Justin Thomas chief pricing officer at Acorn Group explains how AI may well redefine the motor sector in the coming year.

As we look towards 2026, motor insurers face a market in flux, with pricing trends at a crucial turning point but with plenty of reason to be optimistic. The UK motor insurance market has been through a period of softening, with the ABI reporting a drop in motor insurance premiums each quarter in 2025. Across the market, prices have dropped by over 20% in some parts of Personal Lines in 2025, following a hard market peak around summer 2024. However, recent market signals suggest that this softening may just be about to reach its end.

The bottom of the market cycle typically lasts around six months. During this period, pricing stabilises, further reductions are unlikely, yet providers are often cautious about implementing increases too quickly. A “who goes first” dynamic tends to emerge, as no market participant wishes to act first and potentially risk their competitive position or sales volumes.

This hesitancy leads to a period of relative stability before the inevitable upwards correction and a return to the hardening market cycle. Barring unexpected disruptions, we should see some increases in price through next year and, for a sustainable market, that should be in line with inflation.

While navigating and responding to a hardening market can be challenging, insurers that have invested in technology to enhance their data analytics and strengthen decision-making will be better placed to succeed.

The double-edged sword of AI

This brings us to the big talking point right now – AI and how it’s being used across the industry.

In this environment of mounting risks and rapid change, AI emerges as both a tool and a challenge for motor insurers. Having price sophistication and machine learning models as part of the pricing ecosystem is important. It gives the best, most statistically robust view of what has driven past risk. AI can sift through huge datasets, identify subtle patterns, and offer pricing suggestions that might escape more manual methods.

Yet, there are risks in overreliance on AI. AI models use past events as a strong indicator of the future — yet just because something has happened before, it doesn’t necessarily mean it’s going to happen again. Change can be subtle.  This is where human bias and expertise are crucial — to tell you a result is wrong, even if it looks statistically sound.

There must be a balance between modern modelling techniques and experienced human judgement. Dangers arise when people take AI outputs at face value, without applying human expertise. Fundamental errors can creep in if human oversight is removed from the process, especially as pricing models become more sophisticated and dynamic. Over the next decade, the best insurers in the motor market will perfect this collaboration between technology and human acumen, using AI to augment and enhance human expertise, rather than replace it.  This will require the emergence of a new kind of underwriter — one who leverages the capabilities of AI but sets its predictions and suggestions in the realities of the real world.

As pricing expectations change, underwriters that utilise Machine Learning and other AI effectively but sensibly will be best positioned to navigate the turning market, updating pricing to both keep their offering competitive and reflect the evolving risk landscape.