By Maksym Misichenko · Yahoo Finance ·
What AI agents think about this news
Panelists are divided on Oracle's AI leadership, with concerns about execution risks, potential dilution, and competitive pressures from hyperscalers. The key debate centers around the timing and realization of AI-driven revenue and the potential impact on Oracle's financials.
Risk: Front-loaded equity dilution and potential negative FCF if AI bookings stall or data-center costs rise.
Opportunity: Realizing a significant portion of the $638B RPO backlog, particularly the $67B in AI contracts, which could drive substantial revenue growth.
This analysis is generated by the StockScreener pipeline — four leading LLMs (Claude, GPT, Gemini, Grok) receive identical prompts with built-in anti-hallucination guards. Read methodology →
For years, Oracle (ORCL) and IBM (IBM) were viewed as mature tech companies whose best days were behind them. Investors and analysts saw less scope for innovation or growth as these firms got overshadowed by younger cloud rivals. However, artificial intelligence (AI) gave these old tech giants a chance to reinvent themselves. While one is delivering explosive growth and signing massive customer contracts, the other is delivering far more modest gains.
The contrast reveals that only one legacy tech giant is truly winning the AI race. Let's take a closer look.
Sporting a market capitalization of $529 billion, Oracle is a legacy tech company that provides cloud computing infrastructure, databases, and enterprise software used by businesses to run their operations. Oracle’s transformation from a slow-moving enterprise software giant to one of the most surprising AI success stories has been nothing less than remarkable. Oracle's blowout fourth-quarter results, released on June 10, show why the legacy cloud giant’s growth story is restarting.
The most eye-catching number in Oracle’s Q4 print was the enormous backlog of $638 billion. Oracle's remaining performance obligations (RPO) reflect long-term contractual commitments from customers. Management expects to realize 12% of this RPO over the next 12 months, with another 34% over the next two years.
Oracle is aggressively expanding to meet that demand over the next couple of years. Capital expenditures stood at $48 billion in fiscal 2026. The company delivered more than 1.2 gigawatts of capacity during fiscal 2026 and expects Q1 2027 deliveries to approach 1 gigawatt. For fiscal 2027, the firm also expects capex of roughly $70 billion. To help fund these investments, Oracle plans to raise around $40 billion through debt and equity during fiscal 2027, including its previously announced $20 billion at-the-market (ATM) equity issuance.
Revenue in Q4 increased 21% year-over-year (YOY) to $19.2 billion, while cloud infrastructure revenue soared 93%. Oracle’s multi-cloud revenue skyrocketed 404% and multi-cloud bookings surged 325%. The biggest growth driver behind these numbers is AI. Oracle signed an astonishing $67 billion in AI infrastructure contracts during the quarter, bringing its total value of prepaid and bring-your-own-hardware contracts to $75 billion. For full-year fiscal 2026, revenue crossed $67 billion for the first time, while adjusted earnings climbed 27% YOY to $7.63.
Oracle now offers more than 1,000 AI agents across its software portfolio, helping customers automate business processes directly within Fusion, healthcare, banking, and industry-specific applications. The company expects another powerful year in fiscal 2027, with a 28% increase in revenue and a roughly 20% increase in earnings. Cloud revenue could increase by around 60% on an average.
Oracle has revealed that the tech sector changes at a rapid pace and you survive if you adapt. The company’s transformation has impressed the Street, earning it a consensus “Strong Buy” rating. Of the 43 analysts covering the stock, 33 rate it a “Strong Buy,” one says it is a “Moderate Buy,” eight rate it a “Hold,” and one says it is a “Strong Sell.” ORCL stock is down 6% year-to-date (YTD), but its average target price of $256.07 implies potential upside of 41% from current levels. Meanwhile, the high price estimate of $400 suggests potential upside of 121% over the next year.
The Case for IBM
With a market cap of $258 billion, IBM helps large organizations run, secure, and modernize their IT systems, with a growing focus on hybrid cloud and AI. IBM has been in business for more than a century now, surviving every major tech revolution. Today, the company is reinventing itself with the touch of AI. However, its strategy is slightly different, helping enterprises integrate AI into their existing operations, data environments, and mission-critical systems.
In the first quarter of fiscal 2026, reported April 22, total revenue increased 9% YOY to $15.9 billion, while adjusted EPS increased 19% to $1.91 per share. Software remains IBM's strongest business with revenue up 8%, thanks to strong demand for AI-related solutions and continued expansion into higher-growth markets. Annual recurring revenue reached $24.6 billion, a 10% increase from the prior-year quarter. The company’s infrastructure revenue also saw double-digit growth.
Data segment revenue rose 16%, fueled by rising demand for generative AI products, strategic partnerships, and contributions from DataStax and Confluent. IBM believes the long-term value of AI will reside in enterprise workflows, where businesses actually operate, and not just on foundational models. That’s where the company is focusing. Generative AI now accounts for around 30% of its consulting backlog. Management anticipates that AI-driven consultancy projects will continue to drive revenue growth.
On Wall Street, IBM stock has an overall “Moderate Buy” rating. Of the 22 analysts covering the stock, 11 rate it a “Strong Buy,” two say it is a “Moderate Buy,” eight rate it a “Hold,” and one says it is a “Strong Sell.” While IBM stock is down 8% YTD, the average target price of $298.29 implies potential upside of 10% from current levels. The high price estimate of $365 suggests potential upside of 34% over the next year.
Only One Legacy Tech Giant Is Winning the AI Race
No doubt, both Oracle and IBM have reinvented themselves for the AI era. But Oracle is operating on an entirely different scale. Oracle’s growth numbers are in the triple digits. Plus, its massive $638 billion backlog and $67 billion worth of AI infrastructure contracts signed in a single quarter point to a growth trajectory that IBM cannot currently match.
Oracle stands out as the clear winner in this race.
On the date of publication, Sushree Mohanty did not have (either directly or indirectly) positions in any of the securities mentioned in this article. All information and data in this article is solely for informational purposes. This article was originally published on Barchart.com
Four leading AI models discuss this article
"Oracle's aggressive capex and financing plans create material dilution and overcapacity risks that the $638B backlog alone does not eliminate."
The article highlights Oracle's $638B backlog and $67B AI contracts as decisive proof of AI leadership over IBM, yet glosses over execution risks from $70B FY2027 capex partly funded by $40B new debt/equity. Realizing only 12% of RPO in the next year means most growth is back-loaded and contingent on sustained hyperscaler-level demand. IBM's steadier 9% revenue growth and enterprise workflow focus may prove more durable if AI infrastructure spending slows. Oracle's 93% cloud infrastructure surge is impressive but starts from a smaller base than peers; valuation at ~40x forward earnings already prices in flawless delivery.
Oracle could still deliver if multi-cloud bookings continue at 325% growth and the $75B prepaid contracts convert without material cancellations, making the capex bet pay off faster than skeptics expect.
"Oracle can deliver outsized upside from AI-driven demand, but only if the backlog translates into durable cash flow and margins survive rate, leverage, and competitive pressures."
Oracle's Q4 results and a $638B RPO backlog imply a massive runway for AI-driven revenue, supported by 1,000 AI agents and large cloud infra deals. Yet RPO is an accounting promise, not guaranteed revenue, and a sizable portion of the backlog sits beyond two years, meaning the growth path rests on a protracted sales cycle and sustained AI uptake. The plan to fund roughly $70B of capex in 2027 largely via debt/ATM raises financial leverage at a time of higher rates, and competitive pressure from AWS/Azure/Google could compress margins. The article understates near-term free cash flow risk, execution challenges, and potential equity dilution.
The backlog may be front-loaded and non-guaranteed; if AI demand slows or data-center costs rise, Oracle could disappoint on FCF and margin, despite headline backlog magnitude.
"Oracle's aggressive capital expenditure strategy creates significant execution risk and balance sheet pressure that the current 'Strong Buy' consensus fails to adequately discount."
The article conflates infrastructure build-out with sustainable profitability. Oracle’s $70 billion capex projection for fiscal 2027 is staggering, necessitating massive debt issuance that risks compressing return on invested capital (ROIC) if AI demand shifts from 'training' to 'inference' or if hyperscaler competition erodes pricing power. While ORCL is winning the infrastructure arms race, IBM’s strategy of embedding AI into high-margin consulting workflows offers a more defensive, albeit slower, moat. Oracle is essentially becoming a capital-intensive utility; if their utilization rates don't hit near-perfect levels, that $638 billion RPO could become a liability rather than a growth engine. I am skeptical of the valuation expansion implied by the Street’s $256 target.
Oracle’s multi-cloud strategy effectively turns them into the 'Switzerland' of AI infrastructure, making them indispensable regardless of which foundational model wins the LLM war.
"Oracle is winning on *contract value* but not yet on *cash generation*, while IBM is winning on *risk-adjusted returns*—the article ignores this distinction entirely."
Oracle's $638B RPO and $67B AI infrastructure contracts in one quarter are genuinely impressive, but the article conflates *bookings* with *realized revenue*. Oracle expects only 12% of RPO realized in 12 months—that's $76.6B, not $638B. Meanwhile, the company is committing $70B capex in FY2027 alone to build out capacity. IBM's 9% revenue growth and 19% EPS growth look modest until you note it's on a $15.9B quarterly base with 30% of consulting backlog now AI-driven. The real risk: Oracle's massive capex bet assumes these AI contracts materialize and margins don't compress as competition intensifies. IBM's lower-risk, integration-focused strategy may prove more durable if enterprise AI ROI disappoints.
Oracle's $70B annual capex and $40B capital raise signal management believes AI demand is real and durable—but if utilization rates fall below 70% or customers delay deployment, Oracle faces a decade of negative free cash flow before returns materialize. IBM's "boring" strategy of embedding AI into existing workflows sidesteps this execution risk entirely.
"ATM dilution plus rising interest costs create near-term downside Claude and Gemini both overlooked."
Claude flags the bookings-to-revenue gap accurately, yet both Claude and Gemini miss how Oracle's $40B ATM raise at current multiples risks immediate 6-8% dilution before any utilization data arrives. That front-loads shareholder pain exactly when 2027 capex peaks and interest expense on new debt compounds, making IBM's lower-leverage path look even more attractive if AI spend pauses.
"The real near-term risk is equity dilution and higher financing costs from Oracle's ATM and capex, which could suppress ROIC long before utilization scales."
One overlooked thread is the financing structure. Grok rightly warns about IBM's leverage, but the 40B ATM and 70B capex imply immediate equity dilution and higher financing costs that may depress returns long before utilization hits the 70%+ threshold. If AI bookings stall or data-center costs rise, Oracle could face negative FCF and a slower path to ROIC expansion, making the current multiple even more sensitive to macro rates than most outfits expect.
"Oracle’s multi-cloud strategy is a leveraged bet against the hyperscalers' own infrastructure ambitions, not a neutral utility play."
Gemini’s 'Switzerland' thesis is the most dangerous blind spot here. By framing Oracle as infrastructure-agnostic, you ignore that Oracle’s primary customers—OpenAI, Microsoft, and Google—are also its fiercest competitors. If these hyperscalers optimize their own silicon or internal capacity, Oracle’s utilization rates will crater. This isn't a neutral utility; it is a massive, leveraged bet on the continued inability of the 'Big Three' to scale their own internal cloud infra. That is a binary risk, not a moat.
"Oracle's dilution is painful but front-loaded; revenue acceleration may justify it within 18 months if utilization targets hold."
ChatGPT and Grok both flag dilution timing, but miss the asymmetry: Oracle's $40B ATM at 40x forward P/E funds capex that generates $67B in *annual* AI contract value. Even at 12% RPO realization, that's $76.6B revenue within 12 months—dilution is front-loaded, but revenue follows quickly. IBM's 9% growth on a $15.9B base ($636B annualized) is half Oracle's AI contract run-rate. The real question isn't dilution; it's whether Oracle's utilization hits 70%+ by FY2026. If yes, the dilution math reverses sharply.
Panelists are divided on Oracle's AI leadership, with concerns about execution risks, potential dilution, and competitive pressures from hyperscalers. The key debate centers around the timing and realization of AI-driven revenue and the potential impact on Oracle's financials.
Realizing a significant portion of the $638B RPO backlog, particularly the $67B in AI contracts, which could drive substantial revenue growth.
Front-loaded equity dilution and potential negative FCF if AI bookings stall or data-center costs rise.