4 Takeaways from the inService Podcast with Circuitry.ai

AI is moving from experimentation into everyday service operations. But as adoption grows, service leaders face a harder question: Where can AI make the greatest difference, and how should that value be measured?

That question shaped the episode “Shifting the Focus from AI to Decision Intelligence” of Service Council’s inService Podcast, hosted by Gerardo Pelayo, Chief Research Officer at Service Council, and Edward Krzysik, Vice President of Customer Success and Value at Circuitry.ai.

Together, they explored why service organizations need to move beyond broad AI initiatives and focus on the decisions that directly affect technicians, customers, and business performance.

Check out the podcast on demand.

Here are our four takeaways for service leaders who want to improve service outcomes.

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1. Treat service, parts, and warranty as one activity

Customers experience a service event as one interaction. Internally, that event may cross several teams and systems.

A technician may diagnose the problem, determine the correct repair, identify a replacement part, document the work, and initiate the warranty process. Each decision depends on the one before it.

Edward expands on what that looks like. Decision Intelligence could provide the technician with the asset and service history needed to diagnose the problem, anticipate whether a replacement part is likely, identify the appropriate part, verify availability, and initiate the relevant warranty process.

"Instead of managing this as three different functions: service, parts, and warranty, it becomes one service activity that is driving customer value. Because you're impacting downtime, it's providing the right financial efficiencies internally, because you're spending less time onsite, you're probably going to decrease truck rolls by a significant portion as well. And you're going to make sure that you don't leave any money on the table by not following the adjudication process on the warranty side. There is great value in that."

Circuitry.ai connects these decisions through a purpose-built Service Decision Intelligence layer that supports the decisions made before and during the visit: what service is required, what fix will resolve the issue, and what part will complete the job.

2. Align KPIs and visibility across functions

Service, parts, and warranty processes may be working toward different metrics. Service teams measure first-time fix. Parts teams track availability. Warranty teams monitor productivity, compliance, and financial performance.

Those metrics aren’t independent. A technician can’t achieve a first-time fix without the right part. A warranty team can’t process the repair correctly without accurate service and parts information. Yet organizations may not consistently measure those relationships.

As an example, Gerardo noted a Service Council finding that close to 40% of supply chain leaders weren’t actively tracking the impact of service parts on first-time fix.

Edward used the relationship between first-time fix and parts availability as an example:

"If you follow that path, whereby reducing the time on site or improving the first-time fix rate and ensuring that you have the right parts, those two are tied together, right? Because a first-time fix could have a dependency on ‘I don't have the right part’. But if you have that predictive model that says you 100% have the right part because you've checked it prior to, that's going to improve both of those KPIs."

Circuitry.ai Service Decision Intelligence works as a decision layer across the CRM, ERP, FSM, DMS, warranty, parts, and knowledge systems organizations already run. Service Decision Intelligence makes the existing information and workflows more intelligent by reading context, applying AI reasoning, generating recommendations or decisions, automating approved workflows, and writing results back into existing systems.

3. Turn data volume into decision value

Service organizations usually don’t lack data. Their challenge is that service histories, technician expertise, parts information, customer records, and warranty details are scattered across disconnected systems and often remain underused.

Edward describes this as a “density” problem: how much useful intelligence an organization can produce from the data it already has. By bringing that information together and delivering the right insight at the moment of impact, Decision Intelligence can help technicians make better decisions while creating value from information that previously sat unused.

That value extends beyond individual service calls. Better use of install base and service data can support technician development, product uptime, early renewals, expansion opportunities, and a stronger customer experience.

For Edward, applying Decision Intelligence can help move field service from a perceived cost center toward a revenue-generating and profit-supporting function.

“I absolutely believe that these are revenue-generating centers to me. I think field service, if applying the principles of Decision Intelligence, it becomes a revenue center, a profit center, and continues to be.”

4. Make adoption part of the ROI strategy

AI value depends on more than technical implementation. Organizations need clear baseline metrics, realistic targets, workflow integration, executive support, and employee adoption.

Edward placed strategic alignment and organizational culture at the beginning of the implementation process:

"To me, it's all about that initial strategic alignment. Discovery is the key aspect of our business model. I think understanding a few elements of a customer's business, like what's driving the current decisions today, what are the baseline metrics, and the first-time fix rate? Those types of things, and being able to share examples of where we've implemented our solution, and they've gotten the benefits that were expected."

Circuitry.ai’s TRACK Framework puts that approach into practice. It helps service leaders identify the right journey, understand the current process, assign the right AI Workers, measure value, and continuously improve adoption.

Explore the TRACK Framework for Autonomous Service Journeys.

Better service decisions create better business outcomes

Service Decision Intelligence moves AI from answers to governed decisions and actions.

Circuitry.ai helps manufacturers and service organizations improve the decisions that drive uptime, cost, service margins, and customer loyalty using domain-deep intelligence, governed autonomy, and measurable ROI.

Circuitry.ai turns service knowledge, warranty history, parts data, policies, contracts, and repair outcomes into ready-to-deploy AI workers. Our Service Decision Intelligence platform recommends, scores, and automates the decisions from diagnosis and parts identification to warranty review, service contract claims, dealer support, and customer updates.

Ready to explore what Service Decision Intelligence can do for your organization? Schedule your personalized demo.