A risk-based approach to adopting AI in insurance
Tiffine Wang is an investment partner at MS&AD Ventures, an early-stage venture fund backed by Mitsui Sumitomo & Aioi Nissay Dowa.
As asset managers and financial executives, much of our work revolves around managing risk and safeguarding the health and longevity of our portfolios and organizations. Whether it's monitoring political instability, economic shifts, or weather-related events, the range of risks we face is vast and complex, the latest being artificial intelligence.
For years, AI was primarily the domain of smaller, innovative enterprises as they sought potential in niche applications. With recent technological advancements and increased investment, AI has evolved and become more accessible to the broader market. What was once limited to select use cases is now being adopted on a larger scale, transforming AI into a series of practical, indispensable tools in risk management and everyday life.
The rise of AI agents, chatbots and companies built around AI-first principles signals a new era of technological evolution. This next generation of AI features advanced natural language processing, allowing chatbots and agents to manage complex interactions and deliver highly personalized responses. Machine learning now provides deeper insights and more accurate risk assessments, while significant advancements in processing power and connectivity are enhancing AI's capabilities.
AI-powered recommendation engines and computer vision technologies offer real-time, precise analytics, impacting areas from autonomous vehicles to security surveillance. Generative AI further extends these capabilities by facilitating the creation of new content and designs with ease. But is it all just a hype?
AI and Insurance
AI is weaving itself into our daily lives — often without us even realizing it. Tasks that once required considerable effort are now accomplished with a few taps on a screen. Our devices anticipate our needs, and the internet feels increasingly personalized, almost as if it knows us better than we know ourselves. This subtle integration of AI into our routines represents a profound shift in how we interact with technology and, by extension, the world around us. AI touches every corner of our lives—from data-driven profiling to talioled experiences in recruitment, retail, workplace dynamics, and healthcare. Executives face two major challenges: keeping pace with AI advancements and understanding how to leverage this powerful technology while managing its inherent risks.
Challenges with Adoption
A key challenge with the integration of AI solutions into legacy systems is regulatory compliance and the ethical implications. Many corporations and larger companies have been slow to integrate AI due to concerns over data privacy, regulatory compliance, and the significant investment required for AI infrastructure. Additionally, the complexity of traditional insurance models and the need for accurate, explainable AI decisions pose further hurdles. At the same time, a growing number of insurers are putting AI to the test, recognizing its potential to transform risk management, underwriting, and claims processing. Companies that have started to embrace AI are starting to see improvements in efficiency, accuracy, and customer satisfaction, demonstrating that the potential rewards far outweigh the risks.
For traditional, established industries like insurance, AI can be a catalyst for change, revitalizing outdated systems and propelling the industry into the future, potentially leapfrogging other industries.
Addressing the risks
To effectively counteract the risks associated with AI deployments, corporations should bring in the right talent in AI, data privacy, engineering and ethics. Upgrading and implementing proper infrastructure will make it much easier to partner with AI solutions and tech companies for data-driven risk modeling. Aligning these specialists with top executives and legal teams — while still allowing business units some autonomy to implement solutions — will ensure a cohesive strategy for integrating AI across an organization. This approach prevents the siloed operations approach that can lead to wasted resources and challenges with IT and legal compliance.
Lessons from our portfolio companies and investments
Within our portfolio, many startups are adopting AI strategies, including car buying and selling, cybersecurity risk assessments, underwriting, diagnostic capabilities in healthcare, and more.
From enhancing business operations, decision-making, and customer personalization, it is becoming part of the company’s everyday life. We've also invested in a company that insures AI models, along with an insurance provider for AI startups.
Building Resilience
For insurance companies and financial institutions to successfully adopt AI, having a clear and well-defined strategy is crucial. This strategy should begin with a comprehensive assessment of the organization’s current risk management processes while identifying specific areas where AI can add value. Leaders should prioritize building a robust data infrastructure, ensuring that data is clean, accessible, and secure. Investing in AI talent and training is also essential to ensure that teams have the skills necessary to implement and manage AI systems effectively. Partnering with technology firms or AI startups can accelerate innovation and provide access to cutting-edge AI tools and expertise. As the industry continues to evolve, those who embrace AI and develop the capability to harness its potential will be better positioned to navigate the complexities of the future and drive sustained growth and stay competitive in the future.