Synopsis: Zuper CEO Anand Subbaraj explains how artificial intelligence (AI) is being used by field service teams to navigate everything from increased prices caused by higher tariffs on equipment to offloading inventory costs to the companies that ship the equipment directly to the customer.
Field-service teams are being squeezed from every side: tariffs raise parts costs, fuel prices swing and skilled technicians are hard to hire. Anand Subbaraj says the answer isn’t a bigger warehouse—it’s better foresight. By feeding years of job, parts and equipment history into machine-learning models, dispatchers can predict which components a Friday repair will need and have them drop-shipped to the customer’s driveway minutes before the van rolls up. The goal is “just-in-time” inventory, not aisles of stock whose price changes every week.
Price volatility has pushed many firms from time-and-materials billing to flat-rate menus. A model weighs labor, parts and overhead, then recommends a fixed quote customers can accept on the spot—giving both sides a fighting chance against next month’s inflation spike.
Profit tracking now starts upstream, during the job, not weeks later in the ledger. Dashboards show whether a ticket is on course for a 60% margin based on real-time part usage and labor hours; the same view flags technicians, regions or subscription plans that consistently lose money. Technicians, once a “cost center,” are recast as brand ambassadors who can upsell maintenance contracts when data says the visit is a good fit.
Subbaraj’s playbook for leaders comes in three parts:
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Embrace agility—experiment fast, fail faster and iterate as prices and models evolve.
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Start with the “why.” Let the customer problem—not shiny tech—drive every AI rollout.
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Prioritize people.
