Designing with AI | Kenna Pezzi

Prototype Design in Figma, User Research with Data Analysis, Independent Study

The rise of artificial intelligence (AI) has opened new avenues for improving efficiency and innovation across industries. In user experience (UX) design, AI tools offer significant potential to transform traditional methods by streamlining processes such as user discovery, ideation, prototyping, usability testing, and data analysis. While prior research has demonstrated AI’s capacity to assist designers, the direct impact of AI-driven design on the end-user experience remains underexplored.

Goal

Evaluate the effectiveness of AI-driven design from the user experience perspective. Assess whether AI integration improves task efficiency, ease of use, and overall satisfaction with app interfaces.

Design Selection

During my own job search, I experienced firsthand the overwhelming and time-consuming nature of the application process. Customizing resumes, writing tailored cover letters, and navigating inefficient platforms often felt frustrating and discouraging. These challenges inspired me to design an app that streamlines the job application process, helping users save time, stay organized, and feel more confident in their efforts. By addressing these common pain points, I aimed to create a tool that empowers job seekers to focus on showcasing their skills rather than battling application hurdles.

User Research

Study of Blogs

I analyzed several Reddit posts to understand how people apply for jobs and their frustrations with the process². This approach allowed me to quickly gather diverse insights from a broad range of experiences. Key takeaways include:

Time-intensive process: Many applicants report spending an entire day applying to just 5-10 jobs due to the time-consuming nature of customizing resumes, writing cover letters, and navigating inefficient application platforms.
Organized tracking methods: Many applicants use Google Sheets to track job applications, including details like role titles, application dates, and salary information. Color coding is commonly used to highlight application status, helping users stay organized and manage follow-ups efficiently.
ATS Reliance: Employers often rely on automated applicant tracking systems (ATS), making ATS compatibility essential.
Keyword Optimization: Resumes should be tailored with relevant keywords to improve ATS recognition.
Current Inefficiencies: Workday is frequently criticized for requiring manual data entry instead of importing resume details.
Emotional toll: The repetitive, time-consuming nature of job applications can lead to frustration and burnout, making strategies for maintaining motivation and mental well-being valuable.
Automation tools help: Applicants frequently use tools like resume builders, keyword optimizers, and job-tracking platforms to streamline the process and improve application quality.

Personas

The insights gathered from Reddit user research informed the development of personas that represent the primary user groups. These personas encapsulate the frustrations, goals, and behaviors of users, enabling a more targeted design approach that addresses their specific needs and pain points.

George’s struggles with tracking applications and feeling overwhelmed mirror the insight that many applicants lose track of their progress and feel unsure about their qualifications.
Maeve’s need for efficiency aligns with the insight that job seekers often want faster application processes and timely role notifications.
Richard’s focus on selective job searching reflects the insight that experienced professionals often prioritize roles with better pay and improved benefits.
Sonia’s experience of applying to hundreds of roles without success mirrors the frustration many users expressed about sending numerous applications with little to no response.

User Journey

A user journey for Maeve was designed following best practices outlined by Nielsen Norman Group to ensure it effectively guided the prototype’s development. Journey mapping is a powerful tool for understanding a user’s experience, uncovering pain points, and identifying opportunities for improvement ¹. By visualizing Maeve’s process step by step, the journey map provided a clear narrative of her frustrations, emotions, and goals to inform targeted design solutions.

Summary of Findings

Streamlined Job Search Process: Maeve’s initial success with LinkedIn’s filtering system demonstrated that effective search filters can help users quickly find relevant roles. The prototype reflects this by incorporating robust filtering options to save users time.
Reduced Sign-In Barriers: Maeve’s frustration with forgotten passwords and time spent recovering accounts underscored the need to minimize login obstacles. The prototype incorporates options like guest applications and improved password recovery to simplify this process.
Enhanced Autofill for Faster Applications: Maeve’s experience with Workday’s unreliable auto-fill feature revealed the need for improved data import capabilities. The prototype enhances this by offering a resume parsing tool that accurately extracts information to reduce manual entry.
Resumé Customization Support: Maeve’s time-consuming effort to tailor her resume emphasized the need for an efficient way to modify resumes for different roles. The prototype should introduce automated resume suggestions that highlight relevant skills and experiences based on job descriptions.
Progress Tracking for Motivation: Maeve’s disappointment after completing only one application instead of her intended three demonstrated the need for better progress visibility. The prototype should include a dashboard that tracks completed applications, estimated time spent, and pending tasks to keep users motivated.

Competitive Analysis

Through my research of blog posts, I identified three job search apps, Teal, JobScanner, and EarnBetter, for competitive analysis. I evaluated these platforms by performing key user tasks: registration, job searching, and job application. This analysis revealed several important features to prioritize for a positive user experience in my design:

Incorporate Stronger AI Integration: Utilize AI to generate resume content, suggest relevant skills, and analyze job descriptions.
Prioritize Automation: Features like auto-tracking viewed jobs, reminders, and autofill tools can significantly improve efficiency.
Improve User Guidance: Adding features like “match rate” scores, skill recommendations, and resume feedback can empower users.
Streamline Navigation: Fixed navigation, improved document organization, and clear visual indicators for application progress can reduce user frustration.
Support Portfolio Integration: Including portfolio compatibility would address a key gap in many existing platforms.

User Flows

User flows were instrumental in this project as they provided a structured way to visualize user journeys and identify key points for improvement. By outlining each step a user takes, I was able to anticipate potential challenges and ensure that design decisions aligned with user needs. This guided the development of efficient, intuitive prototypes that improved task clarity and minimized friction in key processes.

This flow assists users in refining their resumes and improving their job match score. Users can modify job descriptions and skill sections based on system recommendations to better align with desired roles. Real-time feedback and visual indicators highlight changes, ensuring users can track improvements easily.

The registration flow streamlines account creation by offering both manual entry and resume upload options. Uploading a resume allows the system to auto-fill details, reducing manual input. Users can customize job alerts and preferences, improving personalization while maintaining a structured experience.

The job search flow supports intuitive exploration of opportunities by allowing users to apply structured filters or explore listings freely. A dynamic match score evaluates the alignment between the user's resume and the job posting, offering insights into areas for improvement. This guided yet flexible approach enhances the job search experience.

Human-Designed Prototype

The human-designed prototype addresses common job seeker frustrations by emphasizing clarity, guidance, and user control. The registration flow minimizes manual entry by offering both resume uploads for data extraction and manual input options.

Users can customize job preferences and alerts to manage notifications efficiently. The job search flow combines structured filters with flexible browsing, while a dynamic job match score helps users assess their resume's alignment with listings. The application flow provides real-time resume feedback, suggested improvements, and a clear progress tracker to support users in refining their materials efficiently.

AI-Designed Prototype

🚧 This project is still under construction!🚧

The AI-assisted prototype will leverage generative AI tools to create layout structures, optimize visual hierarchy, and enhance features for a similar application. Key design choices will be evaluated through comparative usability testing against the human-designed prototype.

Additional findings, visual updates, and refined prototypes will be added as the design process continues.

Exploring the Impact of AI-Driven Design on User Experience

Kenna Pezzi