Introducing Adjuster’s Cockpit and Clive Claim Conductor for No-Touch and Low-Touch Claims
7 min read
Most claims AI makes part of the adjuster’s job faster.
A document gets read faster. An estimate gets reviewed faster. A recommendation gets generated faster.
But then the claim often waits for a person to decide what happens next.
That is the limitation we set out to address with Adjuster’s Cockpit and Clive Claim Conductor, two new Five Sigma capabilities designed to move claims automation beyond individual tasks.
Together, they support a different operating model: AI takes greater responsibility for moving the claim forward within insurer-defined guardrails, while adjusters supervise the operation and step in where their judgment or authority is required.
That distinction is what makes no-touch and low-touch claims handling possible.
From automating claims tasks to progressing the claim by agentic AI
Claims orchestration is the layer that connects AI decisions to AI actions, so a claim keeps moving through its lifecycle without a person authorizing every step.
The next step in claims automation is not simply giving adjusters more AI tools. It is enabling AI to connect decisions and actions so the claim itself keeps moving.
That is the role of Clive Claim Conductor.
Conductor understands where a claim is in its lifecycle, what needs to happen at that stage and the goal that needs to be achieved. When that goal is met, it can advance the claim to the next stage within the insurer’s configured permissions and guardrails.
Adjuster’s Cockpit addresses the other side of the operating model: human oversight.
Instead of opening claims one by one to determine what needs attention, adjusters get a cross-claim view of the automated work they supervise. They can see which claims are progressing, which require human input and which are unable to move forward.
When intervention is required, Cockpit gives the adjuster the context to act, including Clive’s recommendation, confidence and supporting explanation.
Conductor keeps claims moving. Cockpit shows adjusters where they need to step in.
This is the difference between a claims system of record and a system of action, where agents run the workflow rather than logging what a person already did.
No-touch and low-touch claims are part of the same AI operating model
An AI operating model for claims defines which actions AI can execute on its own, which require human approval, and how work passes between the two.
Not every claim should be automated to the same degree.
A straightforward claim may be able to progress from beginning to end within predefined rules without human intervention. That is no-touch claims handling.
A more complex claim may progress automatically through much of its lifecycle but require an adjuster for a coverage decision, exception, approval or other point requiring human judgment. That is low-touch claims handling.
The important change is that human involvement no longer needs to be the default at every step.
Five Sigma allows insurers to determine which actions can execute automatically and which require approval. Automation can be configured by action, sub-organization and line of business, while guardrails prevent AI from executing actions outside those controls.
That means the same operating model can support different levels of automation across different claims, and even at different points within the same claim.
Rather than choosing between “automated” and “human-handled,” insurers can decide where human involvement actually adds value.
This is also why straight-through processing rate understates progress. STP counts only claims completed with zero human touches, which is why the metric stalls near 10% even as automation runs inside far more complex files.
The delay that default human involvement creates is visible to policyholders. J.D. Power found that 22% of customers report high effort on claims settled in under a week, rising to 48% on claims that take 30 days or more. Effort roughly doubles as a claim ages, and Celent’s 2026 analysis found delays in claim handling accounting for 22% of all 2025 claims complaints, the largest single category.
The adjuster becomes the supervisor of an AI-led claims operation
This is where the shift becomes more significant than automation alone.
In a traditional claims workflow, the adjuster is both the expert and the mechanism that keeps the claim moving. Even routine claims frequently depend on someone opening the file, determining the next action, completing it and moving on to the next claim.
In an AI-led operating model, those roles begin to separate.
AI can handle more of the procedural work required to progress claims. The adjuster can focus on the work that calls for judgment, experience and authority.
“What do I need to do next on each of my claims?”
“Which claims need me right now, and why?”
That changes what the adjuster’s day can look like. Rather than manually advancing every claim, claims professionals can oversee a larger portfolio of automated work and concentrate on exceptions, complex decisions and moments where human judgment matters.
As Gil Nechushtai, Chief Product Officer of Five Sigma, explains:
“The real transformation isn’t adding AI to existing claims workflows. It’s redesigning claims operations so AI takes the lead within defined guardrails, while adjusters supervise and step in when human judgment is needed. For insurers, this means applying experienced claims expertise across more claims, while reducing the administrative work required to keep routine claims moving.”
Gil Nechushtai, Chief Product Officer of Five Sigma
For more on how this changes day-to-day work, see where the adjuster’s role moves as claims become agentic.
See the new AI operating model in action.
Guardrails make greater AI autonomy possible in claims
Guardrails are the insurer-defined limits that determine which claims actions AI can execute automatically and which stop for human approval.
Giving AI more responsibility does not mean giving it unrestricted authority.
In fact, greater autonomy requires clearer controls.
Insurers determine where AI is permitted to act automatically and where human approval remains required. When an action falls outside those boundaries, it does not execute automatically. The claim is surfaced for human intervention.
This is what allows insurers to expand automation progressively rather than making an all-or-nothing decision about AI autonomy.
A carrier might begin with automatic execution for a narrow set of predictable actions, for example, and expand the scope as it gains confidence in performance. Another line of business or action can remain low-touch.
The insurer controls the boundary between AI action and human intervention.
Our view on autonomy levels and the guardrails behind each one goes into how those controls are structured in practice.
The last two are where most operations fall down. A claims system that logs the final state of a claim, and not the sequence of decisions that produced it, can tell an examiner what was paid. It can’t tell them why, or who could have stopped it.
Speed of reconstruction is its own compliance property. At Resorts World Las Vegas, document review that consumed a full working day now runs in 37 seconds, and answering a question about any claim takes about 10 seconds against 30 to 45 minutes. A week of file pulls becomes an afternoon.
The market is moving faster than the regulation. The Lloyd’s Market Association surveyed firms representing over 60% of Lloyd’s stamp capacity in April 2026 and found 93% have or are building formal AI governance frameworks, with over 60% mandating human review of AI outputs. In the European carrier RFIs we’ve seen this year, “full traceability and audit trail of every agent decision” now appears as a stated platform requirement alongside data residency.
Moving toward Automation First claims operations
Automation First is Five Sigma’s product vision: a staged path from AI that assists adjusters toward AI that manages claims, with people moving into oversight.
Adjuster’s Cockpit and Clive Claim Conductor represent the third stage of that vision.
The direction is from AI that primarily assists people toward AI that takes greater responsibility for progressing the claim, with humans moving into an oversight role.
The objective is not to remove people from claims. It is to stop requiring people to be the mechanism that moves every claim through every step.
That creates a path toward no-touch handling where the claim allows it, low-touch handling where human involvement is needed, and deeper human attention for the claims where expertise matters most.
Five Sigma will show Adjuster’s Cockpit and Clive Claim Conductor at ITC Vegas 2026, September 29 to October 1, at Booth 3244.
Key takeaways
- Clive Claim Conductor advances a claim through its lifecycle stages within the insurer’s permissions, so progress no longer depends on a person opening the file.
- Adjuster’s Cockpit gives adjusters a cross-claim view of the automated work they supervise, showing which claims are progressing, which need input and which cannot move forward.
- No-touch and low-touch claims handling are settings within one AI operating model, configurable by action, sub-organization and line of business.
- Guardrails are what make greater autonomy workable. Anything outside the defined boundary is surfaced for human intervention rather than executed.
- 70% of auto writers already use AI in claims while only 14% of P&C insurers run straight-through processing. Closing that gap is the point of claims orchestration.
See the new AI operating model running on claims like yours.
Frequently asked questions
What is Clive Claim Conductor?
Clive Claim Conductor is Five Sigma’s claims orchestration capability. It recognizes where a claim is in its lifecycle, performs the work that stage requires, and can advance the claim once the stage goal is met within insurer-defined permissions and guardrails.
What is Five Sigma’s Adjuster’s Cockpit?
Adjuster’s Cockpit gives adjusters a cross-claim view of automated claims, including which claims are progressing, which need human input and which are unable to move forward. When intervention is required, adjusters can review Clive’s recommendation, confidence and supporting explanation.
What is the difference between no-touch and low-touch claims?
A no-touch claim can progress end to end without human intervention when it remains within predefined rules and guardrails. A low-touch claim is automated through the parts of the lifecycle that do not require a person, with an adjuster brought in for specific decisions, approvals or exceptions.
What is an AI operating model for claims?
It is the set of rules governing which actions AI executes automatically, which require human approval, and how work passes between them. It covers guardrails, escalation paths and the oversight view adjusters use to supervise automated claims.
How do insurers control what claims AI can automate?
Automation is configured by action, sub-organization and line of business. Insurers decide which actions execute automatically and which require approval, then widen that scope as confidence in performance grows.
Does no-touch claims automation replace adjusters?
No. It changes what adjusters spend their time on. Procedural work required to progress claims moves to AI, while adjusters handle exceptions, complex decisions, coverage questions and oversight of the automated work they supervise.
Why is straight-through processing rate a poor measure of claims automation?
STP rate counts only claims completed with zero human touches, so it ignores automation running inside complex claims. Touches per claim and active work time capture the gains that STP rate misses.
Tirtza Bensoussan
Related resources
- Blog: Agentic AI in Claims: Autonomy Levels and Guardrails
- Blog: Agentic AI in Claims: Autonomy Levels and Guardrails
- Blog: Agentic AI vs STP: Why STP Rate Stalls Near 10%
- Blog: How Agentic AI Changes the Claims Operating Model
- Blog: The Agentic Era of Claims: The System of Record becomes the System of Action
