This Underrated Artificial Intelligence (AI) Infrastructure Stock Has Surged 80% in a Year. It Can Still Surge 53%.

Adjusted EPS rose 39% YoY to $2.69 and revenue jumped 23% YoY to $8.3B in fiscal Q2; Jabil raised fiscal 2026 EPS guidance to $12.25 (from $11.55) and now expects AI revenue to increase 46% to $13.1B. The company is pursuing a third hyperscaler customer, completed a $500M capacity expansion (on track), has capacity utilization at 75% targeting 80%, and sees adjusted operating margin expanding to >6% (vs prior 5.7%), supporting upside to the stock.

Analysis

Jabil’s ramp in AI-related builds is less a pure demand story and more a fixed-cost absorption story: incremental hyperscaler orders will flow almost directly to operating margin as newly commissioned capacity and tooling are already installed. That creates a convex earnings profile where a handful of large order wins — not steady broad-market growth — materially drives EPS beats over the next 12–24 months.

The most important second-order effect is on component suppliers and aftermarket services. Faster adoption of liquid cooling and custom rack designs shifts value to specialized cold-plate, pump and assembly suppliers and creates a recurring serviceable-revenue stream (maintenance, retrofits, decommissions) that incumbents often under‑price. Conversely, traditional OEMs and smaller EMS players without dedicated AI-factory assets risk margin compression as hyperscalers favor scale partners with integrated thermal/power expertise.

Key near-term catalysts are discrete: announcement of new hyperscaler contracts, quarterly capacity-utilization inflection, and visible pricing trends for cooling subsystems. Tail risks are concentrated — a large hyperscaler pause, accelerated vertical integration by a hyperscaler, or a component bottleneck that forces Jabil into guaranteed-delivery discounts could flip the narrative quickly within a single quarter.

The consensus appears to treat Jabil purely as an AI exposure play and underweights business-model optionality (recurring service revenue + proprietary rack IP) while also understating mean-reversion risk once capacity saturates. Trade sizing should therefore target event-driven convexity: asymmetric option structures or pairs that capture upside from order flow while limiting downside from cyclical capex pauses.

Key Decisions for Investors

• Long JBL via defined-risk LEAP call spread: Buy JBL Jan-2028 1–2yr LEAP call and sell a higher strike to finance cost (target 40–60% upside, max loss = premium paid). Rationale: captures convex EPS leverage from large order wins while capping premium decay. Timeframe: 12–24 months.
• Pair trade to isolate manufacturing share: Long JBL equity (small size) / Short FLEX (equal notional) for 6–18 months. Rationale: long exposure to AI‑optimized factory footprints, short the diversified EMS that may see weaker operating leverage. Risk control: 15–20% stop on either leg; target asymmetric return of 2:1 if JBL re-rates versus FLEX.
• Event-driven options ahead of expected hyperscaler win: Buy JBL 2–3 month call spread (near-term expiration) entering within 2–6 weeks of the announced customer close window. Rationale: small-cost ticket to capture announcement-driven gap; limit premium loss if deal slips. Take profits on announcement or cut at 50% of premium.
• Hedged upside capture: If worried about a broader AI capex chill, buy JBL call spread and simultaneously buy a short-dated put on a hyperscaler-heavy ETF as portfolio hedge (e.g., option on NVDA-heavy index). Timeframe: 3–6 months; aim to preserve upside while capping downside from sector-wide drawdowns.