From cautious steps to bold strides: Accelerating AI adoption in Swiss insurance

Artificial Intelligence (AI) is reshaping industries worldwide at an unprecedented pace, with the US and China leading the rapid developments. In contrast, Europe and Switzerland lag in implementing these transformative technologies, risking competitive disadvantage. When compared to its European peers, Switzerland is characterised by a flexible regulatory environment, compared to the stringent frameworks set by the European Union. This flexibility could be a significant advantage in accelerating AI adoption within the Swiss market.

At the same time, Switzerland boasts a dynamic AI startup environment, with globally recognised universities, a significant presence of US technology companies, and access to local and international top talents. Together, these factors create a promising foundation for Swiss insurers embarking on AI transformation.

Swiss insurers have been exploring AI solutions in response to the need to keep pace with AI adoption. This has been mostly in the form of disjointed experimentation and pilot projects across claims and customer service areas, rather than organisation-wide transformations. This cautious approach is understandable, given the ongoing focus on cost reduction. However, AI should be seen as more than a trend, but rather as a critical enabler and accelerator of change for reshaping operations, enhancing efficiency, and redefining the way insurers engage with their customers.

To unlock AI’s full potential, insurers must go beyond experimentation and address five foundational layers: (a) data and AI platform setup, data management and ecosystem integration, (b) IT infrastructure, and security, (c) core business process re-imagination, (d) workforce onboarding and culture transformation, and (e) regulatory compliance, governance and data privacy.

Partner ecosystems : the key to E2E data management and acceleration of AI Adoption

Data is the key to successful AI adoption. While many insurers can find ideas for AI use cases, a greater challenge lies in establishing robust, governed data management systems that ensure quality, availability and security. Without strong data foundations, pilot projects rarely scale up successfully, as AI models require access to clean and trusted data sources to be effective.

Adopting a “(Gen) AI factory” model, which entails standardised data architectures, pipelines, and governance frameworks, can help consolidate such foundations. This model functions like a production line for AI, enabling faster and more efficient development by reusing components and ensuring quality control throughout the process. This approach has been shown to reduce development times for new AI solutions by up to 40%, particularly in areas such as fraud detection and claims management. Operating within an ecosystem that includes specialised tech providers and consulting firms can be a further catalyst for scaling. To harness its full capabilities, such models must be integrated as part of an organisation-wide data strategy and governance framework.

Robust data foundations offer several key benefits, including the ability to leverage components strategically, such as portfolio insights as well as third party data for risk assessment data enrichment. Furthermore, they enable faster scaling of AI solutions, including agentic AI and promote more effective partnerships with innovative ecosystem players.

IT infrastructure and IT security

Technology is the foundation for scaling AI from isolated pilot schemes to organisation-wide system transformation. It is essential for insurers to build secure, modular, and interoperable platforms to keep pace with the advances in Generative AI and Agentic AI , which enable autonomous management of complex tasks. Early pilot projects show Agentic AI’s potential to revolutionise key operations such as claims handling, policy servicing, and underwriting by reducing human intervention and accelerating decision-making. However, realising this potential requires infrastructure that supports autonomy, adaptability and continuous learning.

Swiss insurers, often operating across multiple lines of business with legacy systems, face increased complexity in integrating and modernising their technology environments. Prioritising interoperability in AI initiatives, particularly those involving agentic systems, will deliver an organisation-wide impact rather than incremental departmental gains. By investing in flexible, cloud infrastructure, insurers can not only reduce the cost and complexity of scaling but also establish a foundation for sustained innovation as more advanced models emerge.

The main benefits of an AI-ready technology stack are enhanced operational efficiency and greater organisational agility, allowing insurers to position themselves to lead in a rapidly evolving digital landscape. Prioritising future-proof technology aligned with a clear AI roadmap is essential to unlocking long-term value.

Core business process re-imagination: Joining the Agentic AI journey

The true potential of AI lies not merely in automating existing tasks but in fundamentally re-imagining business processes and operations. This is relevant for Swiss insurers, who face increasing pressure to enhance efficiency, customer satisfaction, and regulatory compliance.

While progress is already evident in P&C insurance, AI applications also hold significant potential in life and health insurance. For example, AI-powered automation can accelerate customer onboarding by quickly verifying documents and assessing risk profiles, while advanced analytics can improve claims payout accuracy by detecting anomalies and potential fraud. Beyond customer-facing processes, embedding AI into finance, risk, and compliance functions can enhance operational efficiency by automating routine tasks, reducing human errors, increasing transparency through real-time data monitoring, and accelerating reporting cycles with faster data aggregation and analysis. These improvements collectively support more informed decision-making and stronger regulatory compliance.

What sets leaders apart from laggards is their willingness to rethink processes end-to-end. Rather than introducing AI into existing workflows, insurers should redesign workflows to leverage AI capabilities, for instance, by moving from manual compliance monitoring to AI-driven continuous oversight.

The benefits of AI extend beyond efficiency. Reengineering core processes with AI can improve organisational resilience, strengthen regulatory alignment, and open new avenues for offering differentiation. To succeed, insurers must initiate cross-functional transformation efforts, bringing together business, risk, and compliance leaders to co-design AI-enabled processes across the entire value chain.

Workforce onboarding and culture transformation

Workforce readiness remains one of the biggest barriers to scaling AI within insurance firms in Switzerland. Compared to their international peers, Swiss insurers tend to adopt a more cautious approach to experimenting with AI, stemming from employee concerns over job security, trust and change fatigue.

For AI adoption to gain momentum, insurers must prioritise workforce onboarding. This involves structured training programmes to build digital literacy, targeted reskilling initiatives to prepare employees for new roles, and transparent communication about AI’s intended use. Onboarding staff in the use of AI should be viewed not as a one-time event: there should be an ongoing cultural shift. Employees need to see AI as a collaborative tool, automating routine tasks and enabling them to focus on higher-value activities such as customer engagement and complex problem-solving.

Insurers that invest early in workforce readiness will not only accelerate AI adoption but will also foster a culture of innovation and adaptability. This approach will lead to greater employee engagement, smoother transformations j, and lower resistance to change. To secure workforce buy-in for AI transformations, talent strategies must evolve alongside investments in technology.

Regulatory compliance, governance, and data privacy

In Switzerland, regulation is often viewed as a factor that can limit or slow down the adoption of AI technologies, requiring organisations to carefully navigate compliance while pursuing innovation. However, in the realm of AI, it can regulation can also serve as a catalyst. Regulators themselves are experimenting with AI to enhance supervisory capabilities and identify emerging risks. This raises expectations for insurers to adopt similarly advanced practices. Insurers that embed AI into their compliance and governance frameworks will not only meet regulatory requirements but also enhance their reputation. By implementing transparent and explainable AI systems—where decisions can be clearly understood and justified—they build greater trust with customers and regulators, who value accountability and clarity in automated processes. Beyond compliance, applying ethical principles in the adoption of AI, prioritising data privacy, and establishing robust governance guardrails help insurers manage reputational and operational risks, ensuring that innovation advances in a responsible and sustainable manner.

The benefit of a proactive compliance strategy- compared to a more widespread reactive approach for Swiss insurers- is twofold: it safeguards organisational integrity while enabling insurers to innovate with confidence. Firms that align AI deployments with regulatory frameworks will be recognised not only as compliant but as leaders in responsible innovation. The path forward lies in proactive engagement with regulators to co-develop standards and best practices, enabling compliance and innovation to progress in tandem.

Conclusion

Swiss insurers stand at a pivotal moment. While traditionally cautious towards new technologies, the rapid advances in AI—especially Generative and Agentic AI—present an unprecedented opportunity to transform the industry. Those who remain in the experimentation phase risk losing ground to more agile global competitors, whereas decisive action can establish Switzerland as a benchmark for innovation and trust in insurance.

This transformation requires more than technology alone; it demands a comprehensive approach encompassing robust data foundations, scalable infrastructure, reimagined processes, workforce readiness, and strong governance. By addressing these areas in parallel, insurers can accelerate value creation, enhance operational efficiency, and deepen customer trust.

Looking ahead, AI adoption is not just a technological upgrade but a strategic imperative that will redefine how insurers operate and compete. The time to act is now. Insurers who embrace this challenge with ambition and responsibility will not only secure their competitive position but also shape the future of the insurance industry in Switzerland and beyond.
 

Authors

• Marcel Thom, Partner, Insurance
• Madan Sathe, Partner, Insurance
• Rebecca Roj, Senior Consultant, Insurance