AI, hybrid work and the future of loss adjusting

Artificial intelligence (AI) is rapidly reshaping the insurance industry. From streamlining administrative processes to enhancing data analysis and decision-making, the technology is creating new opportunities to improve efficiency and service delivery across the claims lifecycle.

At the same time, the way insurance professionals work is also evolving. Hybrid and remote working models have become firmly established, changing how teams collaborate, share knowledge and develop expertise.

Together, these shifts are transforming the profession of loss adjusting. While technology has the potential to enhance capability and productivity, it also raises important questions about how future generations of adjusters will acquire the judgement, experience and critical thinking skills that have traditionally been developed through hands-on learning and mentorship.

The importance of this challenge becomes clear when considering how many experienced adjusters developed their skills in the first place. Reflecting on the lessons learned throughout a career in loss adjusting highlights why this challenge matters.

Several years ago, a developing loss adjuster attended a major loss alongside a senior colleague. Like many professionals early in their careers, the focus at the time was on the physical damage. Photographs were taken, information was gathered and efforts were made to understand exactly what had happened.

What proved far more valuable, however, was the conversation that followed. It highlighted an important lesson: loss adjusting is not simply about collecting information. It is about understanding what that information means and how it should influence the direction of a claim.

Technology is changing the way we work

There is no doubt that AI and digital technologies are transforming the insurance sector. From document review and information analysis to research and report drafting, AI is helping claims professionals complete administrative and analytical tasks more efficiently than ever before. Many adjusters are already using these tools as part of their daily work and seeing genuine benefits.

Used effectively, AI enables adjusters to spend less time on routine administration and more time focusing on complex issues, stakeholder management and strategic decision-making. This is undoubtedly a positive development.

However, many of the tasks now being automated or streamlined were traditionally part of the learning process for junior professionals. Reviewing documents, researching technical issues, drafting reports and analysing claim information often provided the foundation upon which deeper expertise was built.

As technology changes the way work is performed, it raises an important question: if technology changes how people learn, how will the industry continue to develop the next generation of experts?

How expertise is really developed

Technical knowledge is important, but expertise in loss adjusting is rarely developed through technical knowledge alone.

For many experienced loss adjusters, the most valuable lessons came from working alongside senior colleagues and mentors. Site visits, claim reviews, report discussions and informal conversations all played a significant role in professional development.

Often, the most important learning occurred after the formal work was done. It was through these discussions that junior adjusters learned how experienced professionals identified risks, interpreted evidence, managed competing stakeholder interests and developed effective claims strategies.

Similarly, having reports reviewed by senior adjusters provided insights that extended well beyond writing technique. Feedback often focused on whether key issues had been identified, whether conclusions were supported by evidence and whether attention had been directed toward the matters most likely to influence the outcome of the claim.

These interactions helped develop professional judgement, a skill that remains central to effective loss adjusting.

The impact of hybrid working

At the same time that AI is reshaping workflows, the workplace itself is evolving. Hybrid and remote working arrangements have become a permanent feature of many organisations, delivering significant benefits in terms of flexibility, productivity and employee wellbeing.

The insurance industry has embraced these changes, and rightly so. However, there is also a need to recognise that some of the informal learning opportunities that helped develop previous generations of insurance professionals can be more difficult to replicate in a hybrid environment.

Many valuable lessons are learned through everyday interactions: a conversation about a challenging claim, a review of a draft report or a discussion following a site inspection. These moments often provide practical insights that are difficult to capture through formal training programs alone.

As organisations continue to embrace both AI and flexible working models, careful consideration must be given to preserving opportunities for mentorship, collaboration and experiential learning.

Why experience still matters

Despite rapid technological advancement, complex claims continue to require human judgement. Major losses frequently involve competing expert opinions, nuanced policy interpretation issues, stakeholder expectations, commercial considerations and situations where there is no clear or straightforward answer. These challenges require more than technical capability, they require experience.

AI can process information, identify patterns and support decision-making. What it cannot do is replicate the knowledge gained through years of handling real-world claims, navigating difficult conversations, managing uncertainty and making decisions under pressure.

In many respects, the rise of AI may actually increase the value of experienced professionals.

As technology becomes more powerful, the need for knowledgeable individuals who can challenge assumptions, validate outputs, interpret findings and provide context becomes even more important. The quality of decisions will continue to depend on the quality of human judgement applied to the information available.

Looking ahead

The future of loss adjusting is not a choice between people and technology. The most successful organisations will be those that combine the strengths of both.

AI will continue to evolve, creating new opportunities to improve efficiency, consistency and insight. The industry should embrace these advancements and the benefits they bring.

At the same time, equal emphasis must be placed on mentorship, training and professional development. Future expertise will not develop by accident.  The conversations, guidance and mentoring relationships that have shaped generations of loss adjusters remain as important as ever.

Technology can support expertise. It can enhance it, accelerate it and amplify it, but it cannot replace it.

As AI and hybrid working continue to redefine the profession, the challenge for the insurance industry is not whether technology will transform loss adjusting, it already is. The challenge is ensuring that the next generation of professionals still have the opportunity to develop the judgement, experience and expertise that remain at the heart of great claims handling.