The Swiss Re Headquarters In London.

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Swiss Re has spent more than 160 years helping organizations navigate risk. Today, that mission is evolving. Rather than stepping in after events unfold, the company increasingly aims to anticipate and prevent them. For Pravina Ladva, Swiss Re’s Group Chief Digital and Technology Officer, that shift is being driven by data, technology and artificial intelligence.

Ladva’s role spans the full technology landscape, from infrastructure and cloud to software, data and AI. But at its core, her mandate centers on enabling Swiss Re to deliver more predictive, insight-driven services to clients around the world.

Building an AI-Ready Foundation

Ladva described Swiss Re as “AI ready,” a position built on years of investment in data. That foundation rests on three pillars: technology, talent and trust.

On the technology side, the company has consolidated more than six petabytes of data into a unified environment, covering tens of thousands of contracts and risk models. Equally important is understanding how that data is structured and accessed. “It’s about knowing exactly what we’ve got, where we’ve got it and how we can use it,” she noted.

But data alone is not enough. Ladva emphasized the importance of analytical capability across the organization. “It’s one thing having the data,” she explained. “It’s another thing how you use it.” To that end, Swiss Re has invested heavily in talent development, combining hiring with internal reskilling and partnerships with universities. Crucially, Ladva stressed that data is not confined to a single function. “The democratization of data is key,” she said. “The more hands it’s in, the more value you derive.”

The third pillar is trust. In an industry where decisions carry significant financial and societal implications, data must be accurate, secure and governed effectively. “I firmly believe in digital trust,” Ladva said, underscoring the need for quality and governance to ensure reliable insights.

Culture as a Catalyst for Innovation

While technology and data are essential, Ladva pointed to culture as the true differentiator. “People can go anywhere and do work,” she underscored. “But to do the best work, the secret ingredient is culture.” Her approach to culture centers on breaking down traditional barriers between business and technology teams. Rather than operating in silos, she advocates for fully integrated, multidisciplinary teams. “I shouldn’t be able to tell who is from business and who is from technology,” she explained.

This shift reflects a broader evolution in skillsets. Ladva believes that professionals across the organization must become “bilingual,” understanding both business context and technological possibilities. “The more we drive towards that, the better outcomes we obtain,” she offered. The result is not only improved delivery but also greater employee engagement. Teams that operate in this integrated model, Ladva noted, often resist returning to more traditional ways of working.

From Experimentation to Enterprise AI

Swiss Re has long used machine learning in areas such as risk modeling. The emergence of generative AI, however, is opening new possibilities, particularly in addressing long-standing inefficiencies. One example lies in data ingestion. The reinsurance industry processes vast amounts of information across varied formats, often requiring significant manual effort. “Colleagues should be spending time analyzing value, not extracting it,” Ladva underscored. Generative AI is now helping automate that process, allowing employees to focus on higher-value work.

The company’s approach to AI has been deliberately broad and inclusive. Early on, Swiss Re made generative AI tools available to all employees. “If you don’t use this in your day-to-day job, you won’t become comfortable with it,” Ladva explained. That decision has driven widespread adoption, with roughly 60% of employees using AI tools regularly. It has also sparked grassroots innovation, as teams build custom agents to automate specific tasks. These solutions are then shared across the organization through a governed internal library.

At the same time, Swiss Re is pursuing larger, enterprise-level transformations. Ladva described a shift toward reimagining entire value chains, such as underwriting and claims, rather than applying technology to isolated steps. “70% of the conversation is about process and people,” she said. “The last bit is about the technology.” The impact is already visible. Processes that once took weeks can now be completed in days, enabling faster decision making and improved client service.

The Human Side of Transformation

For Ladva, the success of AI initiatives depends as much on change management as on technology itself. “I could build the best solution ever,” she said. “But if I haven’t considered how people interact with it, it will not succeed.” Her approach emphasizes co-creation, continuous learning and employee engagement. Initiatives such as Swiss Re’s internal innovation awards encourage teams to experiment with new ideas, many of which now involve AI.

Importantly, Ladva frames AI as a tool for augmentation rather than replacement. By automating routine tasks, the technology allows employees to focus on more complex and meaningful work. “It’s about enabling colleagues to work higher up the value chain,” she noted.

Data, AI and the Future of Risk

The convergence of data and AI is also reshaping how Swiss Re approaches its core business of risk management. Ladva highlighted tools such as Magnum, which enables clients to perform underwriting using Swiss Re’s insights, as well as advanced modeling capabilities that help organizations assess risks across global operations. These capabilities combine multiple data sources, from satellite imagery to historical risk data, to provide actionable insights. “It gives practical capabilities into the hands of people who can take action,” she said.

Ladva sees the current wave of AI as just the beginning. She drew parallels to earlier technological shifts, noting how tools like email transformed the nature of work. “We’re right at the start of this journey,” she noted.

Beyond AI, she is also closely watching developments in quantum computing, particularly the potential for exponential acceleration when combined with AI.

For Ladva, however, the most important question is not the technology itself but its impact. “What are these capabilities going to do for corporations, for our day-to-day lives and how we work?” she asked.

At Swiss Re, the answer is already taking shape. By combining data, technology and a culture of innovation, the company is redefining its role from responder to predictor, helping build a more resilient world in the process.

Peter High is President of Metis Strategy, a business and IT advisory firm. He has written three bestselling books, including his latest Getting to Nimble. He also moderates the Technovation podcast series and speaks at conferences around the world. Follow him on X @PeterAHigh.