Insurance Underwriter
C1110
Future work distribution
Human only
Collaboration
AI only
This chart shows how the job's tasks split between humans and AI. "AI only" means a task AI can handle without a human — not a job removed: the role recomposes and the human refocuses on judgment, relationships and oversight.
AI Position of the Job
AI Impact on this job
The role of Underwriter in insurance is undergoing deep transformation. AI is taking on an increasing share of tasks, reshaping job roles and the skills required. This shift demands transparency and proactivity to navigate this change effectively.
This is a transforming role: AI boosts productivity but doesn’t automatically eliminate positions; instead, it reconfigures roles, skills, and decision-making spaces.
What will change
- Extracting and verifying outstanding amounts and insurance values in records to determine current values for isolated or closely linked risks.
- Drafting and sending communications (letters, emails) to request information, share pricing, or explain underwriting rules.
- Reading and sorting documents to assess risk levels (health, financial status, asset value, condition) in preparation for decisions.
What AI will improve
- Faster analysis and synthesis of files, increasing individual productivity and the ability to handle larger volumes.
- Reallocation of tasks toward data interpretation and portfolio management using AI tools; enhanced quality and speed of decision-making.
- Role evolution: greater focus on critical assessment, AI project leadership, and team coordination; requires stronger human and managerial skills.
This result describes the occupation — not your role yet
Adjust your tasks, seniority and context to uncover your real exposure to AI.
For Insurance Underwriter, AI can already do 40% of tasks on its own — on average. What about you?
Your strengths against AI
Recommendations & outlook
Skills to develop
- Master AI tools (LLMs + specialized tools) to automate data extraction and risk analysis.
- Strengthen communication and explanation of underwriting rules, leveraging AI to generate and review documents.
- Ensure quality control and compliance using AI-powered audit and verification systems.
3-year outlook
In three years, AI will have transformed how you work: repetitive tasks will be more automated, but critical decisions and human interactions will remain essential. Teams will need to blend automation with expertise, roles will reconfigure, and workforce reductions will depend heavily on the sector and choices regarding skill development investments.
AI tools used in this profession
Solutions deployed in production by professionals in this field
A general LLM assistant is already within reach
Before any specialized software, a latest-generation LLM assistant (Claude, ChatGPT, Mistral Le Chat, Gemini…) is available for this profession. Versatile, it helps draft, summarize, translate, structure or explore ideas. We treat it as a common baseline shared by almost every profession, distinct from specialized tools.
Understand this baselineMap your whole team's AI exposure
See at a glance which roles to transform first and where to invest in training.
Tasks most exposed to AI alone
7Tasks most augmented by AI
7Your role isn't an average.
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Frequently Asked Questions
AI is transforming certain insurance tasks and automating processes, but your role is evolving rather than disappearing. You will continue to assess complex risks, make informed decisions, and advise clients, activities that require human judgment. To stay relevant, it’s helpful to train in interpreting AI models, data analysis, and ethics.
The need for insurance professionals will persist, though staffing levels will adjust based on automated processes. You’ll focus more on in-depth analysis, high-value decisions, and client advisory, which require multidisciplinary teams. The key challenge isn’t the absolute number of roles but the skill level and autonomy of teams.
Start by assessing your current skills and identifying gaps in data, AI, and regulatory knowledge. Pursue certified training, participate in cross-functional projects, and collaborate with data and IT teams to integrate AI underwriting tools into your workflow. Also, develop soft skills and management abilities to guide clients in leveraging advisory value and risk management.