Hippo: Bridging the Generational Divide: AI Adoption in Home Insurance

The integration of artificial intelligence (AI) into daily tasks is reshaping consumer behavior across industries, including home insurance. While AI offers significant potential to streamline claims, enhance risk assessment, and provide clearer policy information, its adoption is not uniform. A notable generational divide is emerging, presenting both opportunities and challenges for senior marketing and customer experience (CX) leaders. The 2026 Hippo Housepower Report examines these trends and outlines actionable strategies for enterprises.

The Widening Generational Divide in AI Adoption

The 2026 Hippo Housepower Report highlights a significant disparity in how different generations approach AI for home insurance research. This gap necessitates tailored engagement strategies from insurance providers.

• Generational Preference: Gen Z homeowners are substantially more likely to leverage AI tools for understanding their home insurance policies. The report indicates that 65% of Gen Z homeowners expect to use AI for this purpose in 2026, compared to only 24% of baby boomers. Millennials and Gen X fall between these two extremes, showing higher adoption rates than boomers but generally less than Gen Z. This trend suggests that younger generations view AI as an intrinsic part of their research process, a habit formed through its increasing presence in everyday routines.
• Key AI Use Cases: Homeowners are increasingly turning to AI for various insurance-related tasks. The most common applications identified include:
• Checking if they are paying a fair price (54% overall, 73% of Gen Z, 41% of Baby Boomers).
• Comparing different insurance providers and policies (49% overall, 68% of Gen Z, 35% of Baby Boomers).
• Exploring additional coverage options (48% overall, 67% of Gen Z, 34% of Baby Boomers).
• Better understanding their current policy (40% overall, 65% of Gen Z, 24% of Baby Boomers).
• Learning more about insurance riders for local risks (48% overall, 68% of Gen Z, 35% of Baby Boomers).
• Understanding how to file a claim (43% overall, 59% of Gen Z, 30% of Baby Boomers). Older generations, having often owned homes and maintained insurance for longer periods, may feel more confident navigating these processes through traditional channels, leading to lower AI adoption.

Summary: The data clearly shows a proactive embrace of AI by younger homeowners for various insurance inquiries, particularly those related to cost and coverage comparison. This underscores the need for CX strategies that cater to these diverging preferences.

AI as a Catalyst for Proactive Risk Management

Beyond basic policy understanding, AI is emerging as a critical tool for younger homeowners in proactively managing and mitigating local risks, reflecting a heightened awareness of climate-related challenges.

• Proactive Preparedness: Gen Z homeowners demonstrate a greater inclination toward preparing for home emergencies and extreme weather events, with 86% planning to do so in 2026, compared to 68% of baby boomers. This generational difference extends to specific actions, many of which can be informed by AI:
• Creating an emergency plan (e.g., evacuation routes, supplies): 36% of Gen Z homeowners vs. 28% of baby boomers.
• Purchasing optional insurance coverage (e.g., flood, wildfire): 33% of Gen Z vs. 8% of baby boomers.
• Installing more home protection equipment (e.g., sump pumps, smoke alarms): 34% of Gen Z vs. 13% of baby boomers.
• Setting aside an emergency fund for home repairs: 38% of Gen Z vs. 26% of baby boomers. This proactivity aligns with rising insurance costs, which have increased by nearly 70% on average since 2020 due to factors such as climate change, higher home values, and increased building material costs. AI tools can help homeowners, especially those facing extreme weather for the first time, to quickly identify and understand recommended riders and preventative measures based on their specific location and home characteristics.

What to do:

• Develop AI-powered risk assessment tools: Offer self-service portals where homeowners can input their location and home details to receive personalized information on common local risks and recommended insurance riders (e.g., “Flood risk in ZIP code [XXXXX] is High; consider X, Y, Z riders”).
• Integrate AI into claims preparation: Provide AI-guided checklists for documentation and immediate steps following common damage types.
• Educate on AI limitations: Clearly communicate that AI provides guidance and recommendations, but final coverage decisions and risk assessments require consultation with a licensed insurance producer.

What to avoid:

• Assuming a one-size-fits-all approach: Do not force all customers into AI-first channels. Maintain robust traditional channels (e.g., phone, in-person agents) for those who prefer them.
• Over-reliance on AI for complex decisions: AI should augment, not replace, human expertise for nuanced policy selection or claims adjudication.

Operationalizing AI for Customer Experience and Governance

For enterprises, effectively leveraging AI means more than just offering tools; it requires a robust operating model, clear governance, and careful integration with existing CX channels.

• AI as an Information Augmenter: AI tools, such as large language models, excel at summarizing complex policy documents, explaining insurance terminology, and outlining coverage basics. For example, homeowners can paste their insurance declarations page into an AI tool to receive a summary of key coverage details. This improves comprehension and prepares customers for more informed conversations with agents.
• Prompt for identifying core coverage: “I am buying my first home. In simple terms, what are the five main things a standard home insurance policy protects? Does it cover the house itself, my stuff inside, and what happens if someone gets hurt on my property? Please cite your sources.”
• Prompt for creating a claims checklist: “I recently experienced [type of home damage]. I need to file a claim with my insurance company, [name of insurance company]. Create a step-by-step checklist of what I should do before, during, and after calling [name of insurance company]. Include advice on how to document the damage and what questions I should ask the adjuster when they arrive. Please cite your sources.”
• Governance and Risk Controls: The use of public AI tools raises significant data privacy and accuracy concerns.
• Data Readiness: Implement policies that prohibit customers from sharing Personally Identifiable Information (PII) with public AI models.
• Policy: Customers must never share personal details like full name, contact information (e.g., email or phone number), home address, bank account information, or credit card numbers with public AI tools.
• Integration: For sensitive interactions, deploy enterprise-grade AI solutions (e.g., through a secure customer portal) that ensure data anonymization and privacy compliance.
• Accuracy: Establish clear disclaimers that AI output is for guidance and must be validated by a licensed professional.
• Operating Model and Roles:
• Roles: Licensed insurance producers remain critical for final policy decisions, legal interpretations, and complex claims. CX agents should be trained to guide customers on appropriate AI tool usage and when to escalate to a human expert.
• Guardrails: Define clear parameters for when AI provides sufficient information versus when human intervention is mandatory (e.g., (threshold: claim value > $X; complex legal inquiry)).
• Escalation Paths: Ensure seamless transitions from AI-assisted interactions to human agents, avoiding frustrating handoffs.
• Measurement: Track the impact of AI adoption on key CX metrics:
• Customer Effort Score (CES): Measure how easy it is for customers to find information using AI.
• Customer Satisfaction (CSAT)/Net Promoter Score (NPS): Assess overall satisfaction with AI-assisted services.
• First Contact Resolution (FCR): Monitor whether AI helps resolve simple inquiries without requiring agent intervention.
• Time-to-resolution: Evaluate how AI impacts the speed of information gathering and claim initiation.
• Complaint Rate: Track any increase in complaints related to AI inaccuracies or misunderstandings.

What ‘good’ looks like: A hybrid model where AI tools empower customers with initial information and insights, while human agents provide personalized advice, navigate complexity, and ensure compliance. This approach respects generational preferences and optimizes both efficiency and customer trust.

Summary

The generational divide in AI adoption for home insurance is a critical trend for CX and marketing leaders. While younger generations are eager to leverage AI for research, comparison, and risk preparedness, older demographics often prefer traditional channels. Enterprises must develop multi-channel strategies that embrace AI as an empowering tool for initial information gathering and proactive risk management, particularly for climate-conscious consumers. Simultaneously, stringent governance, clear communication about AI limitations, and seamless integration with human expertise are paramount to building trust and ensuring positive customer outcomes. By understanding and adapting to these evolving preferences, insurers can deliver relevant, efficient, and secure experiences across all customer segments, transforming AI from a technological capability into a strategic CX advantage.

Source: 2026 Hippo Housepower Report, published March 12, 2026.