Field service leaders are under enormous pressure. Teams are shrinking, products are growing more complex, and customers expect fast, flawless fixes every time. AI has been held up as a silver bullet, but despite the hype, most organizations aren’t seeing real impact.
Why? Because AI only works as well as the knowledge it’s fed. And right now, the most valuable knowledge—what experienced technicians know and do in the field—is walking out the door faster than it’s being captured.
The real barrier to AI in field service isn’t technology, it’s knowledge. When tribal know-how disappears through retirements, turnover, or outdated systems, the costs ripple across the business. The results are slower onboarding, more repeat visits, rising support costs, and ultimately, disappointed customers.
That’s where the real cost of doing nothing comes in. Many leaders think waiting is the safer choice. Delay the investment, push the decision to next quarter, wait to see if AI “gets better.”
But the truth is, waiting isn’t neutral.
Doing nothing is often the most expensive decision you can make.
Why “Doing Nothing” Costs More Than You Think
One field service leader put it plainly: “Every quarter we delay capturing tribal knowledge, we pay twice—once in lost productivity and again when another veteran tech walks out the door.”
The math backs them up. Repeat visits alone can cost an organization $2.4 million annually.
Add in knowledge loss from retiring SMEs, the time and expense of producing documentation manually, and the revenue left on the table when customers churn, and the totals are staggering.
Calculating the Price of Inaction
To make the impact of inaction more tangible, take a look at the Cost of Doing Nothing (CoDN) formula.
On its own, the formula is simple: multiply the volume of jobs by the cost impact and the rate of inefficiency. Even with conservative inputs, the math adds up fast. Factor in knowledge loss from retiring experts, content creation inefficiencies, and churn, and the totals easily reach millions more.
But the CoDN formula is only the starting point.
The categories below show just how many ways inaction chips away at performance. Each item represents a different category of hidden loss. Each can be quantified with its own formula and together they reveal the full picture.
The formula gives leaders a quick way to put hard numbers around the problem; the list unpacks the complexity, showing how those costs spread across the entire service operation.
Taken together, they send a clear message: every quarter you delay capturing knowledge, the bill for doing nothing gets bigger.
Ways Inaction Can Impact Your Bottom Line
Extended Resolution Times
Cost of Doing Nothing:
Troubleshooting & resolution takes longer due to lack of readily accessible expertise.
How to Quantify:
(Average time per job × labor cost per hour × jobs/year) – target reduction
Repeat Visits / First-Time Fix (FTF)
Cost of Doing Nothing:
Incomplete knowledge sharing leads to repeat dispatches. Industry leaders cite FTF as the #1 cost/ productivity KPI.
How to Quantify:
(Repeat visit rate × total jobs/year × cost per truck roll)
Knowledge Loss / Attrition
Cost of Doing Nothing:
Retiring experts take undocumented know-how with them. US companies lose $31.5B annually to this issue.
How to Quantify:
Estimate % of expert workforce attrition × cost to replace + retrain × lost productivity window
High Knowledge Creation Costs
Cost of Doing Nothing:
Manual creation of documentation & tutorials is slow and resource-intensive.
How to Quantify:
(Hours to produce content × hourly rate × content volume/year) – AI-assisted time reduction
Onboarding & Ramp Time
Cost of Doing Nothing:
New hires take longer to become productive without guided, contextual, multimodal knowledge.
How to Quantify:
(Onboarding duration × cost per new hire × hires/year) – target ramp reduction
Missed Self Service Deflection
Cost of Doing Nothing:
Tribal knowledge is the norm. Service Council™ reports that “calling a colleague” is the #1 source of knowledge when facing a complex situation.
How to Quantify:
(Deflectable case volume × cost per case) – expected deflection rate
Customer Churn Risk
Cost of Doing Nothing:
Slower resolutions + inconsistent quality erode satisfaction, impacting renewal and upsell revenue.
How to Quantify:
(Churn % due to service issues × revenue at risk)
A Graveyard of Knowledge
One VP of Service at a global telecom captured the frustration well: “We realized our knowledge base wasn’t a library—it was a graveyard. Static PDFs couldn’t keep up with the pace of the field.”
This is the reality for many service organizations. Legacy systems were designed for documents, not the dynamic, in-the-moment content that modern AI and frontline teams need.
They don’t capture the quick fix a technician invents on site. They miss the subtle audio cue of a failing component. They never record the workaround for an outdated part.
Without that context, AI can’t connect the dots. Technicians can’t find the guidance they need. And customers don’t get the fast, reliable service they expect.
Breaking the Cycle
The only way out is to rethink how knowledge is captured. Instead of relying on a handful of SMEs to document fixes weeks after the fact, service organizations need tools that capture expertise automatically, in the flow of work.
When knowledge is preserved in real time—whether through video, annotations, or live troubleshooting—it doesn’t just speed up onboarding or reduce repeat visits. It feeds AI systems with the structured, contextual data they’ve been missing, making both people and technology more effective.
The cost of inaction is measurable, growing, and unsustainable. The leaders who act now will not only stop the losses, they’ll build a service organization that gets smarter with every call.
In field service, the hidden costs of inaction are real. Every missed opportunity to capture frontline expertise erodes productivity, service quality, and customer trust.
Today, the question isn’t whether you can afford to invest in knowledge capture, it’s how much longer you can afford not to.
