When foundations and ambition collide: the real test for insurance in 2026

The insurance sector is entering one of its most transformative periods in decades. AI, automation and modern data platforms are reshaping the industry, from underwriting to claims handling. While ambition has rapidly accelerated, many insurers are discovering that their foundations aren’t designed to support the pace of change.

It has never been more exciting to be an insurer. Processes once requiring entire teams can now be automated instantly. Decisions previously reliant on fragmented data and manual judgement are now informed by real-time insights. AI, automation and modern data platforms promise faster claims, smarter underwriting, lower costs and new customer engagement.

However, this chapter has arrived faster than the foundations beneath it can support. There was no dramatic shock, collapse or overnight disruption; instead, pressure accumulated quietly, shaping almost every board decision.

Most insurers are now trying to scale digital ambition on estates that were never designed for continuous change, real-time decisioning or intense regulatory scrutiny. Legacy systems still carry critical workloads, data remains siloed and governance is often retrospective. Tech teams must work to innovate as well as maintain operations, while business leaders push ahead with modernisation without increasing risk.

This is no longer simply an ambition, it is the condition for remaining credible in the market and has become the defining challenge for insurers in 2026. The real test ahead is not whether insurers can adopt new tools, but whether they can rebuild the foundations required to turn vision into durable, compliant and repeatable outcomes.

Regulation moves into the operating model

Regulatory requirements that once sat with specialists now sit firmly within operations. Claims teams are measured against digital experiences that are reshaping customer expectations. Technology leaders must stabilise ageing estates while delivering value from data, automation and AI. Each of these demands is rational on its own, but together they create significant operational pressure.

These challenges are not new. What has changed is their convergence. Regulatory scrutiny, margin compression, legacy technology, talent constraints and competitive acceleration are now inseparable. Insurers are being forced to modernise under constraint, not choice, and that distinction matters.

Regulation, consumer duty and resilience demand that insurers provide evidence-based decision-making, customer treatment and risk understanding. However, assembling that evidence manually at scale is increasingly unrealistic. Many estates were not designed to explain themselves. Data lineage, bordereaux reconciliation across broker and insurer systems, and KYC/AML checks still rely on fragmented sources and spreadsheets. Audit trails exist, but not always where needed.

The firms making the most progress have recognised something uncomfortable, but important: the issue is rarely intent, it’s architecture. When data across policy, claims, finance and third parties is connected and governed by design, resilience and auditability become natural by-products of how the organisation runs. When it’s not, compliance becomes a recurring cost centre and a source of operational fatigue.

Claims: where customer expectation becomes a stress test

Claims provide a clear example and increasingly act as the industry’s operational stress test.

Customers now compare insurance experiences with the best digital interactions they  have elsewhere. Quick settlements for simple claims are expectations, not differentiators, but friction lingers via manual hand-offs, duplicate data entry and inconsistent document intake. The impact is tangible: higher operating costs, slower claims cycles and avoidable customer churn.

The insurers improving outcomes are not attempting wholesale reinvention. Instead, they are removing friction where it compounds. First notice of loss ingestion is automated, structured and unstructured data is used to triage earlier, and decision support is embedded directly into handlers’ workflows, so expertise is applied where it matters most. The result is not simply cost reduction. It also creates cleaner, higher quality data captured at the source, improving pricing, reserving accuracy and fraud detection further downstream.

The false trade-off: foundations vs innovation

This is where the industry’s current debate often stalls. Organisations frequently frame the challenge as a choice: foundations or innovation, governance or AI, stability or speed. In practice, the insurers pulling ahead have learned to do both. They strengthen data quality and ownership while selectively applying automation and advanced analytics to high-impact use cases. They dial up ambition where foundations are strong and dial it down where they’re not, without losing momentum.

Organisations struggling to scale innovation often follow the same pattern. AI capabilities are layered onto untrusted or poorly owned data with unclear lineage. Early pilots may show promise but stall under risk or compliance scrutiny. Investment is questioned, not because technology failed, but because the operating model wasn't ready to support it.

Early adopters are compounding their advantage

The advantage window that opened over recent years has narrowed. Early movers invested in data platforms, governance and workflow integration before AI became a board-level priority. As a result, they are now compounding gains through faster underwriting decisions, improved catastrophe modelling, more accurate reserving and lower fraud leakage. Others are accelerating investment now, only to discover that advanced analytics cannot compensate for years of fragmented data and disconnected systems.

Examples of disciplined progress are emerging across the industry. Some insurers are reporting AI-enabled automation savings in the tens of millions. However the deeper shift is operational: routine claims automated, document processing standardised, rework reduced and decisions supported by consistent, trusted data. Financial gains follow operational clarity.

Why strong foundations are becoming a competitive advantage

The real transformation happening in insurance is not simply the deployment of new tools, it is the redesign of how work flows through the organisation, supported by trusted data and governed intelligence. That requires architectural choices, clear accountability and an acceptance that foundations and innovation must evolve together.

What was once optional and strategic is now structural and unavoidable. The risk is no longer moving too slowly; it’s mistaking activity for progress and ambition for readiness. The insurers that succeed will be those that treat data, automation and AI not as separate initiatives, but as the operating fabric of modern insurance, deliberately woven into how decisions are made, evidenced and continuously improved over time.

Helping you create strong foundations

For many insurers, the challenge is not recognising the need for change, but understanding where to begin. Here at Softcat, we work with insurance organisations to assess their existing estates, identify where legacy architecture is slowing progress and work with them to design practical modernisation strategies that balance innovation with operational resilience.

If you’re exploring how to unlock the value of AI, automation and advanced analytics, please get in touch.