Artificial intelligence (AI) and machine learning are revolutionizing the insurance industry, driving operational efficiency, enhancing personalization, and improving customer interactions. As digital transformation accelerates and new technologies emerge at an unprecedented pace, AI-powered platforms are becoming indispensable for insurers.
The ongoing build vs buy analysis has become increasingly complex. Insurers are now asking whether their internal tech teams can match the innovation speed and expertise of specialized insurtech providers.
A recent Forrester Research report (2024) found that 45% of insurance firms are already using AI-driven solutions to optimize underwriting, claims processing, and customer service. As the pressure to integrate AI continues to grow, insurers are faced with a pivotal decision: develop custom solutions internally or leverage third-party platforms. This choice is no longer purely a matter of technology but a strategic move that will impact their long-term competitiveness in a rapidly evolving market.
As a result, the conversation has shifted from a simple "build vs. buy" decision to a more nuanced question: Is investing in external technology the smarter choice?
The Challenges of In-House Development in the Age of AI
Building an AI-powered platform in-house is a resource-intensive undertaking that comes with significant challenges for insurance companies.
First, hiring the right talent is costly. Experienced IT professionals, particularly in emerging technologies like AI, command high salaries—often ranging from $100,000 to $200,000 annually. For a larger team of specialized experts, these costs can quickly scale up, creating substantial long-term financial commitments.
In addition to personnel expenses, there are costs associated with acquiring development tools, software licenses, and infrastructure. A successful AI-driven insurance platform requires a multi-disciplinary team, including software engineers, data scientists, product managers, and operational experts. There’s also a need for staff dedicated to data model integration, employee training, and ongoing platform optimization.
Given these financial and logistical hurdles, many insurers are finding that the practical choice is to partner with third-party providers who already have the necessary expertise and resources to deliver sophisticated AI solutions. https://www.simplesolve.com/blog/build-vs-buy-insurance-technology