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Are in-house AI teams the right move for...

Are in-house AI teams the right move for insurance companies?

Trending and new

9 min read

21st Oct 2024

Natalie Smithson
AI enthusiast | Tea addict | Focused on using AI assistants to win the working week
Illustration of a couple and child outside a home with an AI assistant nearby

Smart AI automation of policy management is working well for insurance customers. Of all those asking Legal & General’s AI assistant for answers to their queries, 83% say they prefer it to making phone or email contact.

But for insurance firms building AI in-house, is the extraordinary cost they face to recruit specialists and the time it takes to develop their own tools damaging for business?

Let’s examine the pros and cons of working in-house on AI, where accuracy, security and infrastructure are all critical to building trust and loyalty among customers.

Jump to section
Why are insurance companies building in-house AI teams? The dangers of trying to reinvent the wheel (or spend millions trying) The 3 unseen difficulties of building AI in-house Why the AI platform you invest in is integral to success Frequently asked questions (FAQs)

TL;DR

  • The budget and time you need to build a robust AI system is beyond the scale and expertise of most companies outside the AI industry
  • If an in-house build doesn’t give your customers positive automated experiences, your data isn’t protected, or mistakes end up costing your firm money, you can quickly fall behind those who find success straight away
  • A high success rate is a critical requirement for any AI assistant worth having ― especially for the insurance industry, as is always keeping a human in the loop to keep control of customer-facing content
  • AI takes the work of a multidisciplined team of people, including non-tech teams to perfect the language and tone you use to communicate with customers, add vital human reasoning, and use knowledge of human behaviour to send meaningful responses
  • Add the guidance of an expert AI team and, even with gaps in your own in-house knowledge or crucial skills missing altogether, you can still find success, so your agents can focus on selling insurance without any fear technicalities will get in their way

Why are insurance companies building in-house AI teams?

Insurance Edge reports “call centre agent productivity has flatlined over the past 10 years” and now sits at around 55%, but they’re positive “advanced AI driven automation technologies can help”.

Latest statistics show “92% of businesses are considering investing in AI-powered software in 2024” and, overall, business leaders are feeling “excited, optimistic, and motivated” about AI. Now digital transformation teams in insurance companies can affordably use AI to boost productivity, they no longer have to use multiple systems to manage workflows and customer relationships, making their insurance practice more efficient overall:

  • Quotes are instant
  • Policy details can be instantly retrieved
  • Renewing and cancelling policies is done in seconds
  • Customers get a hyper-personalised service too, since AI can recall the full history of every conversation you’ve ever had with them so far

The problems can start when you try to achieve all of this and more in-house.

The dangers of trying to reinvent the wheel (or spend millions trying)

Using an in-house AI team gives insurance experts the opportunity to build new automated systems to handle everything from insurance packages and loyalty programmes to loss calculation and B2B products.

The problem is the budget and time you need to build a truly robust system is beyond the scale and expertise of most companies outside the AI industry:

  • It’s incredibly expensive to hire AI talent because they’re a small group and in high demand
  • The cost required for AI expertise isn’t limited to a launch project, it’s an ongoing commitment
  • Non-experts will struggle to keep up with the extraordinarily fast-moving pace of AI development

Having an in-house AI team to keep track of what’s happening in the world of artificial intelligence and recognise how it can benefit your firm is smart because Salesforce reports, “high-performing service organisations are 2.1 times more likely than underperformers to be using AI chatbots”. What drains your resources faster than a bad investment is trying to build an AI platform when affordable high-end systems already exist.

To get ahead quickly in AI, the smarter move can be to work with a consistent budget alongside an expert AI provider to build and scale together quickly.

The 3 unseen difficulties of building AI in-house

Insurance companies ― or any company, can get caught out building AI in-house in ways that often aren’t anticipated before work begins. The outcome of that is not only being late to market with new automated offerings, but also the risk of failure overall.

If the in-house build doesn’t give your customers positive automated experiences, your data isn’t protected, or mistakes end up costing your firm money, you can quickly fall behind competitors who find success straight away with the right tools and talent on board to cope with an ever-accelerating rate of disruption.

To avoid this, it’s important to recognise three key truths:

1) Accuracy is everything

Regulated to a far higher degree than other industries, insurance companies can’t risk having an AI assistant that gets things wrong. Having full control over customer-facing content is non-negotiable.

In-house teams who know what they’re doing will be using both NLP (to understand what customers ask for) and LLM, or generative AI, to improve responses, but LLMs must be introduced safely to avoid errors, and you need the choice to limit or switch off LLM for the highest level of protection. All this extra development work takes time, budget and expertise, and it doesn’t always guarantee success.

Most providers exclusive to AI, even, aren’t even able to offer a high success rate (above 90%) for their AI assistants yet, which is the percentage of queries it can successfully recognise and fully resolve for your customers without any help from your teams. In-house AI teams are likely to struggle more, and using a hit and miss AI assistant not only puts you at risk of it making costly mistakes in its responses, you risk an increased customer churn rate as a result.

“26 percent of insurance customers will switch their insurance providers, based solely on one bad experience,” so, whether you’re dealing with a complex life insurance claim or a simple quote for insuring a new pet, incorrect or unreliable information can negatively impact both your profit levels and brand reputation. A high success rate is a critical requirement for any AI assistant worth having, as is always having a human in the loop to keep control of everything you do.

2) AI never sits in isolation

Traditionally, when you improve your technology systems, you work with a qualified team of people, a pot of money, and a deadline. That’s not the case with AI because it’s never a once-and-done task. With an AI assistant at the heart of every automation, it needs constant training, and while that might only take an AI administrator 30 minutes a week to do, it’s an integral part of maintenance for any healthy AI system.

AI is also only one part of the technological structure needed to automate insurance. You’ll also need accurate data and expert information management from an experienced provider. You also have to test and validate your systems, maintain them, and keep them compliant.

All of that takes the work of a multidisciplined team of people, and since AI is artificial, you also need non-tech teams to perfect the language and tone you use to communicate with your customers using AI , to add vital human reasoning, and use knowledge of human behaviour to send meaningful responses ― all at significant cost.

3) You’re accountable for the tech you choose

All AI rests on accurate data and having to successfully manage vast amounts of it isn’t just a problem for insurance companies. Any business using AI has to be certain their data systems meet rigid security measures and compliance regulations because, if there’s a problem one day, you’re accountable for it.

A key part of staying compliant is making sure your user interface for chatbot interactions is built to the highest accessibility standards. Your AI assistant must be able to give customers a positive onboarding experience and deal with any errors appropriately. You’ll also need advanced communication features for it to be truly successful, like being able to ask a clarifying question and give alternative answers depending on the customer’s answer, so every query can be clearly recognised, and responses take people to the correct information they need in seconds, not just offer a faux-helpful response that ends up creating more work for your support teams.

With so many AI providers on the market right now, and with new technology coming along all the time, you need to be certain your in-house team is experienced and knowledgeable enough to make the right decisions for the future of your firm.

Securing help for your in-house team

Joining forces with an experienced provider to help you achieve key customer service goals and manage your AI and data projects can remove pressure from your shoulders.

Choose the right platform provider and they’ll be able to explain in real terms every element of the technology used to fuel your AI-led systems and demonstrate a responsible commitment to security and data management too.

Why the AI platform you invest in is integral to success

Skills and knowledge aren’t the only key to successful AI projects, you also need to build on a platform with:

That last one is something you don’t get with an LLM ‘wrapper’ or opensource technology, where generative AI is simply linked up with your AI assistant directly and used without guardrails. Companies like DPD and Chevrolet have already been caught out with poor functioning AI assistants that embarrassed their brand by swearing at customers and selling expensive goods off cheap. You can avoid that by using AI already proven to work for the insurance industry, with enterprise security and strict guardrails in place.

Add the guidance of an expert AI team and, even with gaps in your knowledge or crucial skills missing altogether, you can still find success in-house without worrying something will go horribly wrong.

You can control all the parts you want to understand, and safely experiment with AI under the watchful of eye of someone who’ll warn you if you step too far. That way, your agents can focus on selling insurance while your systems are upgraded in the background, without any fear the technicalities will get in their way.

Top tip: Make sure the platform is agnostic (so you’re not tied to any particular AI provider, like Google or AWS), and you’ll have even greater freedom to move quickly to market with a new, automated offering that best serves your customers and business.

Get ahead of competitors fast

Using a fully developed AI platform like AI Studio from an experienced provider gives you the option to benefit from cutting edge AI built on foundations that are already reliable. The average success rate for our AI assistants is 96%, thanks to decades of experience, and goes as high as 99.88%.

Hire us and you’ll have the freedom to go as deep into advanced AI as you want to go, working alongside specialists who can support you in turning traditional services into modern day online experiences.

“Our AI assistant assists customers by making useful information more readily available in ways that haven’t been possible before, and therefore reducing pressure on our service centres.”

Claire Hird

Operations Director for Legal & General Insurance

→ Read the Legal & General Insurance case study

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Tell us what you’re trying to achieve, and we’ll show you how AI Studio can help you get there.

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FAQs

How does AI Studio have such a high success rate?

Our AI assistants have five crucial elements built in that need to be equally present to fully support your customers, your teams, and growth of your insurance firm:

We’ve been creating AI assistants for 10 years and managing data for almost a quarter of a century, and we’ve put everything we know into AI Studio to perfect the platform.

Read some of our case studies:

Legal & General Insurance

Barking & Dagenham Council

More…

What are the GenAI use cases in insurance?

There are lots of exciting use cases for generative AI in insurance:

  • Detecting anomalies to protect against fraud
  • Personalised risk assessments by analysing individual data
  • Automated claims processing to speed up payments
  • Making faster decisions by automating underwriting
  • Forecasting industry trends with predictive modelling
  • Personalising products based on customer behaviour trends <― one of the 7 hottest innovations for customer service this year 

Top tip: Find out how to bring LLMs into your business safely 

Can you integrate with our backend systems?

AI Studio has easy integration with all your favourite tools and apps, and if it doesn’t already exist, we can build it!

See our current list of templates and learn through eight real-world examples how APIs can transform your service.

Can we have a human in the loop?

Every AI assistant on AI Studio has human in the loop built in as standard. You can also add your own with a designated AI administrator to check over every response your AI assistant will ever send out and train it to learn new ones.

Training suggestions on our platform are automated, so it takes little time to manage.