Scaling the Enterprise Field Workforce

I’ve always had the same view on what contributes to the biggest failures in traditional field service implementation. It’s forcing very unique organizations to fit their real-world workflows into what is now legacy and rigid software.

You connect to different systems than your competitors, you organize your field teams differently. Your field workflows and your processes differ.

The same is also true for AI agents. There’s a difference between bolting on AI to a legacy system and redesigning a process from the ground up for AI.

In this whitepaper, we took the latest research from the Verdantix Global Corporate Survey: Industrial Transformation Budgets, Priorities And Tech Preferences and turned it into a benchmark you can use to assess how you measure up against your industry peers.

Verdantix interviewed 333 decision-makers across 22 industries and 16 countries and regions.

They asked 2 questions that we were most interested in: 

“How are you using or plan to use field service management software to boost productivity, safety and efficiency of your field technicians?”

“In 2026, to what extent will your firm apply AI agents to the following activities?”

In the whitepaper you’ll get:

• Three signals from the 2026 research on FSM implementation and AI agent use
• Six capabilities that are required for scale
• What scaled FSM looks like in practice (using a Zinier customer as an example)
• The groundwork that decides what AI can do
• A benchmark you can use to score how ready your operating model is for growth

Download the whitepaper and find out where you score on the maturity model

‍

Andrew Wolf

Co-founder / Chief Product Officer

Zinier

‍