Why accessibility is one of the most important AI procurement decisions you can make

Robin Christopherson | 24 Aug 2026

An AI product can look convincing in a demonstration and still become an expensive problem in live service. The gap often appears only after a contract has been signed, integrations have been built, and customers or colleagues begin using the system in real situations. 

That is when organisations discover that a chatbot is difficult to navigate with a screen reader, an AI assistant cannot be controlled reliably by voice, generated answers lack the structure some people need, or a decision cannot be understood and challenged. What begins as an accessibility failure can quickly become a delivery delay, a customer complaint, a governance concern and a costly remediation programme. Two professionals looking at a monitor displaying text saying 'AI Assist' with other monitors with code

For large organisations, inaccessible AI creates a procurement and assurance problem. The decisions that determine whether AI will work for disabled people are increasingly being made before the technology is bought. 

Why AI creates a different buying problem 

Traditional software procurement usually assesses a relatively defined product. AI services may combine models, infrastructure providers, third-party components, data sources, APIs and interfaces. Any of these can change after deployment. 

A buyer must assess how a product works on the day of evaluation and how the service will be governed as models, features and suppliers change. The buyer must also establish who is responsible when an update introduces a barrier, an output becomes harder to explain or a customer cannot complete an essential task. 

This is why UK Government guidance on AI procurement emphasises AI-specific criteria, supplier evaluation and responsible deployment. Accessibility needs to sit inside that work and be addressed well before testing, shortly before launch. 

The buyer problems that surface too late 

The commercial consequences are easiest to see when AI is already embedded in a high-volume or high-risk journey. 

The contract does not secure the evidence the buyer needs. A supplier may offer broad accessibility assurances but no testing evidence, disabled-user research, known limitations or commitment to retest after material changes. 

Ownership is split across teams and suppliers. Procurement owns the contract, technology owns the integration, risk owns the controls and accessibility is asked to review the experience. When something fails, no one has clear end-to-end accountability. 

The organisation is locked into costly remediation. A barrier found after integration may require changes to workflows, interfaces, supplier agreements and operating processes that extend far beyond a simple technical fix. Team of professionals reviewing a screen about analytic summary with pie charts and graphs

Customer and colleague journeys fail under real conditions. A system may pass a controlled demonstration yet create difficulty for people using screen readers, magnification, voice control, alternative input or simplified content. 

Governance cannot keep pace with product change. An initial review becomes stale when a supplier changes the model, interface or functionality without a defined trigger for reassessment. 

These are predictable risks. Addressing them early gives an organisation more freedom to select a different supplier, strengthen contractual requirements, redesign a journey or delay scaling a proposed use of AI until it is ready. 

Why senior leaders should care 

For a senior decision-maker, the central question is whether the organisation can deploy an AI tool without creating avoidable risk, rework and loss of trust. Meeting an accessibility standard forms part of that wider assurance. 

In financial services, an inaccessible or opaque AI interaction can affect customers seeking support, understanding information or challenging an outcome. Retailers may introduce barriers into customer service or colleague tools at scale. Technology companies may embed inaccessible generated content or controls into platforms used by many other organisations. The same issue matters wherever AI affects access to work, services, information or decisions. 

Regulation adds further pressure. Article 14 of the EU AI Act requires high-risk AI systems to support effective human oversight, including the ability to understand limitations and intervene. Effective oversight is weakened if disabled customers, employees or reviewers cannot use the system, interpret its output or reach a human route when needed. 

For sectors such as financial services, the UK Government's Financial Services AI Adoption Plan describes responsible adoption at pace across areas including fraud detection, operations and risk management. Moving quickly increases the importance of early assurance. A control introduced before purchase is easier to act on than a problem discovered after rollout. 

Five questions to ask before signing 

Buyers need evidence that can stand up to procurement, governance and real-world use. A product demonstration alone cannot provide that assurance. A professional sitting at a desk, smiling at the camera with an open laptop in front of her

  1. Can everyone use the critical journeys? Ask for evidence covering disabled users and relevant assistive technologies, supported by specific information about the product’s accessibility. 
  2. Can people understand and challenge important outputs? Check how decisions, recommendations and uncertainty are explained, and whether a clear human route is available when somebody needs help or disagrees. 
  3. What changes after launch? Identify which model, interface and workflow changes require notice, retesting and renewed approval. 
  4. Who owns a failure from end to end? Name the accountable roles across the supplier, procurement, technology, risk and accessibility teams, with defined escalation and remediation routes. 
  5. What evidence will be available throughout the contract? Set expectations for known issues, testing results, user feedback, incident reporting, remediation timescales and ongoing monitoring. 

What organisations should do now 

Organisations need accessibility built into the controls they already use to buy and govern AI, supported by practical requirements and evidence. 

  • Put measurable accessibility requirements into procurement. Define the journeys, user groups, assistive technologies and evidence that suppliers must address. Make material product changes and retesting part of the contract. 
  • Review the highest-risk journeys before wider rollout. Prioritise uses of AI that affect essential customer support, access to information, employment, financial outcomes or other important decisions. 
  • Bring the right people into assurance early. Connect procurement, AI leadership, risk, legal, technology and accessibility expertise before requirements and supplier choices are fixed. 
  • Test with truly diverse users in realistic conditions. Assess the complete journey, including generated content, hand-offs, errors, escalation and recovery, alongside the interface itself. 
  • Monitor accessibility as the system changes. Create triggers for reassessment, clear ownership of reported barriers and a route to pause or constrain deployment when risk remains uncontrolled. 

How AbilityNet can reduce the risk before it becomes embedded 

AbilityNet brings together technical accessibility expertise, diverse-user insight and practical experience of working with large organisations. We support the points at which buyers and AI teams need independent evidence throughout procurement, integration and governance. 

Our accessible AI integration and consultancy services can help organisations: 

  • Review proposed AI use cases and identify the journeys where accessibility failure would create the greatest customer, colleague or governance risk. 
  • Turn accessibility expectations into practical procurement criteria and supplier questions. 
  • Assess supplier evidence and test AI-enabled experiences with assistive technologies and disabled users. 
  • Review the accessibility of explanations, human oversight, escalation and recovery routes. 
  • Build accessibility checkpoints into AI governance, change control and post-launch monitoring. 

This gives procurement teams stronger evidence, helps AI and risk leaders make better-informed decisions and enables accessibility teams to influence the choices that matter before the organisation becomes locked into a product or operating model. 

If your organisation is evaluating, buying or scaling AI, speak to AbilityNet before the requirements and contracts are fixed. We can help you identify the risks, challenge supplier evidence and build accessibility into the way AI is selected, deployed and governed.

Talk to us about accessible AI integrations 

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