From Legacy to AI – One Connected Agenda

Published on: 06/05/2026 Published in: Blog

From Legacy to AI: Why Insurance Needs One Connected Modernisation Agenda

Insurance leaders do not need more trend lists.

They already know the pressures.

Legacy platforms are hard to change. Data is fragmented. Claims and underwriting teams are under pressure to move faster. AI is everywhere in conversation, but much harder in production. Brokers and customers expect speed and simplicity that many insurers still struggle to deliver.

What matters now is not whether these issues exist.

It is understanding that they are no longer separate.

They are converging into one operating model challenge. Capgemini’s 2026 insurance trends work puts legacy modernisation, AI-powered distribution, and customer centricity at the heart of the sector’s agenda. EIOPA says nearly two-thirds of European insurers are already using generative AI, but most are still at proof-of-concept stage. KPMG says AI adoption is accelerating to improve underwriting, onboarding, claims processing, and cyber resilience, while trust in AI remains a priority. The FCA is also explicitly focused on claims efficiency, cost control, fraud prevention, and smart data in insurance.

That matters because many insurers are still trying to solve each issue in isolation.

A legacy programme sits in one corner.
A data programme sits in another.
Claims automation is treated separately.
AI pilots run on the side.
Distribution and service improvement become another workstream.

The result is familiar: lots of motion, slower impact.

The firms that move fastest over the next few years will not be the ones running the most programmes. They will be the ones that recognise the overlap and redesign the operating model around it.

Legacy modernisation is no longer a technical clean-up exercise

For years, insurers could treat legacy modernisation as necessary but deferrable.

That is getting harder.

Capgemini’s 2026 insurance trends identify legacy modernisation as a major trend, with insurers modernising core systems to improve flexibility, agility, and experience. Capgemini’s cloud work in financial services also highlights cloud as a route to stronger efficiency, innovation, and growth.

The reason is simple.

Legacy is no longer just an IT cost problem.

It is now a business speed problem.

If product change takes too long, growth suffers.
If integrations are hard, partner ecosystems weaken.
If new workflows require workarounds, operating cost rises.
If data remains trapped in monoliths, AI stays cosmetic.

That is why the smartest insurers are no longer modernising for the sake of platform purity. They are modernising because the existing core has become a ceiling on growth, responsiveness, and service.

For The Data Company, that means the conversation should not start with “replace everything”.

It should start with:

- where is the legacy estate slowing decision-making?
- where is it blocking integration?
- where is it trapping data that the business needs to use?
- where is it adding avoidable cost to claims, underwriting, service, or reporting?

That leads to a more commercial approach to modernisation.

Not one giant leap.

But pragmatic, modular moves that lower friction and create room for change.

Data fragmentation is still the hidden tax on insurance performance

Most insurers do not suffer from lack of data.

They suffer from too many disconnected versions of it.

Policy data sits in one place.
Claims in another.
Underwriting notes somewhere else.
Broker interactions elsewhere.
Finance has its own view.
Customer and servicing data often live across multiple platforms.

Capgemini’s insurance work points directly to the need for stronger data access and centralisation, while one of its recent insurer case studies describes the migration and consolidation of legacy data systems into a unified cloud platform to create a scalable enterprise data foundation.

This fragmentation matters because it affects far more than reporting.

It slows underwriting decisions.
It weakens portfolio visibility.
It limits fraud detection.
It makes claims handling harder to optimise.
It creates inconsistent MI.
And it makes AI harder to trust and harder to scale.

This is where many insurers quietly lose momentum.

They invest in automation, analytics, or AI, but the underlying data still arrives too late, in the wrong shape, or without enough consistency to drive action across the workflow.

The answer is not simply “build a lake”.

The answer is to connect data to the decisions that matter most.

At TDC, that is where the value usually starts:

- one trusted view across key workflows
- cleaner data flows across policy, claims, underwriting, and finance
- clearer operational visibility
- data usable in the workflow, not just in a dashboard afterwards

That is what turns data from an asset on paper into an operating advantage.

Claims and underwriting efficiency are now strategic, not incremental

In tougher conditions, claims and underwriting efficiency stop being operational nice-to-haves.

They become strategic levers.

KPMG says insurers are using AI to realise efficiencies in underwriting, speed onboarding and claims processing, and reinforce trust. The FCA is also working with firms and the ABI to improve efficiency and control costs in claims handling, while continuing to focus on fraud-related issues. Reuters recently reported strong demand for Verisk’s underwriting, claims, and fraud analytics tools, driven by insurers’ need for better policy risk assessment and anti-fraud capability.

That aligns with what most insurance leaders already feel.

They need:

- faster decisioning
- better risk selection
- lower leakage
- more automation
- stronger fraud detection
- better control

And they need all of that without weakening governance or regulatory confidence.

This is why workflow-level improvement matters so much.

The opportunity is rarely just “more automation”.

It is better automation in the places where economics and risk meet:

- submission intake
- triage
- claims routing
- document handling
- exception management
- fraud signals
- underwriting support
- portfolio steering

That is where TDC can help insurers move from abstract efficiency goals to measurable workflow outcomes.

Not just more tooling.

Better flow, better inputs, better controls, and better decisions.

AI is moving beyond pilots, but production is the real test

The market has moved past the question of whether insurers are exploring GenAI.

They are.

The more interesting question is whether they can operationalise it safely.

EIOPA’s February 2026 survey found that nearly two-thirds of European insurers are already using GenAI, but most are still at proof-of-concept stage. McKinsey has also noted that only a few insurers have extracted outsize value from AI, and that doing so requires a more strategic rewiring of the enterprise rather than isolated experimentation.

That should sound familiar.

Pilots are relatively easy.
Production is not.

Because production AI requires more than a working model.

It needs:

- trusted data
- workflow fit
- explainability
- exception handling
- monitoring
- governance
- clear ownership
- controls strong enough for regulated decision environments

This is where many insurers get stuck.

The use case looks strong.
The demo works.
The business case is attractive.

But the operational reality underneath is not ready.

That is why TDC’s role should not be framed as “deploying AI”.

It should be framed as helping insurers productionise AI where it can genuinely deliver value:

- grounded in real workflows
- connected to trusted data
- designed with controls
- measurable in terms of speed, quality, leakage, or experience

That is where AI starts to become commercially useful.

Broker and customer experience are now hard commercial differentiators

Many insurers still think of experience as a front-end issue.

It is not.

It is an operating model issue.

Capgemini’s 2026 insurance trends explicitly call for insurers to take ease of doing business “to the next level” through digital agency capabilities, while also noting that 60% of customers are willing to share personal data for tailored coverage and that seamless omnichannel engagement is becoming a key differentiator. Deloitte’s 2026 insurance outlook likewise highlights changing customer expectations, broker consolidation, and the importance of modernisation.

That has direct implications.

If brokers face slow onboarding, poor visibility, repeated data requests, or clunky interactions, placement friction rises.

If policyholders experience fragmented servicing, slow response times, or poor communication, retention weakens.

If internal teams cannot access joined-up information quickly, the experience degrades even when the intent is right.

Experience is no longer just about better digital surfaces.

It is about:

fewer handoffs
cleaner data collection
stronger workflow design
better orchestration
faster decisions
more relevant communication

In other words, experience improves when the operating model improves.

That is why the insurers that stand out will be the ones that make it easier to do business with them, not just the ones that market themselves well.

The real issue is convergence

Taken separately, each of these pressures feels familiar.

Taken together, they point to something bigger.

Insurance is shifting from siloed technology initiatives to a more connected operating model agenda.

Legacy, data, efficiency, AI, and experience now rise or fall together.

That is the story.

And it changes how firms should respond.

Not with five separate programmes.

But with a practical roadmap that links:

modular modernisation
better data foundations
workflow-level efficiency
governed AI
easier broker and customer journeys

That is where The Data Company fits.

We help insurers connect these agendas in a way that creates commercial value:

modernise without waiting for one giant reset
reduce fragmentation across data and workflows
improve claims and underwriting efficiency
productionise AI with stronger controls
improve speed and ease of doing business for brokers and customers

The insurers that grow fastest over the next few years will not necessarily be the ones spending most aggressively.

They will be the ones that reduce friction fastest across the operating model.

That is where the next advantage sits.

If these five pressures are all showing up inside your organisation, the question is not which one matters most. It is where convergence is creating the biggest commercial drag. That is usually the best place to start.

References

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