Jabil (JBL) Earnings Preview: Is AI Data Center Demand the Key to a FY2027 Breakout?

 

Jabil (NYSE: JBL) reports fourth quarter and full fiscal year 2026 results before the market opens on Wednesday, September 30, followed by a call that doubles as the company's annual investor briefing. According to Jabil's own announcement, management will use the session to lay out strategic and financial priorities for fiscal 2027. That framing matters, because the quarter itself is largely pre-guided. The fiscal 2027 outlook is the event.

 

The reason the market is watching closely is that Jabil has stopped trading as a conventional electronics manufacturing services name and started trading as an AI infrastructure supplier. On the June call, management put fiscal 2026 AI-related revenue at roughly $13.6 billion, up about 50% from $9 billion in fiscal 2025. The share price has not followed that curve. JBL changed hands at $310.13 on September 24, well below its June peak, against a 52-week range of $189.60 to $428.93. The gap between the operating trajectory and the multiple the market is willing to pay is what the September 30 guidance has to close.

 

 

 

The quarter is guided, the year is not. Management set fourth quarter revenue at $9.2 billion to $10.0 billion and core diluted EPS at $3.80 to $4.20. Consensus sits near the upper half of that band, which leaves the fiscal 2027 outlook as the swing factor.

 

AI revenue is now the dominant variable. At roughly $13.6 billion, AI-related revenue accounts for close to 40% of the $35 billion full-year figure. Management has signaled that fiscal 2027 percentage growth should look similar to fiscal 2026, off a materially larger base.

 

Margin is the second storyline. Fiscal 2026 core operating margin is guided at 5.8%, and management expects to move above 6% in fiscal 2027 on mix, higher-value power and cooling content, and operating leverage as new sites ramp.

 

The de-rating came from valuation, not results. Goldman Sachs kept a Buy rating on September 8 while cutting its target to $375 from $482, and the stock fell 5.1% that session. Other desks moved the other way over the same stretch.

 

Risk sits in the supply chain and the customer list. Third quarter inventory days ran at 84 against a 55 to 60 day norm, with high-bandwidth memory and high-density boards still tight, while hyperscaler concentration cuts both ways.

 

 

 

Jabil's third quarter results filed with the SEC put net revenue for the quarter ended May 31, 2026 at $8.751 billion, against $7.828 billion a year earlier, growth of roughly 12%. GAAP operating income was $445 million and GAAP diluted EPS $2.59, while core operating income reached $504 million and core diluted EPS $3.16, up about 24% year over year. Revenue growing 12% while core EPS grows 24% is the part worth dwelling on.

 

The same release raised the fiscal 2026 outlook to approximately $35 billion of revenue, 5.8% core operating margin, $12.70 of core diluted EPS and more than $1.4 billion of adjusted free cash flow. Fiscal 2025 revenue was roughly $29.8 billion for comparison. The nine-month figures support the trend: revenue rose from $21.550 billion to $25.338 billion, and adjusted free cash flow from $813 million to $991 million.

 

 

On the third quarter call, Chief Executive Mike Dastoor put fiscal 2026 AI-related revenue at approximately $13.6 billion. A summary of the accompanying slide deck notes that figure was $500 million above the March outlook of $13.1 billion and represents roughly 50% growth from $9 billion in fiscal 2025. Dastoor added that he expects fiscal 2027 AI-related revenue growth in percentage terms to be similar to fiscal 2026, sustained off a much larger base.

 

One caveat deserves emphasis. AI-related revenue is a company-defined measure, not a reporting segment. It spans high-density racks, liquid cooling, power management, networking and related integration work. The advantage of that framing is that it captures where the business is shifting. The cost is that it does not compare cleanly across peers. What investors should look for on September 30 is whether management attaches a dollar range to fiscal 2027 AI-related revenue and how that range sits against total revenue guidance.

 

 

Two disclosures from the June call bear directly on fiscal 2027 and 2028. The first is a third hyperscale customer win across the data center infrastructure space, with management describing initial revenue in the couple of hundred million dollar range for fiscal 2027, expanding toward $1 billion and beyond in fiscal 2028. The second is the capacity schedule: a new North Carolina facility on track for completion in the fourth quarter with a full ramp expected by January 2027, alongside additions in Memphis, India and Mexico.

 

The longer-dated piece points to India. Per the joint announcement from Jabil and Adani on June 15, the two intend to form a strategic alliance to build a vertically integrated AI and data center infrastructure manufacturing platform in India, targeting gigawatt-scale high-density AI rack capacity. The plan dovetails with Adani Group's commitment to invest $100 billion toward 5 GW of green-energy-powered AI-ready data centers by 2035. Management was explicit on the call that this is a fiscal 2028 event gated by capacity build-out, so it will not appear in this guidance, though it shapes how the market frames the medium-term ceiling.

 

 

 

Shares jumped more than 10% after the June print and have drifted lower since. Market commentary noted the stock at $300.67 in mid-September, still up about 25% year to date but well below its June high. The proximate trigger was Goldman Sachs analyst Mark Delaney trimming his price target to $375 while keeping a Buy rating.

 

Sell-side opinion is anything but uniform. Per Benzinga's roundup of analyst actions, UBS upgraded the stock from Neutral to Buy with a $430 target on August 11, JP Morgan maintained Overweight and raised its target from $395 to $450 on June 18, and Barclays lifted its target from $304 to $426 the same day. Consensus for the quarter sits near $4.05 of EPS on about $9.61 billion of revenue. The disagreement is not about the earnings path. It is about the multiple that path deserves.

 

 

Jabil is not alone in this. Celestica reported second quarter revenue of $4.70 billion, up 62% year over year, with adjusted EPS of $2.54 and a raised annual outlook, according to its quarterly results filing. Flex has grown far more modestly. Valuation dispersion across electronics manufacturing services now tracks how deeply each name participates in AI racks and networking rather than headline revenue.

 

The macro backdrop remains supportive. CNBC's tally put combined 2026 capital spending by the four largest hyperscalers close to $700 billion, with subsequent updates lifting that toward roughly $725 billion, up about 77% from $410 billion in 2025. Street forecasts for 2027 cluster near $1 trillion. The composition of that funding is changing, though. A growing share is financed with debt and customer prepayments rather than operating cash flow, and a September capex roundup found seven AI builders spent $657 billion over their last four reported quarters with none cutting guidance. On September 24, Akamai disclosed that its $11.6 billion agreement with Anthropic carries roughly $5.5 billion of associated capital expenditure, with about $1.7 billion added to 2026 capex to pre-purchase critical components including memory. For upstream manufacturers that kind of pre-buy improves visibility, and it also pulls demand forward.

 

 

 

The first is the fiscal 2027 revenue and core EPS range. Management already flagged core operating margin moving above 6%. Guidance below that line would read as AI rack integration diluting margin more than expected.

 

The second is a dollar figure for AI-related revenue. UBS has argued that Jabil's AI-related revenue could grow roughly 50% to more than $20 billion in fiscal 2027. A materially lower number would likely pull the valuation anchor down with it, while a number at or above that level would recast the recent pullback as sentiment rather than substance.

 

The third is capital intensity. Management has framed the AI business as asset-light, with capital expenditure expectations of 1.5% to 2% of revenue. Whether that holds through a period of aggressive capacity addition determines the cash quality of the growth.

 

 

Per the company's July 15 announcement, the board authorized a new repurchase program of up to $1.5 billion. The most recent 10-Q shows $891 million deployed and 3.7 million shares repurchased under the fiscal 2026 program through May 31, leaving $109 million available. Since 2016, Jabil has returned roughly $8 billion to shareholders and repurchased approximately 114 million shares at an average price of $65.66. With the share count shrinking steadily, part of EPS growth comes from the denominator, and separating that from operating improvement is essential to judging the quality of the trend.

 

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Supply chain is the most immediate exposure. Inventory days ran at 84 in the third quarter against a 55 to 60 day norm, which management tied to tightness in high-bandwidth memory, high-density circuit boards and certain legacy memory products. Rising memory prices absorb working capital and press on gross margin at the same time.

 

Customer concentration is the second. Three hyperscale relationships deliver the growth torque, and any one of them adjusting its order cadence moves reported revenue. Contract structures in this industry typically allow customers latitude to flex demand, which makes short-cycle volatility difficult to engineer away.

 

Third is the timing mismatch between capacity and demand. North Carolina reaches full ramp in January 2027, while the India platform contributes only from fiscal 2028. If industry capital spending enters a digestion phase in between, utilization on new capacity gets tested.

 

Last is valuation itself. When a company is priced as an AI infrastructure name rather than a manufacturing services provider, the multiple becomes far more sensitive to guidance, which is broadly what September's target cut demonstrated.

 

 

In the constructive case, fiscal 2027 AI-related revenue lands at or above roughly $20 billion, core operating margin guidance sits clearly above 6%, and capital expenditure stays within 2% of revenue. That combination shifts the debate from whether the growth is real to how long it lasts.

 

In the base case, AI-related revenue keeps compounding but decelerates modestly from fiscal 2026, margin guidance clears 6% by a narrow margin, and management leans on supply constraints and ramp timing. Shares would likely stay range-bound pending the first two quarters of fiscal 2027.

 

In the pressured case, memory costs or customer scheduling produce a conservative range, or the AI revenue definition is revised. Given that September already removed some valuation risk, the marginal impact on the stock would depend on the size of the miss rather than its direction.

 

 

The fiscal 2027 first quarter revenue and margin guide tells more about current order cadence than the annual figure does. Disclosure on hyperscaler revenue concentration indicates how diversified the growth really is. Any update on the India platform timeline moves the medium-term ceiling. And the calendar fourth quarter reporting season, when the largest hyperscalers set 2027 capital spending plans, remains the shared upstream variable for the entire chain.

 

 

For James Mitchell, the informational weight of this report sits less in the September 30 quarter than in how management characterizes the composition of fiscal 2027 AI-related revenue. At $13.6 billion, that business is approaching 40% of a $35 billion revenue base, and once a line item reaches that scale its growth rate stops being incremental and starts being the model. Quantitatively, 12% revenue growth against 24% core EPS growth shows operating leverage working, but it also embeds a buyback effect, with $891 million deployed in the first nine months. Splitting those two apart is how to judge how much margin improvement is structural and how much is financial engineering.

 

Two misreadings look plausible. The first is treating a target cut as a fundamental downgrade. Goldman lowered its target while maintaining a Buy rating, which is closer to a multiple reset than a rejection of the earnings path, and UBS moved in the opposite direction over the same window. The second is pulling the Adani alliance into near-term numbers. Management said plainly it is a fiscal 2028 event gated by capacity build-out, so counting it in fiscal 2027 expectations creates a timing mismatch. It also bears repeating that AI-related revenue is a company-defined measure, which makes cross-company comparison a hazardous exercise.

 

Three quantifiable threads are worth tracking from here. The first is where core operating margin lands relative to the 6% line, together with management commentary on the share of revenue coming from higher-value power and cooling content. The second is whether inventory days retrace from 84 toward the 55 to 60 day norm, the cleanest available read on supply chain tightness. The third is capital expenditure as a percentage of revenue, which determines whether this is an asset-light scaling story or the beginning of a capital-heavy cycle. Technically, the stock has returned to the middle of its 52-week range, and the post-print move will be set by the distance between guidance and expectations rather than by any particular price level.

 

The cross-asset lesson runs wider than one company. Funding for AI infrastructure is migrating from operating cash flow toward debt and customer prepayments, and Akamai booking roughly $1.7 billion of component purchases ahead of its Anthropic agreement is a concrete instance of it. Upstream manufacturers gain order visibility from that behavior, but the visibility rests on downstream financing conditions. Tracking the absolute level of hyperscaler capital spending matters. Tracking how it is funded may matter just as much, because that is what determines how resilient the demand curve looks under stress.

 

 

 

Jabil releases fourth quarter and full fiscal year 2026 results before the market opens on Wednesday, September 30, 2026, with a conference call and webcast at 8:30 a.m. ET. The session also serves as the company's annual investor briefing, where management outlines strategic and financial priorities for fiscal 2027, which typically carries more information value than a routine quarterly call.

 

 

Management guided to revenue of $9.2 billion to $10.0 billion, core diluted EPS of $3.80 to $4.20 and GAAP diluted EPS of $3.24 to $3.64. Consensus sits near $4.05 of EPS on roughly $9.61 billion of revenue, in the upper half of that range. After several consecutive guidance raises, a beat on the quarter may matter less at the margin than the fiscal 2027 outlook.

 

 

The company expects fiscal 2026 AI-related revenue of approximately $13.6 billion, up about 50% from $9 billion in fiscal 2025 and $500 million above the March outlook of $13.1 billion. Management has indicated fiscal 2027 percentage growth should be similar. This is a company-defined measure covering racks, liquid cooling, power and networking work, not a standard reporting segment, so cross-company comparisons require care.

 

 

Shares rose more than 10% after the June results and have since retreated, with the pressure coming from valuation rather than operations. Goldman Sachs cut its target to $375 from $482 on September 8 while keeping a Buy rating, and the stock fell 5.1% that session. Over the same period UBS upgraded to Buy with a $430 target, and JP Morgan and Barclays carried targets of $450 and $426.

 

 

Jabil and Adani announced their intent to form a strategic alliance on June 15, 2026, targeting a vertically integrated AI and data center infrastructure manufacturing platform in India at gigawatt scale. Management stated on the earnings call that this is a fiscal 2028 event, gated primarily by capacity construction. It should not be modeled into fiscal 2027 revenue, though it informs the medium-term growth ceiling.

 

 

Three items carry the most weight: whether core operating margin guidance clears the 6% level management flagged, whether a dollar range is attached to fiscal 2027 AI-related revenue and how it compares with total revenue, and whether capital expenditure stays near the previously indicated 1.5% to 2% of revenue. Inventory days retracing from 84 would also signal easing supply constraints.

 

 

On supply, high-bandwidth memory and high-density boards remain tight, and rising memory prices lift working capital needs while pressuring cost. On customers, three hyperscale relationships provide the growth torque and the concentration risk simultaneously. On capacity, the North Carolina site reaches full ramp in January 2027, leaving utilization exposed if industry capital spending enters a digestion phase. Valuation sensitivity to guidance is elevated for the same reason the stock re-rated upward.

 

 

The information above is provided for general market information and analysis only and does not constitute investment advice, financial advice, legal advice, tax advice or a recommendation to trade. Prices of equities, crypto assets and other related financial instruments can fluctuate sharply, and past performance, technical indicators and on-chain data do not guarantee future results. The financial figures, company guidance, analyst targets and market statistics cited reflect publicly available information at the time of writing and may be superseded by subsequent disclosures, so the latest official filings from the relevant companies and regulators should be treated as authoritative. Readers should conduct their own research and make decisions based on their own financial circumstances, investment objectives and risk tolerance, consulting a qualified professional where appropriate. The MEXC Crypto Pulse team accepts no liability for any direct or indirect loss arising from the use of this information.

 

 

James Mitchell specializes in technical analysis, market trends, and trading strategies for both Bitcoin and altcoins. Based in London, he has over 10 years of experience in financial markets. Before joining MEXC Learn, James worked as a senior analyst at a leading European investment firm, where he developed expertise in risk management and quantitative trading. His transition to cryptocurrency markets began in 2017, and he has since become recognized for his data-driven approach. He holds a Master's degree in Financial Economics from the London School of Economics. His analytical approach combines traditional technical analysis with on-chain metrics to provide readers with actionable insights.

 

His areas of expertise span technical analysis, market trends and cycles, trading strategies, Bitcoin and altcoin analysis, and risk management.

 

 

 

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