Artificial intelligence is increasingly being used by insurers to streamline operations, automate routine processes and improve the speed of customer interactions. But as the technology becomes more embedded in the insurance industry, an important question is emerging: can greater automation actually make insurance feel more human?
For an industry often associated with complex policies, lengthy claims processes and stressful customer experiences, the potential benefits are significant. By removing administrative burdens and making information more accessible, AI could give employees more time to focus on customers, particularly when they need support most.
However, there is a distinction between making interactions faster and making them better. Insurers must ensure that automation improves the customer experience rather than creating another barrier between policyholders and the people responsible for helping them.
Matt Twist, Vice President, Sales, EMEA at Earnix, believes the opportunity lies in removing the manual work surrounding important decisions and giving employees greater capacity to focus on customers.
“At Earnix, we are helping insurers reduce the manual work that sits around important decisions. Agent Hub, part of our AI Orchestration System, AIOS, brings specialist agents into insurance workflows.”
One example is Earnix’s Product Expert Advisor, which helps employees access approved product information without having to search across multiple sources or escalate routine questions.
For Twist, however, the real value is not simply the time saved through automation, but how insurers choose to use that additional capacity.
“The real measure of success is whether employees can offer clearer explanations, resolve problems more effectively and give complex cases the attention they deserve. Insurers need to deliberately reinvest the capacity AI creates into better customer service.”
Giving employees more time for empathy
One of the most promising applications of AI is its ability to remove repetitive administrative tasks from customer-facing roles.
In insurance, this could be particularly valuable during claims, when customers may be dealing with property damage, financial uncertainty or other distressing circumstances.
Having to repeat information, wait for updates or navigate multiple departments can add unnecessary frustration to an already difficult experience.
Twist believes automation can help address these problems by bringing relevant information together and allowing employees to concentrate on understanding individual circumstances.
“Someone making a claim may be dealing with a distressing event, and the last thing they need is to repeat information while an employee searches across systems.”
However, he warns that creating more opportunities for human interaction requires insurers to be deliberate about where automation is appropriate.
AI can support employees by preparing them for customer conversations, but recognising vulnerability, responding with empathy and managing exceptional circumstances must remain clearly defined responsibilities.
This distinction is particularly important as insurers introduce increasingly sophisticated AI agents capable of handling more complex tasks.
For Quensus, the opportunity to make insurance more human involves changing the relationship between insurers and policyholders altogether.
Rather than relying on a transactional model in which insurers respond after something goes wrong, the company believes AI can support a continuous relationship built around preventing losses before they happen.
Its CEO argues that real-time asset intelligence and proactive risk mitigation can make insurance more supportive by reducing the likelihood of customers experiencing damaging incidents in the first place.
“When an insurer uses AI to alert a customer and autonomously prevent a £20,000 water leak before it happens, the interaction feels highly supportive and customer-centric, replacing the traditional, often stressful, post-loss claims process.”
This approach moves the focus away from the traditional claims experience towards ongoing protection, where technology can identify emerging risks and take action before customers are exposed to significant losses.
Making customer interactions more personal
Another opportunity for insurers is using AI to make complex insurance information easier for customers to understand.
Insurance products can be difficult to navigate, particularly when customers are trying to understand changes to premiums, policy exclusions or the reasons behind a particular decision.
For Twist, improving the customer experience starts with understanding the problem a customer is trying to solve, rather than simply introducing more automated communication channels.
“If someone wants to understand a premium, the priority is a clear, relevant explanation.”
Earnix’s Premium Explainer agent is designed to provide personalised explanations based on an individual’s policy, helping customers access relevant information without unnecessary effort.
Twist believes interactions become more human when customers feel understood, receive accessible explanations and can make progress towards resolving their concerns.
This also means preserving context throughout an interaction and ensuring customers have an easy route to a human employee when necessary.
He cautions against insurers attempting to make AI sound empathetic without ensuring it can actually resolve problems or recognise when human assistance is appropriate.
The distinction is important as insurers increasingly experiment with automated customer service. While AI-powered communication can improve availability and response times, a more conversational interface does not automatically translate into a better experience.
Quensus similarly believes the customer relationship should be built around meaningful outcomes rather than simply increasing the number of digital interactions.
Its CEO has observed a shift in customer behaviour from apathy towards more active engagement when AI is used to manage risks rather than simply generate alerts.
“Traditionally, facilities managers suffer from ‘alert fatigue’ and operational inertia due to noisy, passive sensors.”
The company argues that AI capable of autonomously managing risks and isolating water supplies can remove much of the operational burden associated with monitoring potential incidents.
“With AI autonomously managing the risk and isolating water supplies without waiting for human intervention, clients feel empowered rather than overwhelmed. They appreciate the frictionless protection it provides.”
This suggests that the value of AI may ultimately be measured not by how frequently customers interact with insurers, but by how effectively the technology prevents problems and reduces the effort required to manage them.
Measuring whether AI improves the experience
Despite the potential benefits, demonstrating that AI is genuinely improving customer satisfaction remains a challenge.
Faster responses, increased digital engagement and fewer interactions with employees may indicate greater operational efficiency, but they do not necessarily mean customers are receiving better service. Twist believes insurers need to be more disciplined when evaluating the impact of newer AI capabilities, particularly agentic systems.
He points to the importance of measuring whether customers understand the answers they receive, resolve enquiries without having to make repeated contact and feel confident in the outcomes.
Earnix has highlighted the experience of a large UK insurer transforming pricing across multiple lines of business to create a faster, more consistent and more governed approach to responding to changing market conditions.
The transformation has reportedly improved efficiency, strengthened pricing control and enabled teams to make quicker adjustments while maintaining oversight.
Twist also identifies wider business benefits, including balancing risk across portfolios and supporting sustainable profitability.
However, he stresses that insurers should avoid drawing conclusions about the customer impact of newer agentic capabilities before measuring their actual outcomes.
This is particularly relevant as businesses look to introduce AI into increasingly sensitive areas of the customer journey, where inaccurate information or poorly handled interactions can undermine trust.
Where insurers risk losing the human touch
As AI takes on a greater role in customer communication, insurers must also consider where automation can create more problems than it solves.
For Twist, one of the biggest mistakes would be prioritising the speed and volume of responses without adequately checking their accuracy and usefulness.
“AI can risk industrialising the wrong answer, especially in sectors where there is asymmetry of information. Customers often rely on insurers to explain complex products, so a confident but misleading answer can do considerable damage.”
He believes insurers need insurance-specific AI capabilities, supported by approved information, clear accountability and appropriate human oversight.
This is particularly important when dealing with complaints, vulnerable customers and difficult claims conversations, where individual circumstances can make standardised responses inadequate.
Quensus shares these concerns, warning against using AI as a means of preventing customers from accessing human support.
“The wrong way is deploying AI solely as a barrier to human contact, such as using frustrating chatbots during a complex or traumatic loss.”
Its CEO argues that insurers should avoid fully automating dispute resolution and complex vulnerability assessments, where empathy and subjective understanding remain essential.
The challenge, therefore, is establishing where AI can improve the experience and where human judgement must remain central.
For insurers, this means moving beyond the assumption that more automation will automatically produce better customer outcomes. Technology should remove friction from the customer journey, not make it harder for policyholders to receive the support they need.
The future of human-centred insurance
The emergence of increasingly capable AI systems presents insurers with an opportunity to rethink what customer service looks like.
From helping employees access policy information to explaining premiums and preventing property damage, the technology could change how customers interact with insurers throughout the life of a policy.
However, both Earnix and Quensus suggest that the industry’s success will depend on how effectively it balances automation with human judgement.
For Earnix, that means using AI to give employees more time, better information and the ability to handle complex customer needs. For Quensus, it means moving towards continuous protection, where technology can prevent losses and reduce the stress associated with traditional claims processes.
Neither approach requires removing people from the insurance experience. Instead, the opportunity is to ensure human involvement is focused where it can make the greatest difference.
Ultimately, AI may make insurance more human not by making machines better at pretending to understand customers, but by allowing insurers to spend less time on administration, respond more effectively to individual needs and prevent some of the problems that bring customers to them in the first place.
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