Retrofitting an Existing B2B UI with GPT AI Functionality: UX Considerations.

In today’s rapidly evolving and fiercely competitive tech-driven business landscape, the urgency to incorporate AI and ChatGPT-type experiences into existing products is a significant challenge. This effort can be new and complex for many or all involved stakeholders.?

Understanding Design Implications: For product designers responsible for an existing domain-specific B2B application used in industries such as fintech, HR, legal, or medical, understanding the design implications of retrofitting an existing UI with Chat GPT capabilities is crucial. This understanding is key to developing a robust experience strategy and corresponding design that add high measurable value to the product’s existing and prospective client base?and end users. It also helps?designers figure out ways to manifest the non-trivial technical, legal, and business complexities involved in blending interaction modalities in the redesign.?

Key Design Implications that align well with or extend the User-Centered Design philosophy:?

• Understanding User Intent: The UI should clearly signal to the user that the chatbot has accurately interpreted the user’s language, context, and intent.?

• Quality Responses: The UI should allow the user to easily confirm?that the chatbot provided responses that are accurate, relevant, and concise. The UI should also make it easy for the user to drill further into the details and supporting references of a response.?

• Quick Responses: Users came to expect quick responses in chat interfaces. The UI should mitigate delays due to the complexity of a user’s request by allowing the user to switch to another task and easily access the response when ready, or employ some other strategy, ensuring that users are engaged and feel productive.?

• UI Integration: The chatbot should integrate well with the existing UI and maintain consistency with the overall design and user experience. If the chatbot is only relevant to a section of the product, its UI should be hidden where it is not relevant to avoid confusion and frustration. The user should be able to easily toggle the visibility of the chatbot panel when not relevant?

• Conversation management: The UI should make it easy for the user to?name, share (per permissions) and manage conversations for reuse and future continuation.??

• User Guidance: Users should be guided on how to interact with the chatbot and what kind of queries it can handle.?

• Fallback Mechanism: The UI should offer a mechanism to complete a task or workflow when the chatbot is offline, or when the user does not need or want to use it. ?

• Personalization: The chatbot's UI should provide easy control for the user to manage and further?personalize chatbot responses based on?role, past interactions, and preferences.?

• User Feedback: The UI should support fresh and compelling ways to encourage users to quickly and easily provide effective and measurable feedback on aspects of the?chatbot’s performance once the chatbot's novelty wears off. The feedback can be used for training the model, managing experience KPIs and for gaging user satisfaction. ?

• Privacy and Security: The UI should communicate in clear and easily accessible language how the chatbot follows all relevant privacy and data security regulations across various workflows, and clearly flag risks and violations. ?

The chatbot should feel like a valuable addition to the product, not a rushed marketing gimmick.?

Risk for Vendors: The risk for vendors of both nascent and well-established B2B applications is considerable. Issues with the chatbot – from concerns about handling of data in model training and normal usage, to misinterpretations of user language or intent – can lead to mistrust in the chatbot. This mistrust can potentially cascade to mistrust in the entire product and its vendor. Therefore, it is crucial to address these issues proactively, taking advantage of the expertise that UX brings to the overall effort.?