More than three-quarters of professionals surveyed across London’s insurance market expect their organisations to make substantial changes to core technology systems to support artificial intelligence and future underwriting requirements.
Research commissioned by insurance technology company Federato found that 76% of respondents anticipate significant integration, modernisation, or transformation of the systems underpinning their operations.
The survey involved 245 professionals working at Lloyd’s managing agents, company market insurers, managing general agents, reinsurers, and brokers.
Although 58% reported that their organisations already use AI in production, only 24% believed incremental upgrades to existing core systems would meet future requirements.
The distinction raises questions about the relationship between introducing individual AI applications and improving the business processes on which they depend.
Insurance underwriting involves the exchange of information between brokers, insurers, and other market participants, often across several technology platforms. Risk assessments, pricing decisions, policy administration, and settlement activities may each depend on different systems.
Where information must be transferred manually or reconciled between platforms, improvements within one part of the process may not produce equivalent gains across the entire operation.
The research also found that 89% of respondents believed their organisations had lost business to competitors because of operational speed during the previous 12 months.
That figure reflects respondents’ reported experiences rather than an independent measurement of lost sales or revenue.
Slow decisions create commercial difficulties —
The most frequently identified obstacle to core technology modernisation was subscription and multi-party underwriting, cited by 43% of respondents.
A further 42% pointed to the number of systems involved throughout the policy lifecycle, while 38% identified difficulties connecting internal technology with brokers, insurance bureaux, or settlement processes.
These problems were reflected in the time required to put underwriting decisions into practice.
Some 42% of respondents said changes in underwriting strategy took weeks or longer to reach day-to-day operations.
Reported commercial losses were more common where implementation took longer. Among respondents describing immediate implementation, 59% reported losing business because of speed.
That increased to 100% among those whose organisations required at least a month to implement changes.
The association does not establish that delayed implementation caused particular lost contracts. It nevertheless indicates how strongly surveyed professionals connected operational responsiveness with commercial performance.
Companies reporting lost business because of speed also placed greater priority on technology investment.
Half of those respondents identified unified platforms or policy administration system modernisation as their leading investment priority over the next three years, compared with 21% of respondents whose organisations had not reported similar losses.
Faster quotations and improved responsiveness to brokers were the most frequently cited objectives for AI and core system modernisation, selected by 36% of respondents.
Improved underwriting margins followed at 26%, while 25% prioritised increasing premium volumes without equivalent growth in employee numbers.
AI adoption does not remove existing constraints —
The survey found that organisations already using AI in business-critical workflows continued to report operational difficulties.
Among respondents at those organisations, 71% reported losing business because of speed, while 54% identified problems connecting core systems with external market processes.
The figures suggest that deploying AI tools within existing processes does not necessarily resolve the limitations of the underlying technology.
For insurers seeking faster underwriting decisions, modernisation may therefore involve changes to data integration, policy administration, and established workflows alongside investment in AI applications.
The survey is limited to a specialist sample of 245 London Market professionals, and its findings should not be treated as measured performance across the entire insurance industry.
Within that sample, however, the investment priorities are clear: respondents placed faster service and broker responsiveness ahead of margin improvement and the ability to increase business volumes without proportional recruitment.
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