Growth is achievable if AI data-center programs stay durable and the company expands content into power, cooling, commissioning, and assurance. The key debate is whether it can capture that value without becoming a price-taker or assuming unpriced service liability.

Jabil’s non-linear upside is becoming a critical-path AI data-center infrastructure integrator (rack + power + liquid cooling + commissioning + assurance), converting scarce “qualified capacity” and power/cooling know-how into higher content per deployment and a modest durability re-rate beyond commodity EMS.

AI compute buildouts raise demand for complex infrastructure builds; Jabil benefits as an industrial-scale enabler, but value capture is constrained by buyer power and competitive EMS dynamics.

Jabil can outgrow traditional EMS by riding AI data-center infrastructure (racks/switches/optics plus power/cooling attach) and by pushing more work into higher-complexity, higher-switching-friction programs. The key is shifting from build-to-print toward “critical-path delivery” (commissioning, power management, and verification/provenance for regulated + hyperscaler builds), which improves mix stability and supports a modest valuation premium versus commodity contract manufacturing. Constraints (factory retrofits for liquid cooling, plus industry-wide power availability) keep growth fast but not explosive; the upside is mainly better content per deployment, steadier utilization, and more recurring services rather than pure volume expansion.

The central risk is that AI infrastructure demand is volatile while Jabil’s value capture remains structurally constrained by competitive bidding and customer bargaining power. Execution risks (liquid-cooling capacity retrofits, working-capital control during fast ramps, and Hanley integration) can quickly turn growth into margin/FCF disappointment. Externally, data-center power availability and permitting friction can delay deployments, pushing out revenue conversion even if end-demand remains intact.

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