The evidence: source quotes behind the claims

Larger accounts give the underwriter more judgment work and less admin

We say

Non-core and administrative work falls from 47% of underwriter time on books averaging under $10,000 in premium to 35% above $250,000, while risk analysis and pricing climbs from 22% to 33%. The separating variable is account size rather than the specialty label: specialty and commercial respondents report near-identical splits. The work on large accounts is bespoke and document-heavy, so triage agents and multi-agent stacks create disproportionate value by returning scarce expert hours.

Correction

Until August 2026 this page and the insurance and specialty page claimed specialty underwriters spend far more time per account than commercial ones. The Accenture survey below does not support that comparison: the specialty and commercial splits are within a point of each other. It supports the account-size comparison instead, and no public source we could find gives absolute hours per account. Both pages were corrected.

"SME underwriting is characterized by maximum automation and speed, with algorithms handling the bulk of simple risks and humans intervening regarding exceptions. Large corporate underwriting sits at the opposite end, marked by bespoke, slow and expert-driven processes to capture unique risks."

"However, even today 30–40% of underwriter time is often administrative, creating significant automation opportunities."

"We chose this line of business because it involves a considerable amount of manual data extraction and analysis ... AI technology, deployed in the right way, has the potential to remove manual tasks from our specialist underwriters, freeing them up to focus on more complex risks where human expertise and analysis are a must."

"At Arch, the intake-to-decisioning cycle time was running two to three days. That stretched quote turnaround times to three to four days."

"P&C underwriters spend on average ~40% of their time on non-core and administrative tasks, while risk analysis/pricing, and negotiation and sales support take ~30% each."

"Automation is lower the larger the account, and is lower in specialty lines and reinsurance."

Capco, "Bionic underwriting" (Jun 2026) · link · Hiscox and Google Cloud lead-underwriting announcement (Dec 2023) · link · Ivans, Arch submission-intake case (May 2026) · link · Accenture, 2021 P&C Underwriting Survey, slides 13–15 · link

The account-size and line-of-business percentages are read from the survey's two stacked-bar charts on slide 15 ("What percentage of your time do you spend each month on the following activities?"). Series were assigned by reconciling each bar against the overall averages on slide 14 (30% risk analysis/pricing, 31% negotiation and sales, 39% non-core), weighted by the published bases: total 434, of which personal lines 76, commercial 295, specialty 50, reinsurance 13; by average account premium, <$10K 111, $10–49K 104, $50–249K 128, +$250K 91. All three series reconcile to within 0.5 points. Fielded by computer-assisted web interviewing among members of The Institutes plus a Risk & Insurance sample.

AIG (Lexington): submission scale, speed, expense ratio

We say

"370k+ submissions/yr; 2–5x faster underwriting; +30% quoted, −55% time-to-quote, +40% binding; expense ratio −90bps." (integration phases, competitor table)

"AIG's Lexington Insurance unit processed over 370,000 E&S submissions in 2025 ... 2X–5X faster end-to-end underwriting across commercial lines ... 1 underwriter now handles the workload of 5."

"...it has helped deliver a 30% increase in quoted submissions, reduced time to quote for underwriters by 55%, and increased binding of submissions by approximately 40%."

"Expense ratio improved to 31.1%, down 90 basis points year-over-year, with management reaffirming a sub-30% target by 2027."

AI for Insurance case study (figures vendor-reported) · link · Reinsurance News, AIG Q1 2026 earnings call (May 2026) · link · actuary.info ROI scorecard (Apr 2026) · link

Markel: 113% productivity uplift, 24h to 2h quotes

We say

"113% underwriting productivity uplift; quote turnaround 24h → 2h." (integration phases, competitor table)

"113% uplift in underwriting productivity (GWP per FTE), effectively more than doubling output per underwriter without proportional headcount growth."

"Quote turnaround time for strategic broker partners reduced from 24 hours to 2 hours."

AI for Insurance case study, figures reported by Cytora · link

Zurich: 5 countries in 90 days, 80% less manual processing

We say

"Cytora submission intake across commercial lines; 5 countries in 90 days, 20+ markets in 16 months; 95%+ extraction accuracy; 80% less manual submission processing." (integration phases, competitor table; corrected in the Aug 2026 evidence pass)

"Zurich is scaling AI-powered risk digitization across 20+ markets within the first 16 months, reducing manual processing time by over 80% ..."

"Proven at scale across seven countries and two major lines of business, processing complex, multi-language submissions with 95%+ accuracy."

Cytora customer blog (May 2026) · link

Chubb: 150bps combined-ratio target, 85% process automation

We say

"Targeting 150bps combined-ratio savings over 3–4 yrs; ~85% automation of major UW/claims processes." (integration phases, competitor table)

"Chubb told investors in April 2026 that nine to ten AI and digital transformation projects would deliver 150 basis points of run-rate combined ratio savings over three to four years (Chubb Q1 2026 earnings call, April 22, 2026) ..."

"The company targets 85% automation of its major underwriting and claims processes, expects roughly 70% of the organization to be touched by the transformation within three years ..."

actuary.info, "Chubb's 150-Basis-Point AI Savings Promise" (Jul 2026) · link

CFC: Lane Assist, agentic underwriting pilot

We say

"'Lane Assist', billed by CFC as a world-first agentic underwriting pilot in specialty; email → quote recommendation in seconds for low-complexity cyber." (integration phases and timeline)

"...the launch of Lane Assist, a world first pilot of agentic underwriting in specialty insurance that takes a submission from email through to quote recommendation in seconds."

"Believed to be a world first in specialty insurance, Lane Assist is designed to increase the proportion of submissions handled on a low touch basis ..."

CFC press release (Apr 2026) · link

Hiscox: 3 days to 3 minutes in the London Market

We say

"S&T renewal quotes: 3 days → ~3 minutes." (integration phases, competitor table)

"...compressed specialty quote turnaround from three days to approximately three minutes in production. That is a 99.4% reduction in cycle time for sabotage and terrorism insurance renewals, delivered not as a proof of concept but as a live operational system processing real broker submissions through WTW."

actuary.info, "Hiscox Cuts London Market Quote Cycle 99% With Gemini AI" (May 2026) · link

Agents can accelerate pricing analysis, code, and documentation

We say

Agents can support end-to-end pricing and costing model development by extracting filing logic, profiling data, building independent challengers, generating governed rater code, testing, and maintaining documentation. Actuaries retain method, assumption, validation, rate, and release authority.

"Traditionally, this required actuaries to manually parse hundreds of rates over several weeks. Now, agentic artificial intelligence (AI) can autonomously reverse-engineer regulatory rate filings in a fraction of the time."

"The Actuarial Agent will support a range of targeted use cases designed to augment the expertise of Aviva's underwriters and brokers, such as enhancing pricing tools with new insights and optimising existing model code."

"Draft or update pricing models in natural language, and the agent generates schemas, rating logic, user interface components, and parameter tables with domain accuracy."

"This research project will examine how autonomous, goal-driven AI agents can transform traditional actuarial processes including data extraction, financial modeling, reserve analysis, pricing, valuation, regulatory compliance, and risk assessment."

Deloitte, "Agentic AI: Transforming pricing analysis in insurance" · link · Aviva/hyperexponential London Market pricing pilot · link · hyperexponential Actuarial Agent demonstration (vendor claims) · link · SOA Research Institute, agentic actuarial workflow scope · link

Sixfold: 50–97% faster processing, +15% hit ratios, +30% GWP per underwriter

We say

"15–30x faster intake, +15% hit ratios, up to +30% GWP per underwriter in reported deployments." (integration phases, Phase 2 card; speed figures additionally from AIG above)

"...customers using its technology have recorded substantial operational improvements, including processing times reduced by between 50% and 97%, increases in hit ratios of at least 15% and growth in gross written premium per underwriter of up to 30%."

Reinsurance News on Sixfold's AI Underwriter launch (Jun 2026) · link

CLARA: attorney-involved claims cost ~4.9x more

We say

"Attorney-involved claims cost ~4.9x more." (integration phases, Phase 2 card)

"Our research found that for casualty claims with attorney involvement, the average indemnity costs are 390% higher than for unrepresented claims ($77,807 vs. $15,936). Claim duration is 295% higher."

CLARA Analytics product page (vendor research) · link

Skills made procedures reusable; harnesses made long loops governable

We say

Agent Skills separated reusable procedural knowledge from prompts and models. Long-running harness patterns then made goals, progress evidence, handoffs, tests, and stopping conditions explicit, improving consistency across agent loops.

"This led us to create Agent Skills: organized folders of instructions, scripts, and resources that agents can discover and load dynamically to perform better at specific tasks."

"Instead of building fragmented, custom-designed agents for each use case, anyone can now specialize their agents with composable capabilities by capturing and sharing their procedural knowledge."

"However, compaction isn't sufficient. Out of the box, even a frontier coding model ... running ... in a loop across multiple context windows will fall short ... if it's only given a high-level prompt."

"The task often terminates upon completion, but it's also common to include stopping conditions (such as a maximum number of iterations) to maintain control."

Anthropic, "Equipping agents for the real world with Agent Skills" (Oct 16, 2025; open-standard update Dec 18) · link · "Effective harnesses for long-running agents" (Nov 26, 2025) · link · "Building effective agents" · link

METR: agent task length doubles about every 7 months

We say

"The length of task agents complete autonomously is doubling roughly every seven months." (timeline, Mar 2025 entry)

"We show that this metric has been consistently exponentially increasing over the past 6 years, with a doubling time of around 7 months."

"...current models have almost 100% success rate on tasks taking humans less than 4 minutes, but succeed <10% of the time on tasks taking more than around 4 hours."

METR, "Measuring AI Ability to Complete Long Software Tasks" (Mar 2025) · link

Noah Intelligence: 12% as-written, 64% mixed-speed

We say

"An independent midpoint audit puts 'broadly as written' at roughly 12%, and a mixed-speed outcome ... at roughly 64%." (timeline, 2028 estimates)

"The probability that rapid transformation arrives broadly as the scenario describes it, by the July 2028 window in which it is meant to have resolved, is about 12%. The likeliest outcome, at roughly 64%, is a mixed-speed future in which frontier capability and capital keep more or less to the AI 2027 trajectory while the institutions that were supposed to be transformed by it carry on much as before."

"On agents, the specific mechanism the scenario depends on, 78% of enterprises are running pilots and 14% have scaled one."

Noah Intelligence, "The two-speed machine" (Jul 2026) · link

Ivans: real-time appetite becomes the #1 carrier-selection factor

We say

"Agencies now rank real-time appetite information as the #1 factor in carrier selection (29% of respondents, up from 12% in 2024)." (integration phases, §2 implications)

"For the first time, real-time appetite information within the agency's preferred rating solution has emerged as the leading deciding factor agencies consider when choosing carrier and MGA partners — cited by 29% of respondents, jumping up from 12% in 2024."

Ivans, 2025 Agency-Carrier Connectivity Trends survey (Dec 2025) · link

AI 2027: the forecast, in its authors' own framing

We say

"AI 2027 said March 2027; its authors now give medians of 2028 to 2030." (timeline, 2027 estimate)

"We predict that the impact of superhuman AI over the next decade will be enormous, exceeding that of the Industrial Revolution."

"(Added Nov 22 2025, to prevent misunderstandings: we don't know exactly when AGI will be built. 2027 was our modal (most likely) year at the time of publication, our medians were somewhat longer.)"

AI 2027 (Apr 2025, with authors' later clarification) · link