt, or diluting shareholders—none of which are ideal outcomes for long-term value creation.
The company’s heavy reliance on a single, massive customer—OpenAI—for a significant portion of its AI infrastructure revenue creates a dangerous concentration risk that is being underappreciated amid the hype around AI growth. Oracle has a $300 billion, five-year commitment to supply computing power to OpenAI, a deal so large that any disruption in OpenAI’s trajectory could materially impact Oracle’s revenue visibility and capital utilization. Recent reports indicate OpenAI has missed internal user growth and revenue projections, sparking internal concern about its ability to fund future compute agreements, with finance chief Sarah Friar warning of potential funding shortfalls if growth does not accelerate. While Oracle publicly defended OpenAI’s trajectory, the market reacted sharply—ORCL shares dropped 3.4% and 4% on two separate occasions following negative OpenAI news—revealing investor sensitivity to this dependency. The OpenAI deal is not merely a revenue stream; it is driving Oracle’s entire AI infrastructure buildout, including Project Jupiter and multicloud expansions. If OpenAI’s growth slows due to competition from Anthropic, Google Gemini, or internal inefficiencies, Oracle could face severe underutilization of its newly built data centers, turning capex into stranded assets and pressuring margins. This concentration is exacerbated by the fact that Oracle’s AI infrastructure revenue growth (243% YoY) is heavily tied to this single relationship, making the business far less diversified than management implies.
Oracle’s applications business, while showing steady growth, is facing increasing competitive pressure from AI-native competitors and internal execution risks that could undermine its long-term SaaS leadership, despite management’s optimistic narrative about AI embedding. Cloud applications revenue grew only 11% in constant currency in Q3 FY26—modest compared to the triple-digit growth in AI infrastructure and multicloud database—suggesting the core SaaS engine is not benefiting proportionally from the AI hype. While Mike Cecilia highlighted new AI-powered CX applications and over 1,000 embedded agents, there was little discussion of customer adoption rates, upsell success, or churn trends for these features, raising questions about whether they are driving real value or merely serving as marketing collateral. The company continues to win large deals over Workday and SAP—such as Memorial Hermann, University of New South Wales, and a major Wall Street bank—but these are often multi-year transformations with long implementation cycles, meaning current revenue recognition lags behind deal signing. More troublingly, the AI Agent Studio and AI Data Platform, while technologically impressive, depend on customers having the internal expertise to build and deploy custom agents—a barrier that may limit adoption to only the most advanced enterprises. Meanwhile, competitors like Salesforce are investing heavily in their own AI agents (Einstein Copilot) and integrating with external models, potentially eroding Oracle’s differentiation if its ecosystem becomes too complex or costly to manage relative to simpler, more intuitive alternatives.
Sovereign cloud and industry-specific AI initiatives, while strategically appealing, are likely to remain niche opportunities with limited scalability and margin dilution, diverting focus from Oracle’s core strengths without delivering proportional returns. Mike Cecilia emphasized the Alloy model’s ability to deliver full-stack OCI services in sovereign zones across multiple countries, enabling enterprises to control data, operations, and contracting—but admitted that margins on these services differ from infrastructure margins and are not necessarily higher. The Africa Clinical Research Network partnership, while socially impactful, involves deploying clinical trial and safety solutions in resource-limited settings where pricing power is low and sales cycles are long, unlikely to meaningfully move the needle on total revenue. Similarly, Project Jupiter’s community investments—while reducing regulatory friction—represent a significant upfront and ongoing cost ($50M for water, $360M for schools, $6.9M for workforce) that is not directly tied to revenue generation and may compress returns on the data center investment. These initiatives reflect a noble mission but risk becoming costly distractions in a hypercompetitive AI infrastructure race where pure-play competitors like CoreWeave, Lambda Labs, and even AWS and Azure are driving down prices through scale and efficiency. Oracle’s attempt to be everything to everyone—database, AI infrastructure, SaaS, sovereign cloud, social impact—may spread its execution thin, preventing it from achieving dominance in any single high-growth area while incurring unnecessary complexity and cost.

Oracle Corporation’s aggressive AI infrastructure expansion is creating a mounting financial strain that threatens long-term profitability despite strong revenue growth, as evidenced by escalating capital expenditures and deteriorating free cash flow. The company spent $55.66 billion in capex during FY26—exceeding its $50 billion target—and now forecasts up to $95 billion for FY27, with $70 billion expected to be Oracle’s own spending and another $20–$25 billion reliant on uncertain customer repayments. Free cash flow deteriorated to a deficit of $23.7 billion in FY26 from just $394 million in FY25, a worsening trend that raises serious questions about the sustainability of its growth model. Management’s reliance on future customer repayments to offset capex introduces significant execution risk, as these are contingent on project completion, customer creditworthiness, and market demand holding—factors that are unproven at this scale. While Oracle highlights innovative financing models like bring-your-own-hardware, the sheer magnitude of spending suggests that even with partner funding, the company is absorbing substantial balance sheet risk. The gross margin for AI infrastructure, while above 30% guidance at 32%, is notably lower than the 60%-80% range claimed for database services, and the overall OCI margin profile remains under pressure as lower-margin infrastructure scales faster than higher-margin software. This capital intensity could force Oracle to choose between sacrificing growth, taking on more debt, or diluting shareholders—none of which are ideal outcomes for long-term value creation.
The company’s heavy reliance on a single, massive customer—OpenAI—for a significant portion of its AI infrastructure revenue creates a dangerous concentration risk that is being underappreciated amid the hype around AI growth. Oracle has a $300 billion, five-year commitment to supply computing power to OpenAI, a deal so large that any disruption in OpenAI’s trajectory could materially impact Oracle’s revenue visibility and capital utilization. Recent reports indicate OpenAI has missed internal user growth and revenue projections, sparking internal concern about its ability to fund future compute agreements, with finance chief Sarah Friar warning of potential funding shortfalls if growth does not accelerate. While Oracle publicly defended OpenAI’s trajectory, the market reacted sharply—ORCL shares dropped 3.4% and 4% on two separate occasions following negative OpenAI news—revealing investor sensitivity to this dependency. The OpenAI deal is not merely a revenue stream; it is driving Oracle’s entire AI infrastructure buildout, including Project Jupiter and multicloud expansions. If OpenAI’s growth slows due to competition from Anthropic, Google Gemini, or internal inefficiencies, Oracle could face severe underutilization of its newly built data centers, turning capex into stranded assets and pressuring margins. This concentration is exacerbated by the fact that Oracle’s AI infrastructure revenue growth (243% YoY) is heavily tied to this single relationship, making the business far less diversified than management implies.
Oracle’s applications business, while showing steady growth, is facing increasing competitive pressure from AI-native competitors and internal execution risks that could undermine its long-term SaaS leadership, despite management’s optimistic narrative about AI embedding. Cloud applications revenue grew only 11% in constant currency in Q3 FY26—modest compared to the triple-digit growth in AI infrastructure and multicloud database—suggesting the core SaaS engine is not benefiting proportionally from the AI hype. While Mike Cecilia highlighted new AI-powered CX applications and over 1,000 embedded agents, there was little discussion of customer adoption rates, upsell success, or churn trends for these features, raising questions about whether they are driving real value or merely serving as marketing collateral. The company continues to win large deals over Workday and SAP—such as Memorial Hermann, University of New South Wales, and a major Wall Street bank—but these are often multi-year transformations with long implementation cycles, meaning current revenue recognition lags behind deal signing. More troublingly, the AI Agent Studio and AI Data Platform, while technologically impressive, depend on customers having the internal expertise to build and deploy custom agents—a barrier that may limit adoption to only the most advanced enterprises. Meanwhile, competitors like Salesforce are investing heavily in their own AI agents (Einstein Copilot) and integrating with external models, potentially eroding Oracle’s differentiation if its ecosystem becomes too complex or costly to manage relative to simpler, more intuitive alternatives.
Sovereign cloud and industry-specific AI initiatives, while strategically appealing, are likely to remain niche opportunities with limited scalability and margin dilution, diverting focus from Oracle’s core strengths without delivering proportional returns. Mike Cecilia emphasized the Alloy model’s ability to deliver full-stack OCI services in sovereign zones across multiple countries, enabling enterprises to control data, operations, and contracting—but admitted that margins on these services differ from infrastructure margins and are not necessarily higher. The Africa Clinical Research Network partnership, while socially impactful, involves deploying clinical trial and safety solutions in resource-limited settings where pricing power is low and sales cycles are long, unlikely to meaningfully move the needle on total revenue. Similarly, Project Jupiter’s community investments—while reducing regulatory friction—represent a significant upfront and ongoing cost ($50M for water, $360M for schools, $6.9M for workforce) that is not directly tied to revenue generation and may compress returns on the data center investment. These initiatives reflect a noble mission but risk becoming costly distractions in a hypercompetitive AI infrastructure race where pure-play competitors like CoreWeave, Lambda Labs, and even AWS and Azure are driving down prices through scale and efficiency. Oracle’s attempt to be everything to everyone—database, AI infrastructure, SaaS, sovereign cloud, social impact—may spread its execution thin, preventing it from achieving dominance in any single high-growth area while incurring unnecessary complexity and cost.

Product and Service Breakdown of Revenue (2026)

Peer Comparison

Companies in the Software - Infrastructure

S.No.	Ticker	Company	Market Cap	P/E	P/S	Total Debt (Qtr)
1	MSFT	Microsoft Corp	2,853.66 Bn	22.79	8.97	40.26 Bn
2	ORCL	Oracle Corp	408.21 Bn	23.92	6.06	122.34 Bn
3	PLTR	Palantir Technologies Inc.	300.98 Bn	131.24	57.61	-
4	PANW	Palo Alto Networks Inc	247.84 Bn	193.34	25.05	-
5	CRWD	CrowdStrike Holdings, Inc.	193.63 Bn	-1,201.41	40.24	0.75 Bn
6	FTNT	Fortinet, Inc.	117.45 Bn	60.08	16.52	0.50 Bn
7	NET	Cloudflare, Inc.	86.88 Bn	-1,001.47	37.31	1.29 Bn
8	SNPS	Synopsys Inc	86.18 Bn	1,416.99	10.76	10.04 Bn

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Product and Service Breakdown of Revenue (2026)

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Consolidation Items Breakdown of Revenue (2026)

Product and Service Breakdown of Revenue (2026)

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