
3 Practical Ways Insurers Are Using AI Today
As AI tools innovate and proliferate at a breakneck pace, 'AI' itself has become the buzzword of the moment. That doesn't undo the fact that AI is a vastly transformative technology with a wide array of applications driving real business outcomes in the insurance industry.
Through conversations with insurers and their customers, we've found that the true potential of AI is rooted in its unique ability to automate tedious processes and more deeply understand customers. These practical applications are not just helping insurers work faster and smarter; they're fully reshaping how insurers operate, offering unprecedented opportunities to enhance customer understanding, personalize services and streamline operations.
But as with any new technology, adopters sometimes miss the forest for the trees, adopting new tools because they're buzzy, not because of the strategic implications. With AI becoming a fundamental part of insurance, insurers must move beyond experimentation and fully utilize AI to drive business growth and efficiency for the benefit of both the insurer and the insured. Here are some ways we see insurers utilizing AI effectively:
Comprehensive Customer Insights
The shift from AI as an aspirational technology to a practical necessity is undeniable.
Just a few years ago, insurance leaders still debated AI's potential impact. Now, they're trying to integrate it into every facet of their operations. Consider Deloitte's 2024 report on insurance industry transformation with GenAI, which found that 79% of insurance CEOs expect GenAI to change their businesses within the next three years.
Among AI's transformative attributes is the ability to aggregate and analyze disparate data sources, providing insurers with a holistic, 360-degree view of their customers. This bird's eye view of customer preferences gives insurers the ability to tailor products and services precisely to customers' individual needs, bolstering customer relationships and driving business growth in turn. AI's ability to break down data silos also enables the integration of information from various touchpoints, ranging from policy details and claim histories to social media interactions and data from connected devices like at-home IoT tools or daily wearables.
For example, last year, Mastercard successfully implemented GenAI-driven fraud detection measures in an effort to increase the speed of alerting merchants to fraud risks. The new initiative doubled their detection rate for compromised cards and reduced false positives of fraudulent transactions by up to 200%.
With AI in their corner, insurers can streamline and automate a plethora of processes while improving their ability to assess risk, tailor products, detect and prevent fraud and proactively address customer needs to foster stronger relationships.
Personalized Solutions
The days of one-size-fits-all insurance solutions are gone. Instead, today's consumers expect services tailored to their unique preferences and circumstances.
AI-powered analytics and machine-learning models, especially paired with no- or low-code platforms, empower insurers to rapidly develop and deploy customized solutions. Let's say an insurer used AI to develop a real-time risk assessment tool for small-business owners. By analyzing industry trends, customer data and financial patterns, the insurer can provide hyper-personalized coverage recommendations based on the specific attributes of any small business—granularity that traditional underwriting methods simply can't provide.
This approach reduces time-to-market for customized applications that cater to specific personas and address customers' unique challenges. It's a win-win for insurers and their policyholders alike. Heightened personalization and agility will help insurers meet customer expectations, providing a competitive edge in a rapidly evolving market.
AI-Empowered Agents
Gartner predicts that by 2028, at least 15% of day-to-day work decisions will be made autonomously through AI-powered agents (up from less than 1% in 2024).
In insurance specifically, AI is augmenting the capabilities of 'insurance agents' with tools such as generative AI, machine learning, natural language processing (NLP), computer vision and predictive analytics. This application of AI, known as 'Agentic AI,' allows systems to operate with a high degree of autonomy, capable of setting goals, planning and executing multi-step tasks without constant human intervention. Agentic AI can adapt to new information and changing environments, making decisions to achieve desired outcomes.
In underwriting, for instance, agentic AI can analyze submissions, assess risk profiles and generate policy recommendations autonomously, reducing processing time and improving pricing accuracy. In claims management, agentic AI can automate everything from intake and validation to settlement, using pattern recognition to flag potentially fraudulent claims in real time.
On the customer engagement front, these systems deliver personalized policy recommendations and initiate proactive communication, helping insurers respond to individual needs more effectively and increase customer retention. In risk management, agentic AI continuously monitors a wide range of data sources to identify emerging threats and dynamically adjust risk models, allowing insurers to be more agile and responsive in a rapidly changing environment.
Autonomous, Not Unchecked
Rather than replacing human touchpoints, AI serves as an enhancer of human roles. But as agentic AI takes on more autonomous decision making responsibilities, it also introduces new governance considerations. Insurers must implement clear policy guardrails that define the ethical and operational boundaries for AI behavior. Maintaining a human-in-the-loop approach for critical decision points ensures oversight and accountability, while transparency in AI-driven processes helps build trust by making decisions explainable and auditable.
To ensure ongoing integrity and regulatory compliance, AI systems must be continuously monitored and assessed against relevant standards. Together, these frameworks help insurers balance innovation with responsibility as they integrate agentic AI into their core operations. This synergy between human expertise and artificial intelligence is the future of insurance.
Beat The Buzz
AI's practical applications have already fundamentally transformed the insurance landscape, and embracing it is no longer optional; it is a strategic necessity for those building the future of insurance.
As this technology improves, insurers must prioritize companywide AI-driven strategies that allow them to execute their operations better than the competition. Embracing AI's ability to unify data, personalize solutions, empower agents and augment human roles will enable insurers to navigate a competitive landscape and deliver superior value to their customers. The sooner insurers integrate AI across both value chains and customer touchpoints, the sooner their competitive advantages will arise.
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