How Are Zebra's Earnings Shaping AI Trends?

Zebra Technologies' second-quarter earnings, reported on August 4, offer a glimpse into the next phase of enterprise AI adoption. The company reported record revenue of more than $1.5 billion, up 20.4% year over year, and raised its full-year outlook after strong demand across retail, manufacturing, healthcare, and transportation.

Throughout the earnings call, executives repeatedly linked that demand to customers investing in AI-powered operational technology.

Chief Executive Officer Bill Burns said customers are accelerating efforts to digitize and automate frontline operations, with Zebra's AI portfolio playing a central role.

"Helping customers globally to improve outcomes, to enhance productivity, visibility, and real-time decision-making."

The comments suggest enterprise AI spending is increasingly reaching employees who rarely interact with chatbots or copilots. Rather than generating documents or writing code, frontline workers are using AI to scan inventory, identify products, inspect goods, manage deliveries, and improve operational visibility.

AI is becoming part of enterprise hardware

Burns highlighted Zebra's latest portfolio of enterprise mobile computers and wearable devices that combine RFID functionality with AI-optimized processing. He said customers are showing strong interest in the company's Frontline AI Suite and pointed to transportation and logistics as an area where AI-enabled mobile computers are gaining traction.

According to Burns, integrating RFID and AI capabilities into enterprise devices is "clearly giving us a competitive advantage in the market."

While Zebra's transportation and logistics business remained flat against a strong prior-year comparison, Burns said the company has built a multi-year pipeline of large deployments beginning in 2027. Those projects focus on last-mile delivery and improving parcel visibility across logistics networks, areas where AI-enabled devices can automate decisions closer to where work is performed.

Frontline AI is expanding across industries

Retail, manufacturing, and healthcare all posted double-digit growth during the quarter, with healthcare emerging as Zebra's fastest-growing end market.

Burns said hospitals are equipping more caregivers with enterprise-grade mobile computing devices to improve staff communication and patient safety.

Manufacturing also remained strong, supported by demand for machine vision systems and greater operational visibility. Burns cited AI-powered optical character recognition as one example, noting that it is being deployed across manufacturing, logistics, and food and beverage operations.

These deployments differ from the enterprise AI implementations that have dominated headlines over the past two years. Instead of helping office workers draft emails or summarize meetings, AI is increasingly being embedded into physical operations where speed, accuracy, and visibility directly affect productivity.

Zebra also believes the market remains in its early stages. Burns cited third-party research showing that nearly three-quarters of warehouses worldwide are still in the early phases of automation, leaving significant room for further investment in AI-enabled operational technology.

AI demand is reshaping hardware spending

The earnings call also highlighted a trend receiving far less attention than cloud infrastructure investments: AI-enabled enterprise hardware is beginning to influence semiconductor supply chains.

Chief Financial Officer Nathan Winters said Zebra exceeded its revenue guidance partly because it secured more memory supply than expected during the quarter. However, executives noted that customer demand continues to outpace available supply.

Burns reiterated that demand had previously been constrained by memory availability, saying customer demand "was being gated by memory constraints."

Winters said Zebra expects only modest improvement in memory availability during the second half of the year and is working with suppliers on an 18-month planning horizon. The company is also qualifying additional suppliers and expects to have five to seven qualified vendors for each of its primary memory categories.

The discussion contrasts with the industry's broader focus on GPUs and AI accelerators used to train foundation models. Zebra's constraint is not access to AI chips but securing sufficient memory components for the devices bringing AI into warehouses, hospitals, factories, and retail environments.

The company also continued to see strong customer demand despite rising component costs. Zebra fully offset a $20 million increase in memory costs during the quarter through pricing actions. Winters said the company's expected pricing recovery for the year has increased from $60 million to approximately $90 million.

Enterprise AI is becoming operational infrastructure

Executives consistently described multi-year deployment pipelines rather than pilot projects, with major transportation and logistics implementations expected to begin in 2027.

The company also raised its full-year outlook. Zebra now expects revenue growth of 14% to 16% for 2026, three percentage points higher at the midpoint than its previous guidance. It also increased its non-GAAP earnings per share forecast to between $20.75 and $21.25 while maintaining an expectation of at least $1 billion in free cash flow.

Taken together, Zebra's results suggest enterprise AI is entering a broader phase of adoption.

Cloud infrastructure and AI software remain central to enterprise investment, but companies are increasingly extending AI into the physical environments where products are manufactured, inventories are managed, patients are treated, and deliveries are completed.

Unlike the first wave of enterprise AI, which largely focused on knowledge workers and productivity software, this phase is centered on operational infrastructure. The value proposition is less about generating content and more about improving visibility, automation, and decision-making where physical work happens. If Zebra's results are any indication, enterprise AI is steadily moving from office desktops to factory floors, warehouse aisles, hospital wards, and delivery networks.

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