RESEARCH REPORT
Underwriting rewritten
Harnessing the power of gen AI for data-driven risk management
5-MINUTE READ
July 31, 2025
In brief
- To uncover the future of underwriting, we surveyed 430 senior insurance underwriting executives across Life, Commercial and Personal Property & Casualty.
- AI and gen AI are poised to revolutionize underwriting, with insurers anticipating an increase in AI adoption, from 14% today to 70% in the next three years.
- 81% of underwriting executives believe AI/gen AI will create new roles, delivering significant efficiency gains in operations, risk assessment and decision-making.
Exploring the next chapter
The term “underwriter” has its origins in the early days of maritime insurance during the 17th century in London, stemming from a time when insurers wrote their names “under” the risk information of a ship or cargo that they were agreeing to cover. And despite the evolution of the industry—and the shift to digital platforms—the function has remained largely unchanged for over 300 years. Today, however, our survey shows an urgent need for reinvention.
Advances in technology notwithstanding, the core areas of risk assessment and pricing continue to rely on traditional actuarial models and historical data often trapped in static formats like PDFs. This makes critical information difficult to access and could result in underutilization or oversight. The legacy approach also hinders innovation and limits the potential for data-driven decision making in a rapidly evolving insurance landscape. By integrating gen AI and agentic AI into the underwriting workflow, insurance companies have a great opportunity to enable faster time to market, drive increased flow and achieve higher conversion rates.
Internal forces compelling change
Internally, insurance departments often operate in silos, resulting in vast amounts of valuable data remaining underutilized. Existing information is often fragmented, and access to it is limited. Moreover, outdated or ineffective systems hinder underwriters from working with agility. Disconnected platforms and manual data entry processes introduce significant inefficiencies. They limit the time underwriters can dedicate to high-value tasks where their expertise delivers real impact—for both insurers and their customers.
Survey respondents identified the top three challenges affecting their underwriting division’s ability to achieve its business objectives as follows:
The untapped power of data
With data being central to the top three challenges raised by the underwriters in Accenture’s survey, it’s clear that efforts to use data to optimize operations and enable data-driven decision making at scale remain in their nascent stages for most organizations. Operational challenges persist, particularly in extracting insights from unstructured data. In addition, only 44% of underwriting executives report that their divisions make extensive use of synthetic data. This number is even lower, 38%, for structured data.
Notably, there are sharp disparities across segments. A majority (63%) of Commercial P&C and 69% of Personal/Retail P&C underwriting executives say their organizations use structured data to a "large" or "very large" extent, compared to 12% of their counterparts in Life insurance.
On average, only 62% of all strategic decisions are made in a centralized manner. This can exacerbate issues like fragmentation and limited strategic alignment, highlighting great room for improvement.
External forces driving change
Meanwhile, our survey found that the top five external forces compelling change are intensifying. Insurers are increasingly pressured to respond with agility and speed to thrive as competitors accelerate efforts to bring the power of AI to bear throughout their organizations. These forces are:
Regulatory change
77%
of respondents believe regulatory changes will have a great impact on underwriting, highlighting growing concerns about compliance and evolving regulatory landscapes
Technology transformation
68%
of respondents see the introduction of new technologies having a greater impact, as automation, AI and analytics shape the future of underwriting
Rising customer expectations
67%
of respondents cite growing customer and producer demands for better service, speed and experiences as a major factor, amplifying the need for more customer-centric processes
Developing underwriting talent
64%
recognize attracting, retaining and developing talent as a challenge. They highlight the crisis of waning expertise in the wake of retirements and lack of Gen Z interest in the industry
Pressure for growth
63%
feel pressure for growth will intensify, highlighting competitive dynamics in the insurance market
Top three factors driving investment decisions
Insurers are re-evaluating their operating models and strategically directing investments toward three key objectives.
Survey respondents told us that quality, ease of doing business and talent development are key factors driving their company’s investment in underwriting.
Underwrite here, underwrite now
To achieve these objectives, insurers are turning to the technology revolution that is anchored in an unprecedented boost to AI-based capabilities. In fact, insurers anticipate that their use of AI technologies will go from 14% today to 70% in the next three years.
AI technology adoption
14%
today
70%
next 3 years
Respondents told us the extent to which their underwriting organization is using a range of technologies/capabilities now versus their expectation for use three years from now. The table shows the average percentages of respondents who answered, “to a very large extent” and “to a large extent” across 11 AI-based capabilities.
| Now | In 3 years | |
|---|---|---|
| Solutions to gather, cleanse and provide quality data views to underwriters | 33% | 85% |
| Modern policy platforms to reduce costs and improve speed to market | 28% | 85% |
| Intelligent e-mail to pre-sort broker requests | 10% | 75% |
| Integrated solutions to prevent redundant data entry | 9% | 72% |
| Generative AI-led broker-facing chatbots/virtual assistants | 10% | 72% |
| Data enrichment with internal and external data to evaluate submissions | 17% | 70% |
| Intelligent ingestion to extract and prepare data from submissions | 9% | 68% |
| Generative AI and Analytic Desktops for the assessment of risks | 11% | 66% |
| Comparative analytics to be able to evaluate risks based on peer groups | 12% | 65% |
| Broker APIs and Portals to receive submissions | 8% | 62% |
| Triage analytics to prioritize work and submissions based on risk and win capabilities | 10% | 52% |
In tandem, executives expect the impact of AI and gen AI on underwriting tasks to make an impressive jump from 17% to 75% in the next three years. This will be particularly felt in the areas of data analysis, improving agents/brokers interactions, risk assessment, decision-making and operational efficiency. It will transform the way underwriting works to be faster, more efficient, accurate and collaborative.
Impact of AI in underwriting
17%
today
75%
next 3 years
The table shows the average percentage of respondents who answered, "to a very large extent" and "to a large extent" AI/gen AI is and will impact their underwriting organitazion across 12 tasks.
| Now | In 3 years | |
|---|---|---|
| Examining statistical data, claims history and other relevant information to make informed underwriting decisions | 31% | 85% |
| Meeting or talking with agents/brokers to develop sales, gather additional information, clarify details and discuss risk factors | 19% | 82% |
| Preparing and issuing insurance policies for approved applications | 17% | 81% |
| Evaluating insurance policy renewals to determine whether to continue coverage, modify the terms or decline renewal | 15% | 80% |
| Making informed decisions about whether to approve, deny or modify insurance applications | 19% | 80% |
| Developing and implementing underwriting guidelines/rules | 17% | 79% |
| Evaluating the level of risk associated with insuring a particular individual, business or asset | 23% | 79% |
| Reviewing insurance applications and policy documents to ensure that they comply with underwriting guidelines and company policies | 13% | 75% |
| Data entry/data gathering to prepare submissions or renewals | 15% | 73% |
| Determining the appropriate premium to charge for insurance coverage based on the assessed risk | 9% | 69% |
| Collaborating with actuaries and risk analysts to assess the financial implications of underwriting decisions | 13% | 68% |
| Servicing accounts, including handling inquiries, endorsements and related tasks | 8% | 50% |
The underwriter of the future
AI and gen AI will have a significant impact on existing roles and occupations in the underwriting department. AI-driven tools will automate some tasks and augment workers in others. It will also compel new approaches to upskilling and reskilling.
A majority of our survey respondents said that AI/gen AI will impact existing roles and occupations in their underwriting department “to a very large extent” or “to a large extent”. The pie charts show averages of those two responses combined:
Changing their story
To help make faster, more accurate decisions across multiple lines of business, QBE Insurance Group, a multinational insurance company headquartered in Sydney, is scaling AI-powered underwriting solutions co-developed with Accenture. As a result, for the product lines with solutions in production, QBE can now process 100% of the submissions it receives from brokers, greatly accelerating market response time.
Change your story
Three key steps to empower the AI-led underwriter
A lot is set to happen to underwriting in the next three years. How will your organization navigate the changes? Our findings suggest three key steps to empower the AI-led underwriter:
01 Implement a strategy that will leverage agentic AI
AI agents are goal-oriented; based on multimodal foundation models, they can access external tools and data. Teams of agents can be organized so that individual agents focus on unique tasks, informing an “orchestrator agent” that can make decisions autonomously. With the evolution of gen AI toward agentic AI teams, underwriters will be able to work faster if they learn how to collaborate with these teams effectively by breaking down their workflows and delegating assignments as appropriate.
02 Support workers with a robust talent strategy
AI deployment will require a proactive and strategic approach to workforce development. Gen AI and agentic AI are definitely part of the answer. But AI alone is not the magic bullet; it will require process reinvention too. And of course, in a risk-driven business, insurance practitioners will need to understand the risks and continuously apply responsible AI principles. Accenture's Work, Workers, Workforce research suggests that embedding gen AI models in underwriting can yield substantial returns on underwriting jobs. Up to 65% of working hours are subject to automation/augmentation, with up to 30% in productivity gains at stake.
To fully reap the benefits of data, analytics and AI in underwriting, insurers will have to invest in data synthesis platforms. These platforms integrate the combinatorial capabilities of cloud and AI. They have the power of transforming data locked away in unstructured documents and from alternative sources into usable information for making underwriting decisions.
Insurers will also need to cultivate a new interest in insurance as a career. Our research found that insurers are concerned about attracting Gen Z employees, saying they believe Gen Z sees insurance as stale and excel-based. One approach is to reframe the employee value proposition to appeal to purpose-driven younger generations. Emphasize how insurance protects society, businesses and individuals. Also amplify the growing importance of innovation and skills development in this field, particularly in emerging technologies like AI.
03 Learn from AI; teach AI; evolve together
Human-led underwriting expertise should and will continue to play a pivotal role in underwriting departments. As they set top-down strategy, insurers will need to pay close attention to the lessons bubbling up as employees explore the tools they have, learn from AI, teach AI and improve on the results of their collaborations. A “human in the loop” approach is essential; people need to be heavily involved in training and refining AI systems. Supported by AI, people also need to retain control over core decision-making.
The future of underwriting is bright
AI is the beacon guiding underwriting’s future. Early adopters are outlining a roadmap that others can use to their advantage. By embracing gen AI and agentic AI, insurers can not only meet the demands of a rapidly changing market but also redefine the role of the underwriter, making it more dynamic, efficient and impactful.
