The staggering momentum in AI infrastructure build is driving test, measurement, and assurance demands across three key areas
AI is a dominant force shaping economies around the world. It is sweeping through industries, transforming businesses, changing consumer behavior, and fueling massive demand for infrastructure.
According to IDC, the infrastructure spending to support AI’s rapid growth and adoption is on track to hit a whopping $758 billion USD by 2029. That’s massive, even by investors’ standards.
“The velocity at which all of this is moving is pretty stunning, even by my own estimation,” Marc Ganzi, CEO of DigitalBridge, an investment firm in the digital infrastructure space recently acquired by SoftBank, noted at the Metro Connect keynote. “I’ve been accused of being a bit of a cheerleader for the industry, but it really has even caught us by surprise: the enormity and the complexities of what we’re building.”
That staggering momentum marks a watershed moment for the test and measurement industry. Specifically, it’s driving test and measurement needs in three core areas.
The fiber infrastructure
Despite advancements in high-capacity fiber optics, single-mode fiber (SMF) remains the most versatile medium of connectivity, thanks to its fast data transmission speeds and low power consumption.
With fiber deployment topping over 88.1M homes in the U.S., and expanding progressively to support data center connectivity, the global fiber infrastructure is set to become the backbone of communication for AI/ML, IoT, quantum, and 6G technologies.
Fiber monitoring and management is vital to keep this colossal infrastructure pumping. Fiber monitoring entails physical inspection, fault detection, performance analysis, real-time threat detection, and integrated and remote monitoring.
Testing focuses on ensuring the physical integrity of the cables, a must, given their inherently fragile nature. Continuous testing also ensures correct polarity, reduces optical loss and attenuation, and extends the lifespace of the fibers.
It begins at production where all components — fiber, connectors, splices, laser sources, detectors, and receivers — are checked for build quality and compatibility. Post-installation, the cables are tested for polarity and insertion loss. Specialized tests like Optical Time Domain Reflectometer or OTDR are carried out to ensure individual splices are good. And once the network is lit, on-demand tests and automated monitoring are carried out remotely to ensure optimal performance.
Service assurance
Traditional methods of network management are redundant in the era of AI and edge inference. The new networks demand proactive assurance delivered through closed loop automation.
The demand is causing service assurance to evolve from reactive to proactive. Use of AI and digital twins are filling up the gaps in previous methods making assurance predictive.
What used to be a tedious process of capturing and analyzing data byte by byte is now a seamless DevOps cycle of integrated service activation, monitoring, and rapid automated root cause analysis and troubleshooting. As issues are detected, sources are identified, and operators are alerted in a seamless loop of proactive identification and resolution.
The service often relies on deploying active test agents across the network to get a real-time view of domains and their individual performance and health, and analyzing that data with AI engines.
This new kind of service assurance is equipped to meet the demands of cutting-edge AI workloads and keeps networks efficient and reliable from edge to core.
Semiconductors
The AI economy is dominated by chips. According to the Semiconductor Industry Association, global semiconductor sales totaled roughly $208.4 billion in the third quarter of 2025, soaring 15.8% from the quarter before.
Beneath all that growth, the semiconductor testing industry is experiencing its own boom. According to the Yole Group’s Market Monitor, the semi test equipment market saw strong upward movement in the second-quarter of 2025, growing 13.1% quarter-over-quarter, driven largely by sales in SoC and DRAM-HBM testers.
Testing is critical to ensuring quality and reliability in silicon devices. It evaluates
the health and quality of the devices, revealing physical defects in production and functional bugs later in the pipeline, confirming that each design meets the required specifications and standards.
In the recent years, test and measurement companies including Keysight, Rohde & Schwarz, and Anritsu have all expanded their portfolios to include testing solutions for design and simulation, wafers and dies, functions, parameters, and IP management, attracting investments from hyperscalers, neoscalers, and tech giants that have committed trillions of dollars to chip procurement.
