- Intelligent agents, generative AI and process mining are redefining how processes are designed, executed and scaled in insurance companies.
- These technologies enable operational accuracy to be improved by between 30% and 50%.
- Automation is no longer enough: trends point to employee-centric processes that are aligned with business objectives and supported by data.
Hyperautomation is no longer a promise but a structural pillar in the transformation of the insurance sector. Babel, a Spanish technology multinational specialising in digital transformation solutions, has confirmed this in its experience with large groups in this market. The sector is thus beginning a transition from fragmented automation models to an orchestrated integration of exponential technologies, where artificial intelligence, autonomous agents and advanced analytics are enabling the complete redesign of the insurance value chain.
In the new scenario, priorities are no longer just about reducing costs or speeding up tasks. The most advanced trends are based on concepts such as Agentic Automation, which places the user at the centre, and the use of APA (Agentic Process Automation) agents capable of understanding context, making decisions, collaborating and executing end-to-end tasks without human intervention. These solutions enable a reduction of up to 80% in manual intervention in repetitive processes and improve operational accuracy by between 30% and 50%, according to Babel.
Added to this evolution is the deployment of Process Mining and observability tools that enable process mapping, performance measurement and real-time decision-making based on traceable and governed data. Technologies such as machine learning, artificial vision and natural language processing (NLP) are accelerating the move towards truly intelligent automation.
Luis Carlos Tristán, Director of the Insurance & Health sector at Babel, highlights that ‘The insurance sector has been immersed in a profound digitalisation process in recent years and is now hyper-automating with exponential technologies, adding Generative AI as an extension of capabilities in business processes. The key now lies in their complete integration and in ensuring that they are all correctly embedded in business processes.’
As the sector moves forward, the customer relationship model is also changing. Hyperautomation enables more agile and personalised experiences, where a claim is resolved with a click and a policy is adapted in real time. Traditional models are giving way to digital ecosystems, embedded security, on-demand microinsurance and hybrid platforms where insurers, insurtechs, healthtechs and other technology players coexist.
As Tristán points out: “A strategic vision and focus on those processes where hyperautomation can have the greatest impact on the bottom line and customer interaction is necessary. Governance between various stakeholders is also key, as is checking the scalability of the project to ensure it has a future.”
For Babel, this path towards governance based on strategies aimed at real impact is already taking shape around ten major areas of transformation that will set the course for hyperautomation in the sector in the coming years:
- End-to-end orchestration: insurers are moving away from partial automation to give way to the complete coordination of technologies such as AI, RPA, BPM and advanced analytics, applied to strategic processes and not just operational tasks.
- Intelligent agents at the heart of processes: APAs are becoming a key component: they perform complex tasks, collaborate with humans, make autonomous decisions and reduce operating costs and resolution times without compromising quality.
- Process mining and continuous observability: real-time process monitoring is now a necessity. Mapping flows, identifying bottlenecks and optimising through indicators allows companies to evolve their operations without losing control.
- Automation with a human focus: it is no longer just about efficiency. Automation is being redefined to free employees from mechanical tasks and enhance their strategic contribution. This improves both productivity and motivation.
- Data governance and scalability by design: sustainable initiatives are born with clear metrics, a shared vision and structures that favour progressive extension throughout the organisation. Scaling is no longer a desire, but a requirement.
- AI tailored to the business: Not all solutions are suitable for all insurers. Hyperautomation is committed to adaptive AI, trained with proprietary data and aligned with the particularities of each operation.
- Emerging insurance models: new products—embedded insurance, on-demand insurance, microinsurance—can only be designed and maintained with hyper-automated processes at their core. They are not an add-on: they are born automated.
- End-customer self-service: Insurers no longer manage customers; they allow them to manage themselves. From policy issuance to claims resolution, processes are designed for immediacy and control from any channel.
- Connected digital ecosystems: the value chain is expanding with data from devices, vehicles, medical applications and third-party networks. Interoperability is now a critical operational layer for any insurer that aspires to grow.
- People leading automation: beyond software, success depends on having teams that are trained, skilled and aligned with change. Without talent to interpret the technology, no transformation is possible.
Implementing these ten transformation pillars provides insurers with a framework for integrating hyperautomation in a coherent manner and generating measurable value from the outset. By combining end-to-end orchestration with rigorous data governance and a human approach that drives both efficiency and experience—for employees and customers alike—the insurance industry can transform itself into a true engine of innovation and sustainable change.