How Physical AI Will Make The Network Part Of The Machine

Venkatesh Gokulraju, technical director of forward deployed-engineering at Lancesoft, specializes in AI-driven network automation.

​Picture what a regional airfield could look like around 2030.

An autonomous baggage tractor loses satellite navigation to interference, yet keeps working. The cellular network carries its commands, helps track its position, detects a drone near the apron and provides a trusted clock. When the tractor moves beyond terrestrial coverage, a satellite keeps its remote supervisor connected, and the machine shifts into a more cautious mode.​

In my work leading telecom product development and forward-deployed engineering across 5G, non-terrestrial networks (NTNs), network automation and service assurance, I work at the boundary between lab design and field reality.

The building blocks for this scenario—edge inference, network sensing, closed-loop automation, satellite connectivity and resilient timing—already exist or are moving through standards and product road maps.

Together, these capabilities point to one of the biggest telecom redesigns since 5G: networks that stop only carrying data for machines and increasingly participate in how those machines sense, decide and act.​

But challenges remain for bringing this vision to life, many of which are organizational, as operations and security teams must increasingly engineer the robotics, network and cloud capabilities as one system.​

How Physical AI Breaks The Old Scorecard

Factories are on track to install more than 700,000 industrial robots a year by 2028, according to the International Federation of Robotics, and mobile machines are spreading from factory floors to yards, ports and airfields.

Unlike generative AI, which answers on a screen, physical AI runs a continuous loop of sensing, computing and acting through a real body.

To meet the demands of this shift, here is how I expect infrastructure to change over the next five years, with much of the technology already available: