Primo AI Agents Are Reshaping Insurance Operations

AI agents are moving beyond chatbots to automate critical insurance workflows, allowing carriers to scale operations, improve intermediary service, and increase efficiency while keeping humans responsible for complex decisions, says Tomás Tuchi, Co-Founder and COO, Primo.

For years, AI in the insurance industry has been associated with chatbots answering customer questions or virtual assistants handling basic requests. That paradigm is changing though a new generation of AI agents are beginning to execute operational processes that traditionally required teams of back-office employees.

According to Tomás Tuchi, Co-Founder and COO, Primo, the shift is not about replacing employees but about redefining their role. Rather than serving as digital assistants that respond to prompts, AI agents are becoming operational workers capable of completing repetitive workflows while leaving oversight and complex decision-making to people. "Our vision is that operators become supervisors," says Tuchi. "The same team that previously reviewed every case manually can now focus only on the situations where human judgment adds value."

Primo was founded after its founders recognized that insurance remained one of the most operationally intensive industries despite its scale. Drawing on experience in technology and financial services consulting, the company initially developed a solution to automate premium collection processes for an insurer in Argentina. 

After validating the model, Primo expanded to Mexico, viewing the country as the largest Spanish-speaking insurance market in Latin America. Rather than positioning itself as a horizontal AI software provider, the company chose to specialize exclusively in insurance, betting that deep industry knowledge would become a competitive advantage as AI development becomes increasingly commoditized.

AI Agents Move Beyond Customer Service

Unlike conventional chatbots, Primo's AI agents execute internal operational workflows. Banking reconciliations illustrate the difference. Traditionally, employees compare bank statements with internal records and manually match every payment to the corresponding insurance policy. According to Tuchi, between 50% and 70% of those activities consist of repetitive actions that follow predefined rules.

Instead of requiring employees to complete every transaction manually, AI agents perform the repetitive work automatically, present recommendations for more ambiguous cases and escalate only the most complex scenarios to human teams. The approach follows a human-in-the-loop model, ensuring every action remains auditable while allowing insurers to train agents according to their own business rules.

"We provide the insurance expertise, but every insurer teaches the agent its own operational rules," says Tuchi. "The goal is to empower teams, not replace them."

For Primo, the industry's future lies in virtual employees capable of executing business processes rather than simply answering questions. That evolution allows insurers to increase operational capacity without proportionally expanding their workforce.

Operational Efficiency Becomes the Primary Use Case

Although claims processing has attracted significant AI investment across the insurance sector, Primo sees greater opportunities in operational processes that remain highly manual. Among the areas with the greatest transformation potential are commission management for insurance brokers, customer service for intermediaries, banking reconciliations, and large-scale document review for policy issuance and renewals.

Insurance intermediaries remain the primary commercial channel for many insurers across Latin America, yet much of their interaction with carriers still depends on emails, spreadsheets and manual document exchanges. AI agents can automate many of those interactions, including policy modifications, beneficiary updates, payment information and administrative inquiries.

Tuchi says document-intensive workflows also represent a significant opportunity because insurers continue reviewing large volumes of paperwork manually despite having standardized evaluation criteria. Rather than requiring organizations to modernize their entire technology infrastructure before adopting AI, Primo works with the operational data and reports insurers already use.

"There is a perception that everything must be perfect before AI can work," says Tuchi. "The reality is that insurance companies already operate with their current systems. We work with the processes they already have while those systems continue evolving." That approach also shortens implementation cycles, which often extend from several months to more than a year in traditional insurance technology projects.

Human Expertise Remains Essential

Despite the growing capabilities of AI agents, Tuchi believes several activities will remain fundamentally human. Sensitive customer situations, including complaints, disputed claims, or commission disagreements, continue requiring human intervention because of the potential business impact and need for empathy. Likewise, decisions involving complex commercial judgment or customer-specific knowledge remain outside the scope of automation.

By contrast, repetitive operational activities represent the clearest automation opportunity. Examples include sending payment reminders, distributing policy documents, providing payment links, handling renewal requests, or routing common customer inquiries.

According to Tuchi, organizations implementing AI agents typically automate between 50% and 70% of repetitive operational tasks, depending on the workflow being addressed. Beyond productivity gains, he argues that customer and intermediary experience have become equally important performance indicators. "The question is no longer whether insurers should implement AI, the question is where," says Tuchi.

Providing faster, more consistent service to brokers may become one of the industry's strongest competitive differentiators, particularly as intermediaries continue playing a central role in insurance distribution across Latin America.

Expanding Insurance Through Better Operations

Latin America continues to report insurance penetration rates well below those of many developed markets, creating a significant opportunity for industry growth. While Tuchi does not believe AI alone will solve structural challenges such as financial education or insurance awareness, he argues that operational efficiency can improve accessibility by reducing friction throughout the customer journey.

Better customer service, stronger support for intermediaries and more efficient internal operations allow insurers to dedicate additional resources to product development and customer engagement rather than administrative work. He also points to emerging digital distribution models as evidence of how AI may reshape insurance purchasing. Recent market initiatives allowing consumers to purchase insurance products directly through conversational AI platforms demonstrate how customer interactions are beginning to evolve.

Over the next several years, Tuchi expects insurers to significantly increase operational volume without proportionally increasing headcount. Employees will increasingly supervise AI agents instead of executing repetitive administrative tasks themselves, while customer interactions become faster and more responsive.

For Primo, that transformation also defines its regional strategy. After establishing itself in Argentina, the company is focusing on becoming a leading AI partner for insurers in Mexico before expanding further across Latin America.

"We want to become the AI reference for Mexican insurers," Tuchi says. "Once we consolidate our position in Mexico, the next step is expanding across the rest of Latin America."