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  • APH’s Order Book Hit $10.7B. Q3 Earnings Are Oct. 28.
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APH’s Order Book Hit $10.7B. Q3 Earnings Are Oct. 28.

A 2-for-1 split, a 1.23 book-to-bill, and IT datacom growing 63% organically keep Amphenol at the center of AI infrastructure ahead of its Q3 report.
Editor September 14, 2026 3 minutes read
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Amphenol’s 2-for-1 stock split was distributed on September 2, 2026, and shares began trading on a split-adjusted basis on September 3. The split adjusted the optics, not the fundamentals traders should care about most: the order book. Orders reached a record $10.7 billion in Q2 2026, with a book-to-bill ratio of 1.23:1, reflecting robust demand across all end markets. That ratio means for every dollar of product shipped, Amphenol collected $1.23 in new orders. Backlog at that level, sustained for two consecutive quarters, is not noise.

The IT datacom segment represented 43% of sales in Q2 2026, growing 89% year over year and 63% organically. AI-related products drove virtually all of the 22% sequential growth, underscoring the increasing role of AI applications in Amphenol’s interconnect business. That kind of sequential acceleration inside an already-large segment is the number management cannot manufacture; hyperscalers either need connectors or they do not.

Amphenol reported Q2 2026 net sales of $8,758.1 million, up 55% year over year, with GAAP diluted EPS of $1.37 and Adjusted Diluted EPS of $1.35. Both sales and adjusted earnings exceeded the high end of management’s prior guidance. The connector manufacturer reported adjusted earnings per share of $1.35, beating analysts’ estimates of $1.16, while revenue climbed to $8.76 billion from $5.65 billion a year earlier, ahead of the consensus estimate of $8.19 billion.

The Q3 guidance issued July 29 is the number that matters most heading into the Q3 report. The company forecast adjusted EPS of $1.40 to $1.42 on revenue of $9.3 billion to $9.4 billion, above analysts’ expectations of $1.28 per share and $8.77 billion in revenue. Third-quarter IT datacom sales are expected to increase in the mid-teens sequentially, providing a near-term indicator of continued AI-driven demand.

The CommScope acquisition is no longer a drag on the story. Amphenol raised its outlook for the recently acquired CommScope connectivity and cable solutions business, now expecting the acquisition to contribute $4.6 billion in 2026 sales and add $0.30 to adjusted diluted EPS, up from prior expectations of $4.1 billion in sales and $0.15 in EPS accretion. CommScope is making strong progress in AI-related applications, with their IT datacom business essentially doubling year over year. This growth is in advanced optical interconnect solutions.

Amphenol’s portfolio spans high-speed, power and fiber-optic technologies for data centers, including interconnect systems supporting bandwidth of up to 1.6 terabits per second. CEO Adam Norwitt pushed back on the copper-versus-fiber framing on the Q2 call, arguing customers need “more of everything: more high-speed copper, more fiber optic solutions, and more power solutions,” with Amphenol holding a strong and scaled position in all three areas. That breadth is the structural advantage competitors including TE Connectivity cannot fully replicate today.

The split adjusted the optics, not the fundamentals. APH continues to show robust growth, with a 22.5% year-to-date increase and strong demand for its products, particularly in AI-driven sectors. Operating income reached $2.58 billion, a 29.5% margin, up from $1.42 billion in Q2 2025, reflecting strong leverage and cost control. At a 29.8% adjusted operating margin on $8.8 billion in revenue, Amphenol is not sacrificing profitability to chase volume.

The next earnings date is October 28, 2026. IT datacom is expected to see a mid-teens sequential sales increase, while communications networks sales are projected to decline in the mid-teens. Traders watching for a Q3 beat need to track whether AI datacom offsets that communications drag. If it does, guidance for Q4 will carry more weight than the Q3 number itself.

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