How to Deploy AI in Field Service

This week, I continued my conversation with Prateek Chakravarty, CEO at Zinier, exploring the practical reality of deploying AI in field service operations. We discussed how Zinier's forward deployment engineers work with customers from initial MVP through full-scale autonomous operations.

The Collaborative Journey: From MVP to Autonomous Operations

Q: Walk me through what a forward deployment engineer actually does in week one versus month six at a customer.

Prateek: It's important to understand how we deploy in general - our value release methodology. We break it up into smaller chunks.

We've morphed agile methodologies for the core physical industries we serve because they're not set up to do agile. The DNA is not there. The way of operating is different. So we've morphed it into what we call value release methodologies. We still go up front, we still do what we call a high-level design to come up with the overarching plan, but then we break it up into value releases. We do an MVP first, then follow it up with more value releases.

Forward deployment engineers are key in our system. Starting off, they get the handover from the sales team. They sit down with the customer. They run the discovery workshop. They map out the workflows that are needed, which ends up in that overall high-level design of the journey or roadmap.

This gets translated by the tech team into the detailed delivery plan. Forward deployment engineers stay involved. They understand how the solution is being built as future value releases are determined. They play a hands-on role in the ROI aspect - any phase that goes live, spending time after UAT, after go-live with the customer, making sure they're shadowing the personas to understand usage and get feedback. What's working? What's not working? How is that brought into the system for future value releases or enhancements? Making sure the ROI is being delivered.

It's a full-cycle job where you are the custodian to ensure that this is implemented correctly and the value is being realized.

Physical industries aren't built for standard agile. Forward deployment engineers are full-cycle custodians ensuring correct implementation and ROI realization through value releases.

AI Readiness: The Mindset Shift Beyond Technology

Q: If a field service company wants to be AI-ready in 2025, what should they prioritize today?

Prateek: Being open for change. That's number one. Continuing to be obsessed about solving the problem and not getting enamored with technology. The good part is they don't need to worry about the technology with the advent of LLMs - that's the least of their concerns.

Continue to be obsessed with the problem to be solved. Think differently beyond standard IT processes. It has to be different. It has to be implemented differently. It has to be rolled out differently. It has to be collaborative. Find the right partner where you can collaborate and work on it.

Stay very focused. Don't go crazy. Don't do pilots just for the sake of doing pilots and checking the box. Be very methodical, be very prescriptive about why and what problem is being solved here, and then go about solving the problem.

The way we approach this is more of a consultative engagement where we work with you, we define and try to identify the use cases, then go after them together. Set it up correctly, make sure the ROI is coming. Don't just treat it as buying another software product. And that's where most things fail. Either you're checking the box to do a pilot to meet certain objectives, or you're just treating it as buying a standard product and expecting it to work straight out of the box like SaaS would.

It's a mindset shift. It is a different way of doing business. It is going to solve your problems quicker and in a more cost-effective way. But you need to have that nuance on how you want to go about it.

AI readiness isn't about technology - it's about being obsessed with solving problems, not checking pilot boxes. It requires collaborative implementation and a complete mindset shift.

Bottom Line

Success in field service requires embedded domain experts who understand that physical industries operate differently than traditional tech companies. They need value release approaches that adapt agile to their reality, not force them to become software companies overnight.

The winners will be those who work collaboratively with partners who understand that implementation is where the real work begins - not where it ends.

Want to learn more about Zinier's value release methodology? Schedule a demo to see how our forward deployment approach can accelerate your AI journey.