What is Hype and What Works Today

If you work in insurance, you have probably heard the same line everywhere you go: 

“GenAI will transform claims.” 

It is a great headline. It sounds exciting. 
But behind the noise, many insurers are quietly asking the same questions: 

What can GenAI really do today? 
What is hype? 
And what is working right now in live claims environments? 

At The Data Company, we spend a lot of time with claims leaders who are trying to make sense of this. The truth is simple. Some parts of GenAI are genuinely changing the way claims teams work and some parts are still a long way off. 

This article breaks it down in a straightforward way, so you know where to focus your time and budget. 

 

What is Real: Where GenAI is already helping today 

Despite the noise, there are clear use cases that work today and make a real difference. 

GenAI can summarise documents incredibly well 

Claims teams spend hours reading emails, medical reports, call notes and long PDF attachments. GenAI can now pick out the key points, highlight issues, and create short summaries that adjusters can read in seconds instead of minutes. 

This cut handling time by around a third and sometimes more. 

GenAI can improve FNOL 

Customers can describe what happened in their own words and GenAI can turn that into structured claim information. It can also spot missing details and ask the right questions, which means cleaner data and faster follow-ups. 

GenAI can route and prioritise claims 

Models can help identify which claims are simple, which ones need urgent attention and which ones carry risk. This makes it easier to balance workload and get quick wins for customers. 

GenAI can support fraud teams 

GenAI can highlight inconsistencies in narratives, repeated phrases across different claims, suspicious metadata in photos and unusual patterns across claim histories. When combined with network analytics, this is very powerful. 

GenAI can draft outbound communication 

Letters, emails and claims updates can be drafted automatically and reviewed by adjusters. This saves time and improves consistency. 

None of this is science fiction. It is happening now inside real insurance operations. 

 

What is Hype: What GenAI cannot do yet 

There is also a lot of misunderstanding about what GenAI can do. 

GenAI cannot replace adjusters 

Claims decisions affect people, finances and compliance. Human judgement is essential. GenAI can support decisions, but it should not make them. 

GenAI cannot work on poor quality data 

If data is incorrect, inconsistent or split across legacy systems, GenAI will produce poor answers. Claims AI needs a proper data foundation. 

GenAI cannot handle complex losses on its own 

Liability disputes, injury cases and multi-party claims still require deep expertise. GenAI can help with summaries and research, but it cannot replace judgement. 

GenAI is not plug and play 

It needs clean data, a secure platform, governance, integration with policy and claims systems and human oversight. 

Any vendor that sells it as a magic box is selling hype, not reality. 

 

What Works Today: The practical GenAI claims toolkit 

Here are the use cases that consistently deliver good results right now: 

• FNOL assistance 

• Claims document summarisation 

• Classification and triage 

• Early fraud warning signals 

• Automated correspondence 

• Knowledge search (policy rules, procedures, past cases) 

• GenAI copilots that guide adjusters in real time 

These are achievable today with the right data platform behind them. 

 

The Missing Ingredient: A modern data platform 

This part is often ignored, but it is the real foundation. 

GenAI only works well when the underlying data is connected, clean and accessible. If your organisation still works with: 

• legacy policy systems 

• outdated databases 

• scattered claims platforms 

• PDF documents in shared drives 

• siloed customer data 

then GenAI will not give you the results you expect. 

This is why modernising onto a Lakehouse platform matters so much. It brings all your claims, policies, documents and customer data into one governed, high quality environment that AI can use. 

At The Data Company, this is where we help most clients get started. 

 

The path forward for insurers 

Here is the simple, realistic roadmap we follow with clients: 

Step 1: Assess 

Understand where data lives, how it flows and where the biggest gaps are. 

Step 2: Build a modern data foundation 

Migrate legacy data into a Lakehouse where everything is unified and governed. 

Step 3: Deploy safe, explainable GenAI 

Start with summarisation, triage and FNOL assistance. 

Step 4: Keep humans in control 

GenAI helps. Humans decide. 

Step 5: Improve continuously 

Models get better as real claim outcomes feed back into the system. 

This is not glamorous, but it works. 

 

Conclusion: GenAI is powerful, but only with the right foundations 

GenAI has real value for claims teams. It saves time, improves customer experience, highlights fraud and speeds up decisions. But it is not a replacement for adjusters and it is not a shortcut. 

The insurers winning with GenAI are the ones who fix their data first. 

At The Data Company, we help insurers build the data foundations and AI workflows that make GenAI safe, practical and genuinely useful. 

GenAI is not the future. It is already here. 
The organisations who embrace it properly will move ahead faster than the rest. 

 

Reference: 

How Generative AI Is Transforming Insurance Claims
Will GenAI and Agentic AI transform insurance claims management for insurer’s competitive advantage?

 

 

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