Insurance back-office work is shifting from manual case review to AI agents that handle repetitive operational tasks, from bank reconciliations to policy document distribution. Primo, an insurance-focused AI company operating in Argentina and Mexico, says carriers using its agents can automate 50% to 70% of repetitive workflows while keeping human teams responsible for oversight and complex decisions, according to co-founder and COO Tomás Tuchi.
Primo's agents are not chatbots. They execute internal operational processes that once required teams of back-office employees, such as matching bank statements to policies and handling renewal requests. The company's founders started Primo after concluding that insurance remains one of the most operationally intensive industries despite its scale, and they first built a system to automate premium collection for an insurer in Argentina. After validating the model, the company moved to Mexico, the largest Spanish-speaking insurance market in Latin America.
From chatbots to operational workers
Tuchi describes the shift as a change in job design rather than headcount reduction. "Our vision is that operators become supervisors," he said. "The same team that previously reviewed every case manually can now focus only on the situations where human judgment adds value."
Banking reconciliation shows how the model works in practice. Employees traditionally compare bank statements with internal records and match every payment to the corresponding insurance policy. Tuchi says 50% to 70% of that work consists of repetitive actions that follow predefined rules. Primo's agents do that work automatically, present recommendations for ambiguous cases and escalate only the most complex scenarios to human teams.
The approach keeps a person in the loop on every action, so work stays auditable, and each insurer trains agents according to its own business rules. Insurers weighing new AI for Insurance tools are evaluating a category that now extends well beyond claims automation.
Where the efficiency comes from
Claims processing has attracted significant AI investment across the sector, but Primo sees larger opportunities in processes that remain deeply manual. The biggest candidates are commission management for insurance brokers, customer service for intermediaries, banking reconciliations, and large-scale document review for policy issuance and renewals.
In Latin America, intermediaries remain the primary commercial channel for many insurers, yet much of their contact with carriers still happens by email, spreadsheet and manual document exchange. AI agents can automate policy modifications, beneficiary updates, payment information and administrative inquiries. Document-heavy workflows are also a target because insurers continue reviewing paperwork manually even where evaluation criteria are standardized.
Primo works with the operational data and reports insurers already use, rather than requiring a technology overhaul first. That shortens implementation cycles that often stretch from months to more than a year in traditional insurance technology projects. It also puts the focus on workflow design as much as software, which is why AI for Operations skills matter for the teams running these systems.
Sensitive customer situations such as complaints, disputed claims and commission disagreements still require human intervention, as do decisions involving complex commercial judgment or customer-specific knowledge. The clear automation opportunities are repetitive tasks: sending payment reminders, distributing policy documents, providing payment links, handling renewal requests and routing common inquiries. "The question is no longer whether insurers should implement AI, the question is where," Tuchi said.
Why this matters for insurance professionals
The practical effect for insurance staff is that their work is being split into two categories. Rule-bound, repetitive tasks are moving to AI agents, while exception handling, training and oversight stay with people. Employees who can define business rules for agents and review the cases agents escalate will manage the higher-value work, just as Tuchi's vision predicts.
That split also changes the strategic picture for carriers. Tuchi argues that faster, more consistent service to brokers could become a competitive differentiator, particularly in Latin America, where insurance penetration remains well below developed markets. He does not claim AI alone will fix structural issues like financial education or insurance awareness, but lower operational friction can make insurance easier to buy and support. As agents take on administrative volume, the people who previously did that work can focus on the cases where human judgment changes the outcome.
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