Exploring the role of AI in addressing the customer understanding challenge
Seven in ten people in the UK are worried about the economic impact of AI. Half would rather avoid it altogether (King's College London and Policy Institute, 2026). Yet many businesses are already using it, and customer communications is one of the areas that could see change.
The concern is understandable. AI makes it faster and easier to produce more communication. Without the right human input, that also means faster and easier to produce more communications that might not be any better for the customer. It could scale up current low customer understanding, and that means scaling confusion, complaints, and ultimately worse customer outcomes.
Whatever the tool, customer understanding is still the measure
The technology firms use to produce communications does not change what those communications need to achieve. Customers still need to understand what they are being told. That obligation does not change.
This doesn’t mean to say that firms shouldn’t make the most of the opportunities that AI creates, or that AI is always going to have a negative impact on the quality of customer communications. However, even if you avoid using it altogether, or use it all the time, you are still accountable for what you produce and send out. That means highly skilled people in your comms creation and review processes remain essential.
For FCA regulated firms, Consumer Duty makes customer understanding requirements explicit, and its guiding principles apply regardless of whether a communication was assisted by AI or not. The question that is most relevant to regulators is not whether AI is being used, but whether customers are being served well.
The FCA's Mills Review, launched in January 2026, is examining exactly this territory; by looking at how advanced AI could reshape retail financial services and affect consumers through to 2030 and beyond. That review is a signal that the regulator is taking the long-term implications seriously. Firms should be doing the same.
How AI can help with customer understanding
There is no doubt that AI is efficient. It can produce communications much faster than people can, respond to customer queries quickly, and deliver useful analysis; identifying complicated language, flagging accessibility problems, and spotting common themes in customer feedback.
Providing a foundation and a direction for communications is well within AI's current capabilities, when used well.
Why AI cannot solve things alone
The problem is context.
Every communication exists within what we call the Communication Environment: the specific audience, the customer journey it sits within, the audience it is trying to reach, and the emotional state of the person receiving it. Two communications with similar purposes can look very different once you account for those factors. A list of rules cannot capture that. Neither can a language model – at least not with the level of understanding of a real person.
The Plain Numbers Method is principles-based. It relies on the person applying it to think carefully about the intent of the communication and account for the nuances that make a real difference to whether customers understand it. That human judgement is what produces the significant improvements in comprehension our research has consistently shown.
This matters even more when communication involves complex information in emotionally charged situations. Maths anxiety is a good example: customers who feel anxious about numbers will engage with information differently. Understanding that, and designing for it, requires human insight that AI cannot reliably replicate.
The future role of AI
AI is still developing, and the opportunity it represents is as real as the danger it poses. The firms that will use it well are the ones that treat it as a tool within a process, not a replacement for one. AI-supported communications still require human oversight. Trained Plain Numbers Practitioners play a crucial role in bringing the contextual judgement that determines whether a communication will actually work for the customer receiving it.
The goal is not to choose between speed and quality. It is to use AI where it helps, while keeping customer understanding and customer outcomes as the focus, not speed of production, as the measure of success.
We asked AI if AI is enough
In writing this article, I asked Chat GPT to answer the very question I am addressing here. Even AI tools themselves are cautious about seeing technology as the standalone solution. Here’s what it concluded:
“In conclusion, AI can contribute to improving understanding of customer communications, but its success depends on how well it is integrated into a broader strategy that includes human oversight.”
On this occasion, I am happy to allow AI to conclude for us, but only because I have given it the oversight and input that it needs.
Author: Ben Perkins, Director of Partnerships & Services at Plain Numbers