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Beyond the Prompt: Engineering Agentforce UX with Intention
When deploying agents, we often trust the model to make it accessible. AI doesn’t live with a disability; people do. We’ll demonstrate how to ground Agentforce workflows in authentic user research.

, User Experience Lead, Salesforce

, Accessibility Engineer, Salesforce

, Lead Accessibility Engineer, Salesforce

Product: Agentforce
Role: Designer, Developer
Industry: Technology
Topic: Agentic AI
Session Level: Intermediate
Session Format: Theater
  • Wednesday, Sep 161:00 PM - 1:20 PM PDT
    (8:00 PM - 8:20 PM GMT)
    Moscone West, L1 Forest, Redwood Theater
    FIRST COME FIRST SEATED
Session Summary: This Salesforce session focused on bridging the accessibility gap in AI-driven experiences by leveraging inclusive design principles and user-centric research methodologies. The speakers emphasized that while AI has the potential to revolutionize user experiences, it is not inherently accessible, as 95% of the top 1 million websites fail at least one WCAG compliance test, and automated tools only capture 30-40% of accessibility issues. They outlined a comprehensive approach to accessibility, starting with extending personas across disability dimensions, defining accessible jobs to be done, and conducting authentic user research with assistive technology users. By integrating accessibility-focused acceptance criteria and human validation into AI workflows, Salesforce aims to create dynamic and inclusive interfaces that benefit all users, not just those with disabilities, while ensuring AI is guided by intentionality rather than assumptions.
Key Takeaways:

• AI interfaces often fail to meet accessibility needs due to their reliance on non-inclusive web data, necessitating intentional design and research to address these gaps.

• Inclusive design begins with extending existing personas to consider visual, motor, and cognitive disability dimensions, enabling more effective accessibility solutions for diverse user needs.

• Authentic user research with assistive technology users and accessibility-focused acceptance criteria are critical for creating AI-driven experiences that are both functional and equitable.

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