UX Design for Enterprise: Why It’s Also Fundamental for AI-Based Tools

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In this article, we explore the universe of Enterprise UX, explaining why user-centered design is the invisible pillar upon which successful digital products are built, especially in the era of Generative AI.

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What is Enterprise UX?

Enterprise UX refers to the design of digital products and services for internal business use (B2B), meaning the end users are the employees of an organization rather than the general public.

This specific context of use adds new challenges to the design process: The final product has to be intuitive, simple and easy to use. It must simplify the workflow and enhance the users’ efficiency instead of adding complexity.

In other words, it should help the employees focus on getting their job done.

A well executed UX design helps employees dedicate more time to their primary responsibilities, boosts productivity and, most importantly, improves business outcomes. 

Key Aspects of UX for Enterprise

The typical UX design process follows the Design Thinking methodology (Empathize, Define, Ideate, Prototype, Test and iterate as needed), and the enterprise context is no different. 

The Design Thinking process

However, in the B2B context there are a few points to focus on: 

• Enterprise vs Consumer UX: Enterprise UX is complex and significantly different from consumer UX. While the end goal (creating an optimal user experience) is the same, the enterprise world requires specialized knowledge of the organizational context, the different user roles, and the company’s workflows. Unlike consumer products, enterprise UX often operates within strict constraints imposed by legacy systems, data security policies, and the necessity for integration with other complex business tools.
  
  
• Working Closely With Users: Collaboration is a key element in enterprise UX, given that multiple departments and roles tend to be involved in workflows and decision-making. In enterprise, there are typically three distinct user types: the end-user (who performs the task), the manager/approver (who reviews and decides) and the administrator (who sets up and maintains the system). As a result, it’s important to involve diverse user groups in the design process to understand their specific goals and the challenges they face. Such involvement is often done through co-designing sessions, interviews, and testing.
  
  
• Leverage UX Patterns and Best Practices: Since our main goal is to facilitate the use of the product as much as possible, it’s good practice to avoid "reinventing the wheel" with the design and instead adopting standard and familiar patterns. For example, UI elements like navigation, filters, and search should use established patterns that are already intuitive for users. Another best practice when designing products that are complex and rich with data is to start with a clear, high-level overview and allow users to drill down into detailed data as needed. This layered approach allows for easier navigation and supports faster decision-making.
  
  
• Tests and Iterations: Testing the solution during the design process is highly important, and becomes even more crucial for large international organizations where end-users work across different countries. This is why we aim to select users from various global areas and roles when conducting usability tests, ensuring that the product works effectively across diverse workflows, cultures, and levels of digital maturity.

Designing AI-Based Tools for Enterprise

Today, AI-based products' popularity is on the rise in the enterprise world and organizations adopt them in order to streamline workflows and help their employees be more efficient and accomplish tasks faster and easier than ever before.

As a result, a solid UX foundation is crucial and the principles outlined above must become non-negotiable. An additional focus must also be put on trust and explainability. Even with advanced technologies like GenAI, a poor user interface -- or one that doesn't adequately explain its workings -- can lead to mistrust, low adoption, and failed implementation.

For instance, when integrating GenAI conversational interfaces, we can adopt established mental models used in popular tools like ChatGPT and Gemini. This leverages users' existing familiarity with the conversational format, prompt engineering, and iterative refinement to reduce friction and accelerate adoption.

Design must also prioritize human oversight and effective error handling, providing clear mechanisms for users to review, edit, or override AI-generated outputs, ensuring the employee remains in control of the critical business workflow.

Conclusion

In Enterprise UX, success can be measured by improved employee efficiency and productivity, business outcomes, and system adoption rate. By prioritizing good design, organizations can not only improve daily workflows for their employees but also maximize long-term business success.