A new industry report by AutoRek has highlighted a growing disconnect between insurers’ ambitions around artificial intelligence and their ability to translate those ambitions into real operational outcomes, as legacy inefficiencies continue to slow performance across the sector.
The firm’s 2026 Insurance Report shows that while confidence in AI remains high, execution is still lagging significantly. According to the study, 82 percent of insurers believe artificial intelligence will play a defining role in the future of the industry. However, only 14 percent have succeeded in fully embedding the technology into their financial operations, underscoring a persistent gap between strategy and implementation.
The report, which draws on insights from 250 insurance and health insurance managers across the United Kingdom and the United States, points to structural inefficiencies that are preventing firms from modernising at pace. These include prolonged settlement cycles, fragmented data environments, and a continued reliance on manual processes, all of which are compounding operational challenges.
Settlement timelines, in particular, are becoming increasingly stretched. About 44 percent of insurers surveyed reported settlement periods exceeding 60 days, with firms handling larger transaction volumes facing even greater delays. Companies processing more than 10 million transactions annually recorded an average settlement cycle of 59 days, compared to 52 days among smaller operators.
The causes of these delays are largely systemic. Nearly half of respondents, 46 percent, identified heavy reliance on spreadsheets as a key bottleneck, while 41 percent pointed to both high transaction volumes and fragmented data systems as major contributors. With transaction volumes projected to rise by 28.7 percent over the next two years, the report warns that these pressures could intensify if left unaddressed.
Beyond delays, inefficiencies are also proving costly. Insurers are currently allocating an average of 14 percent of their operational budgets to resolving errors linked to manual workflows, reflecting the financial burden of outdated processes.
Tony Shek, insurance sector lead at AutoRek, noted that while industry players are largely aligned on the direction of travel, many have yet to take the necessary steps to keep up. He explained that the real challenge lies not in awareness, but in execution, as firms struggle to modernise their systems in line with evolving demands. According to him, companies that have already integrated automation into their financial operations are beginning to pull ahead, widening the gap between early adopters and laggards.
The report also sheds light on the uneven pace of AI adoption across the industry. While some firms are making progress, others remain at a standstill, with 6 percent reporting no use of AI at all. Several barriers continue to hinder adoption, including difficulties integrating legacy systems, cited by 42 percent of respondents, a shortage of in-house AI expertise at 40 percent, and fragmented data environments at 39 percent.
Data management challenges appear particularly acute. On average, insurers rely on 17 different data sources to process premiums, creating a complex web that is difficult to harmonise. More than half of respondents, 54 percent, identified differences in systems and data architectures as the biggest obstacle to integrating operations following mergers and acquisitions, further complicating efforts to scale automation.
These structural weaknesses are also raising concerns about the readiness of firms to deploy AI effectively. Over half of those surveyed described their data governance frameworks as still being in the early or developmental stages, suggesting that many organisations lack the foundational infrastructure required to support advanced technologies at scale.
Despite these challenges, there are indications that the industry is beginning to respond. The report shows that 50 percent of insurers are now prioritising investments in AI and machine learning, while 42 percent are focusing on automating back- and middle-office functions. In addition, regulatory pressures are playing a significant role in shaping modernisation efforts, with 51 percent of firms citing compliance requirements as a key driver of transformation.
Overall, the findings paint a picture of an industry at a crossroads. While the direction toward automation and AI-driven operations is widely acknowledged, the pace of execution remains uneven. Firms that fail to address underlying inefficiencies risk falling further behind, particularly as transaction volumes grow and operational complexity increases.
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