As field service teams face growing pressure to do more with less, AI is stepping in to transform the way they operate. In the latest episode of Service Council’s InService podcast series, Gerardo Pelayo sat down with Ashok Kartham, Circuitry.ai’s Founder and CEO to discuss how businesses can use AI to drive value and a better customer experience.
Here are our key takeaways from the episode. You can watch the full episode on Spotify, Apple podcasts, or YouTube.
For Ashok, successful AI implementation has three main factors: identifying the right use cases, managing the organizational shift, and applying AI with focus.
First, choosing the right use cases is essential. As a service leader, this means focusing on the use cases that directly impact metrics you want to improve, such as reducing overtime, increasing first-time fix rates, and minimizing equipment downtime. Targeting these areas ensures AI delivers real business value.
Next, managing the organizational shift is critical. AI implementation isn’t just a technological change—it’s also a human and process-driven one. Actively guiding your employees, aligning AI with business goals, and being ready to adjust will make the impact of AI even more effective.
Finally, Ashok believes that AI works best when applied with focus rather than trying to use it broadly across every function. It’s also critical to carefully select the industry vertical, targeting areas where AI can truly make an impact. Companies that take the time to match AI to specific business needs are the ones that see the most success.
It’s natural for people to feel defensive when new technology disrupts their routine. AI-powered field service technology is no different—some people see it as a threat to jobs, while others think it’s too simplistic to handle complex tasks. However, Ashok asserts that it’s important for companies to be clear that AI isn’t here to replace jobs; it’s a tool to assist with tasks, including complex ones. “AI is an enabling tool that augments the workforce, not replacing it.”
Using new technology can feel intimidating, but Service AIdvisor is simple, conversational, and designed to reduce—not add to—your team’s workload. There’s no need for complex navigation or forms—technicians just interact with the AI just like they’d talk to a coworker. And it doesn’t rely heavily on Wi-Fi or require downloads, meaning it’s accessible even in low-connectivity areas through familiar platforms like WhatsApp or Microsoft Teams.
Engineers have expressed a growing need for AI-powered tools to help them troubleshoot, as shown in the Service Council’s Voice of the Field Service Engineer (VoFSE) survey. The challenge they face is that finding the right information is often time-consuming.
AI changes that by providing precise and accurate answers based on the product and the specific situation, allowing engineers to troubleshoot more effectively and improve first-time fix rates. As Ashok explained, “AI is making it much easier for technicians to access to this knowledge, which was much harder to find before.”
There’s more data than ever, but it's scattered across many sources. AI helps solve this by pulling information from these diverse sources and delivering an answer that’s easy for technicians to understand and use. This efficiency is crucial given the challenges technicians face with long hours and heavy workloads.
Based on the VoFSE survey, 59% of technicians work beyond 40 hours a week, and 1 in 5 expressed dissatisfaction with their work hours. AI can address these concerns in a few ways. New technicians can onboard faster with immediate access to knowledge. For current employees, AI helps them work more efficiently by providing summarized and instant access to job history.
One of the concerns surrounding AI in field service is whether it will make the customer experience feel less human and more transactional.
However, Ashok emphasized that customers care most about product uptime and how quickly their problems are resolved. “Customers care about their product uptime and the time it takes to resolve the problem they have,” he explained. AI can improve both by providing faster, more accurate solutions to technicians, resulting in quicker resolutions and decreased downtime.
Another key factor is how knowledgeable your team appears to customers. Customers' perceptions of the expertise of the person assisting them play a big role in shaping their experience. With AI, technicians have instant access to the information they need, making them more confident and capable of resolving issues.
When you prioritize key metrics like uptime and resolution time, the customer experience naturally improves with faster, more accurate service—without feeling like their issue is simply being handed off to AI.
One of modern AI's strengths is its ability to process and learn from multiple types of data, making it invaluable for industries that rely on more than just text-based information. Even if your data is scattered across different formats or applications, AI can help bring it all together.
We’ve trained Service AIdvisor to understand videos, schematics, and even MP4 files. This is particularly useful for technicians who often work with products that have intricate components. For example, more products have electronic computers or software components, and technicians rely on wiring diagrams to diagnose and fix issues. These data formats aren’t easy for LLMs to understand, so one of our goals was to teach our AI to understand these diagrams and answer questions based on them.
Ashok closed the conversation by reminding organizations that data quality is important, you don’t need to wait until you have perfect data. You can start with the data you have and build as you go. If you’re using our solution, you can also use our Expert Answers features to incorporate tribal knowledge from your expert staff into the AI.
Check out Gerardo and Ashok’s episode, AI to Drive Value & Experience, with Ashok Kartham, Founder & CEO at Circuitry.ai.
Will efforts by service leaders to build momentum with AI superseded and become obsolete as a result of efforts by IT leaders who are thinking about AI in a more systemic deployment methodology?
As I mentioned before, IT may look at AI as a generic solution. And because it’s a new technology and there are some concerns about governance, they may want to control it, but where we see the value is how business people can start using it and benefitting from AI within their specific applications, like what we are talking about in field service and contact center resolution areas.
Part of our model offering as an enterprise AI as a service is to eliminate a lot of the effort by the technical teams, data engineers, data scientists, and others that have to do the work. So you can have a solution that can activated, in some cases, within even hours or days to get to the fast time to value.
Also a lot of times, instead of focusing on the technology, if the business users can focus on what is the knowledge that can be made available for the fields service side, then they can approach this as a business solution rather than a technology solution.
Obviously, there needs to be coordination with the IT leaders on why this is being deployed and that there are the right governance and security mechanisms in place. We don’t see as much as friction between business leaders and IT anymore. I think IT recognizes that for these vertical applications it’s better to have it as a packaged application. And I think all the work done by SaaS and cloud vendors before, where the benefit was that most applications, instead of being built internally, moved to the cloud—we’re seeing the same thing now with the enterprise AI-as-a-service model.
Circuitry.ai’s Service Advisor reduces the time technicians spend looking for information by drawing on the company’s knowledge and data to provide instant answers to technical questions. Whether troubleshooting an issue or finding the right part, Service AIdvisor helps technicians get answers fast, allowing them to focus on delivering effective service.
Circuity.ai Enterprise AI as a Service model provides a cost-effective subscription pricing with a faster time to value, enabling you to realize value and ROI in days.
Is your team ready for the next step in AI-driven field service? Schedule a personalized demo today and see how Service AIdvisor can help you improve technician productivity, increase equipment uptime, reduce overtime, and more with a 30-day proof of value.