Artificial intelligence is rapidly entering the insurance claims process.

AI systems can review photos, estimate damage, check policy language, and collect claim data faster than ever before. Many insurtech companies are now building automated First Notice of Loss (FNOL) systems and AI claim assistants.

But there is a growing question inside the industry:

Are we automating the easy parts while overlooking the most important human skills?

Experienced adjusters develop abilities that are rarely written into manuals or software specifications.

These skills are learned through thousands of conversations with policyholders during some of the most stressful moments of their lives.

Many of these abilities are difficult to translate into code.

Listening Before Investigating

One of the first lessons new adjusters learn is that sometimes the insured simply needs to tell their story.

A caller who has just experienced a fire, tornado, or major loss may be overwhelmed. They may repeat details or speak at length before answering direct questions.

An experienced adjuster often allows the insured to talk for a moment.

This serves two purposes:

• The insured feels heard.

• The adjuster begins forming a mental picture of the loss.

An AI system designed only to collect structured data may interrupt or redirect the conversation too quickly.

Reading Emotional Cues

Claims conversations contain emotional signals that experienced adjusters recognize immediately.

A change in tone.
A pause before answering a question.
Frustration or anxiety in the caller’s voice.

These cues often tell the adjuster more than the words themselves.

They may indicate:

• confusion about coverage

• fear about the claim outcome

• stress from displacement or financial pressure

Human adjusters instinctively adjust their tone and pace in response.

Adapting Communication Style

No two insureds communicate the same way.

Some people want concise answers.

Others want a detailed explanation of every step of the process.

Adjusters frequently hear things like:

• “You’re talking too fast.”

• “Can you speak a little louder?”

• “Let me explain what happened first.”

Adjusters learn to adjust their cadence, tone, and pacing to match the individual they are speaking with.

This flexibility helps build trust and keeps the conversation productive.

Recognizing When Something Doesn’t Add Up

Another skill adjusters develop over time is recognizing inconsistencies in a story.

It may be something small:

• the timeline of events

• the description of damage

• conflicting statements during the conversation

Experienced adjusters often sense when additional questions are needed.

This instinct is built from years of pattern recognition and real-world experience.

Knowing When to Pause

Silence can be an important part of a claims conversation.

Sometimes the most effective response from an adjuster is simply to pause and listen.

The insured may provide additional information that would not have surfaced through direct questioning.

AI systems built around continuous questioning may overlook this dynamic entirely.

The Future Role of AI

Artificial intelligence will undoubtedly improve many aspects of claims handling.

AI can analyze large datasets, identify patterns, and assist adjusters with technical evaluations.

But claims handling has always involved more than processing information.

It involves people navigating stressful situations.

The most effective claims systems in the future will likely combine:

• the speed and analytical ability of AI

• the judgment and communication skills of experienced adjusters

Automation may transform claims handling.

But the human skills developed by adjusters over decades should not be viewed as obstacles to automation.

They should be seen as design requirements for the next generation of claims technology.