Insurance providers globally are escalating their capital expenditure on artificial intelligence (AI) to optimise underwriting and mitigate claims expenditures. However, a significant proportion of these firms continue to experience difficulties in securing clear financial returns. According to data from sector analysts, this deficit in profitability is directly attributable to outdated legacy systems and poorly integrated corporate data.
Strategic Projections and Financial Impacts
A report published in March by Boston Consulting Group, Inc. (BCG) indicates that AI allocation within the property and casualty (P&C) insurance sector is on a steep upward trajectory. Investment levels are projected to more than triple, reaching 1.9% of total corporate revenue in 2026 compared to trailing baseline figures.
The management consultancy’s research demonstrates that the financial benefits of AI depend heavily on how deeply it is integrated across an organisation. Insurers that successfully embed AI throughout their comprehensive operations stand to achieve an estimated 20% reduction in costs, alongside a potential increase in gross written premiums of up to 5%.
Segmented Applications and Performance Benchmarks
While many insurers currently utilise AI within underwriting and claims processing to automate routine administration, refine pricing models, and identify fraudulent activity early, the deployment remains largely fragmented. BCG observed that these tools are frequently confined to isolated business units, a factor that severely limits their aggregate economic impact.
Despite these structural hurdles, data gathered from current users reveals a strong appetite for the technology, alongside mixed operational outcomes. The table below details the performance metrics and future outlooks reported across the global insurance landscape:
| Operational Parameter | Insurer Assessment Metric | Statistical Share |
| Current Productivity | Achieved modest operational efficiency gains | 63% of users |
| Current Productivity | Realised measurable, significant output gains per employee | 11% of users |
| Business Evolution | Anticipate AI will reshape core business models (2027–2029) | Close to 60% |
| Investment Outlook | Plan to increase financial commitments to AI (2026–2028) | 66.7% (Two-thirds) |
Technical Impediments and Analytical Perspectives
A separate study published in April by A.M. Best Company, Inc. focused on the specific structural liabilities that hinder effective technological transition. Analysts pointed out that modern algorithmic data models are fundamentally incompatible with historical corporate IT infrastructure.
Kaitlin Piasecki, an industry research analyst at A.M. Best, stated within the publication:
“Legacy systems can create significant barriers when implementing AI because they simply were not built for this type of data integration.”
This perspective was reinforced by Sridhar Manyem, Senior Director of Industry Research and Analytics at A.M. Best, who noted that AI tools yield unreliable and sub-optimal outcomes when corporate data is fragmented or suffers from deficient governance protocols. Nonetheless, industry determination to adopt the technology remains intact, with two-thirds of surveyed insurers intending to expand their capital commitments to AI between 2026 and 2028.