Agentic AI: Your Pilot Is Not a Workforce

An agentic AI pilot can produce a convincing answer while the work behind it stays unfinished. A claims handler still has to chase a missing document. A finance officer still has to resolve a payment mismatch. The demonstration looks impressive, but the queue hasn’t moved.

Microsoft’s 2025 Work Trend Index captures that pressure: 80% of surveyed workers said they lacked enough time or energy to do their work, while 53% of leaders said productivity must increase. The survey covered 31,000 knowledge workers across 31 markets.

That gap framed Curacel’s Agentic AI session at AI Compass Lagos 2026. For insurers and banks, the challenge is moving from useful answers to completed work without losing control of consequential decisions.

Give the agent a job, not just a chat window

Agentic AI connects reasoning to actions within a defined workflow. Its usefulness depends on what it’s allowed to do and whether the result can be checked.

Curacel’s Agentic AI presentation illustrates this with Mafa, a commercial agent that helped prepare the keynote for approval. The example shows work moving towards a reviewed deliverable, rather than stopping at a generated response.

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For an insurer, the equivalent might be claims case assembly. An agent checks incoming evidence, flags missing information and prepares a case for an authorised handler. Settlement decisions remain with the people responsible for them.

These are examples of bounded delegation, not evidence that an entire department can run autonomously. A complete-looking claim file isn’t permission to pay it.

Define the workflow before connecting the agent

“Automate claims” is too broad to test. “Check a new motor claim for required documents, draft a missing-information request and route complete files to a handler” gives the team a clear starting point.

Before granting access, answer six questions:

• Trigger: What event starts the job?
• Evidence: Which approved records and systems can the agent use?
• Authority: What may it draft, and what may it change?
• Exceptions: When must it stop and ask a person?
• Owner: Who is accountable for the result?
• Measure: What baseline will show whether the workflow improves?

A recurring claim-status question may reveal a broken handoff rather than a shortage of answers. If nobody owns the next step, adding another agent won’t fix the process.

👉 Explore Curacel Support AI as a starting point for support automation.

Observe before you delegate

Start without permission to make consequential changes. In controlled shadow mode, the agent proposes outputs while the team compares them with reviewed work.

This exposes the details a demonstration can hide. A document arrives in an unfamiliar format. Two records disagree. A customer’s circumstances require specialist attention. Each exception helps define where the agent’s authority should end.

Human review needs evidence and the power to reject an action. Reviewers should see what the agent relied on, what remains uncertain and what it proposes to do next.

The NIST AI Risk Management Framework provides voluntary guidance for managing these risks. It isn’t a compliance certificate or a substitute for local law. Curacel’s AI Compass governance recap explores the related financial-services discussion.

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Measure completed work, including the corrections

A faster draft doesn’t prove that the whole process is faster. If a handler spends the saved time correcting errors, the workload has simply moved.

For a claims-intake pilot, track:

• Handoff time: How long does it take to produce a complete, reviewable case?
• Repeat work: How often must customers resubmit information?
• Corrections: How frequently do handlers override the agent’s output?
• Escaped errors: Which mistakes reach the next stage before anyone catches them?

For reconciliation, examine false matches and unresolved exceptions, not just the number of suggested matches.

Expand authority only when the evidence supports it. Drafting differs from sending; recommending a match differs from posting a ledger entry. Keep permissions narrow and define when to pause or reverse an action.

The Takeaway

An AI pilot proves that a model can help with a task. A workforce needs a defined job, an accountable owner and a result the institution can verify.

Curacel’s Super Workforce proposition is best evaluated on that basis: can people and agents complete a specific workflow repeatedly, with less avoidable effort and clear decision rights?

Start with one process. Test it against current practice. Give the agent more responsibility only when the results justify it.

Ready to scope your first workflow? Book a demo
Watch the AI Compass Agentic AI session.

View the Curacel Agentic AI presentation slides.

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