AI Client Assistant | Ui Designer

New Adventures to Solve

I had the amazing opportunity to pioneer the new AI Client Assistant from scratch as the UX/UI Designer. Our main objective was to reduce the client's time spent posting jobs, pulling reports and searching for data by 30%.

We wanted to create an AI assistant that would allow clients to ask questions about information within the application and provide accurate answers within the perimeters provided. Our first iteration was to create UI concepts for FAQ functionality, while working on the AI tone of voice.

Research & Discovery

If clients find the AI assistant easy to use and helpful with accurate information, it will be their "go to" in completing their tasks and reduce their overall time.

Understanding the User

I reviewed current user personas for the talent management product, I identified the different types of users who would be interacting with our AI Client Assistant product and updated information about the needs, goals, and pain points of these users; establishing detailed AI profiles of each user persona. These personas were then used to guide the design and development of the talent management product, ensuring that it meets the needs of our target audience.

Understanding the User & Problem

Workflows

I created workflows for each task the personas took, and it played a crucial role in ensuring that everything step ran smoothly. We were able to easily track progress, identify bottlenecks, and make adjustments to optimize efficiency.

Posting a New Job
Clinician Extension Requests
Evaluating & Downloading Candidate Documents
Reviewing Clinician "Start/Stop" Dates
Adding New Users to User Maintenance
Investigating Financial Reports for Facilities
Analyzing & Approving Candidates

talent -_ User Journey_edited_edited.jpg

Understanding the User & Problem

Journey Maps

Working through the different users' actions and steps for specific goals, I documented various feelings and pain points that established opportunities for our success.

Posting a New Job
Clinician Extension Requests
Evaluating & Downloading Candidate Documents
Reviewing Clinician "Start/Stop" Dates
Adding New Users to User Maintenance
Investigating Financial Reports for Facilities
Analyzing & Approving Candidates

Understanding the Problem

Timeframes

Using FullStory, I documented the average time it took the client to complete a specific task in their workflow.

In order to reach our goal of client's reduced time by 30%, each timeframe will be compared to the AI assistant's timeframe to complete the same specific task.

Ideation & Design

Starting with crazy 8s, sketches and wireframes, I researched inline and modal pros and cons, dark mode and light mode ideas, gathered my concepts and presented to my UX / UI team on other products for their feedback. After incorporating some great ideas, I worked with the Product Manager to narrow down and create high fidelity screens. I presented a story to our internal stakeholders for approval to move forward. Once we decided on a concept, I kicked off the components.

I was also tasked with creating the Tone of Voice for the AI Assistant. I documented primary and secondary words to describe our AI's personality, along with tips, guidelines, permissions and information about the AI Assistant that would be used internally by our MLabs development team on how our AI would respond and interact with users. I created a list of common questions for MVP and future questions, and then worked with the Product Manager to document responses, instructions and links that would be used.

Brainstorming & Inspiration

Brainstorm / Crazy 8s
Sketches
Wireframes
Inline / Modal Pros & Cons
Light Mode / Dark Mode Concepts
Components
High Fidelity Concepts

Tone/Voice

Through a focus group, it was determined that we wanted to be the business side of the "mullet" (business in the front, party in the back). We wanted our AI to reply / sound conversational but still straight to the point.

Primary & Secondary Communication Principles
MVP FAQ Questions and Answers
Future Questions

Concepts

After research and working through different brainstorming techniques, it became apparent that visualizing the UI would be an important task to get started on and spend time iterating the different concepts.

From inline, split screen and modal options to light mode vs. dark mode. Ultimately, a modal in a light mode UI was the path we were going to take for desktop and modal.

Usability Testing

Over 95% of our clients use desktop devices, I started to develop a prototype and gather questions, assumptions, steps and success criteria for remote usability tests. Our objective was to get feedback on the following:

Successful Task Completion: Could they locate how to get the AI modal started? Were they able to successfully ask a question? How did they feel about the response?
Critical & Non-Critical Errors
Error-Free Rate
Time on Task
Task Level Satisfaction

Lessons Learned

The most obvious constraint was AI being fairly new, so a lot of research went into best practices, but our application limitations were discovered during the journey mapping and what development could ultimately do within the back end.

We also discovered during usability testing that a link to their ultimate destination was the top priority (in addition to displaying steps on how to get there). Participants found the UI to be easy to navigate, but also had strong emotions on how the assistant was presented (your personal assistant vs. the onboarding specialist's assistant.