Analyst Ratings January 23, 2026

Morgan Stanley Highlights Significant AI Infrastructure Spending in Oracle's Backlog

Investment Bank Warns Market May Be Underestimating Oracle's Capital Demands Linked to AI Commitments

By Hana Yamamoto ORCL
Morgan Stanley Highlights Significant AI Infrastructure Spending in Oracle's Backlog
ORCL

Morgan Stanley warns that Oracle Corporation's substantial growth in contracted customer commitments includes a large portion dedicated to AI infrastructure, particularly for projects involving OpenAI. The investment bank highlights the significant capital expenditures necessary to build this AI compute capacity and projects these costs will impact Oracle's future earnings estimates.

Key Points

  • Oracle's backlog of contracted customer commitments has increased by $426 billion in the past year, totaling $523 billion in remaining performance obligations, providing substantial revenue visibility over five years.
  • Approximately 60% of Oracle's backlog is tied to AI compute infrastructure acquisition, with partnerships including OpenAI driving demand.
  • Morgan Stanley projects Oracle will need to invest heavily—more than $356 billion in cash capital expenditures and $185 billion in lease liabilities—to build and operate over 10 gigawatts of AI compute infrastructure by 2030, impacting future earnings estimates.

Morgan Stanley has raised important considerations regarding Oracle Corporation's (NYSE: ORCL) investment obligations connected to its expanding backlog of customer contracts. Over the past year, Oracle's backlog of contracted commitments has surged by $426 billion, reaching a current total of $523 billion in remaining performance obligations. This sizable backlog offers Oracle notable revenue visibility extending approximately five years.

However, Morgan Stanley draws attention to the fact that nearly 60% of this backlog—over $300 billion—is linked to customers securing infrastructure specifically for AI compute applications, including major partnerships like OpenAI. This focus on AI-related infrastructure implies considerable expenditure, given the capital-intensive nature of such assets.

The investment bank estimates that building a gigawatt of greenfield AI compute infrastructure could require as much as $35 billion in capital investment. Oracle aims to expand its AI compute capacity beyond 10 gigawatts by the close of its fiscal year 2030, a substantial undertaking by any measure.

This scale of expansion translates into an anticipated $356 billion in cumulative cash capital expenditures dedicated to IT equipment, such as GPUs essential for powering AI workloads. Additionally, Oracle could incur finance lease liabilities worth approximately $185 billion stemming from data center 'powered shells' necessary for this infrastructure growth.

Reflecting these capital requirements, Morgan Stanley has revised its base case earnings per share (EPS) forecasts for Oracle. The projections now stand at $8.51 for fiscal year 2028 and $10.02 for fiscal year 2030, figures notably lower than Oracle's own targets of $10.65 and $21.00 and below consensus estimates of around $10.68 and $19.67.

In parallel developments, Morgan Stanley has adjusted its price target for Oracle down to $213, expressing reservations about the profitability impact of the company's GPU-as-a-Service operations. Conversely, Guggenheim maintains a Buy rating for Oracle with a $400 price target, designating it as its 'Best Idea' within the software sector. KeyBanc Capital Markets also continues to hold an Overweight rating with a $300 price target, distinguishing between Oracle's traditional core business and its growing infrastructure division.

Additional corporate developments include Oracle's anticipated transaction to acquire TikTok's U.S. operations, alongside Silverlake and other American investors. Meanwhile, Oracle faces legal pressure as bondholders have initiated a proposed class action lawsuit, criticizing the company for allegedly not disclosing their intent to issue more debt to finance AI infrastructure expansion.

These dynamics illustrate a complex environment for Oracle, balancing extensive growth opportunities in AI infrastructure against the significant capital demands and regulatory scrutiny that accompany them.

Risks

  • The significant capital intensity required to develop AI compute infrastructure could constrain Oracle's financial performance and delay anticipated earnings growth, affecting investor returns and valuation.
  • Ongoing legal challenges, including a bondholders' class action lawsuit alleging nondisclosure of additional debt issuances, introduce regulatory and reputational risks for Oracle.
  • Market skepticism highlighted by Morgan Stanley's reduced price target points to uncertainty regarding the profitability and strategic viability of Oracle's GPU-as-a-Service business segment.

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