ICS.AI commissions landmark UK dialects study with the University of Sheffield to strengthen ethical, inclusive AI in public services
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News comes as over half (52%) of the UK public are concerned AI may struggle to understand regional accents and dialects – rising to 71% in Scotland and 67% in Northern Ireland
First UK academic–industry partnership is setting a higher standard for how linguistic inclusivity is evidenced, evaluated and communicated in public sector AI
Basingstoke, UK; Tuesday 24th February, 2026: ICS.AI the UK’s fastest-growing profitable AI business, has commissioned a new national study with the University of Sheffield to tackle one of the biggest challenges in public sector AI – how well digital services understand people who speak with different regional accents and dialects.
The collaboration is the first UK academic–industry partnership to apply sociolinguistic research to the evaluation of public sector conversational AI, focusing on how systems perform in real service interactions between citizens and public bodies. The study, led by Dr. Chris Montgomery, Senior Lecturer in Dialectology at the University of Sheffield, is based on a systematic review of more than five decades of peer-reviewed research on accent and dialect variation across Great Britain.
This follows a recent survey which revealed that over half (52%) of UK residents are concerned that AI may struggle to understand accents or dialects. This increases to 71% in Scotland, 67% in Northern Ireland, and 57% in Wales.
Perception – not pronunciation – is key to bias
A Literature Review, which started ICS.AI and the University of Sheffield’s collaboration in December 2025, found that misunderstanding and bias are most likely to arise not because of how people speak, but because of how speech is interpreted. While most existing studies focus on speech patterns, far less research examines how listeners recognise and judge accents and dialects in practice. The findings provide an important evidence base for how conversational AI should be evaluated in real public-service settings, helping to ensure that systems are tested in ways that better reflect real-world variation in speech and communication.
The review also revealed that UK research on accents and dialects is extensive but heavily concentrated in a small number of locations, with many regions and communities only lightly represented. This limits the evidence base available to those developing and evaluating conversational AI, meaning strong overall performance metrics can mask uneven experiences for different speaker groups.
Dr. Chris Montgomery, Senior Lecturer in Dialectology at the University of Sheffield, said:
“There is already a substantial body of research on accent and dialect variation in Great Britain. What has been missing, however, is its systematic application to how conversational AI is evaluated in real public service contexts. This project brings sociolinguistic theory and evidence on listener behaviour into applied evaluation, enabling performance claims to be framed in ways that are both scientifically defensible and socially meaningful.”
Dr. Crispin Bloomfield, Chief Education Solutions Officer at ICS.AI, added: “Public sector AI has to work for everyone, not just for people whose voices or speech patterns are easiest for systems to process. This collaboration empowers ICS.AI to apply established sociolinguistic evidence directly to how conversational AI is evaluated in live public service environments, helping us build inclusivity in a transparent and scientifically grounded way.”
Following the Literature Review, ICS.AI and the University of Sheffield will continue working together to translate the findings into practical evaluation frameworks and new capabilities within the ICS.AI platform. In parallel, the University of Sheffield will lead further research into misrepresented dialects to strengthen the evidence base that will underpin future joint work with ICS.AI.
