Designing AI for Real Users -- Accessibility Gaps in Retail AI Front-End

TL;DR

This paper highlights how retail AI front-ends often unintentionally marginalize users with disabilities and diverse interaction needs, emphasizing the importance of accessibility considerations in AI design.

Contribution

It reveals the implicit accessibility gaps in retail AI front-ends and proposes front-end assurance as a practical approach to improve inclusivity.

Findings

Retail AI front-ends embed interaction assumptions that marginalize disabled users.

Accessibility issues stem from organizational and procurement practices, not just technical limitations.

Proposes front-end assurance to align AI claims with diverse user needs.

Abstract

As AI becomes embedded in customer-facing systems, ethical scrutiny has largely focused on models, data, and governance. Far less attention has been paid to how AI is experienced through user-facing design. This commentary argues that many AI front-ends implicitly assume an 'ideal user body and mind', and that this becomes visible and ethically consequential when examined through the experiences of differently abled users. We explore this through retail AI front-ends for customer engagement - i.e., virtual assistants, virtual try-on systems, and hyper-personalised recommendations. Despite intuitive and inclusive framing, these systems embed interaction assumptions that marginalise users with vision, hearing, motor, cognitive, speech and sensory differences, as well as age-related variation in digital literacy and interaction norms. Drawing on practice-led insights, we argue that these failures persist not primarily due to technical limits, but due to the commercial, organisational, and procurement contexts in which AI front-ends are designed and deployed, where accessibility is rarely contractual. We propose front-end assurance as a practical complement to AI governance, aligning claims of intelligence and multimodality with the diversity of real users.