Project 04
Keylime Interactive
AI + Upskilling
Experience Studio Project
Keylime Interactive AI Upskilling
Designing AI-Powered Upskilling Tools for Early Professionals and Students
Project Overview
In today's rapidly evolving job market, "upskilling"—the process of learning new, relevant skills—is no longer optional. While Artificial Intelligence presents a massive opportunity to personalize and scale learning, its role is often met with a mix of excitement and skepticism. Our team partnered with Key Lime Interactive (KLI), a woman & minority-owned UX/CX agency, to research and identify opportunities in this complex space.
Experience Studio Project
UX Design
Research
AI
Timeline
January - May 2025
My Contributions
Foundational Research & Synthesis
Primary Research & User Engagement
Collaborative Ideation & Sketching
Low-Fidelity Prototyping & Testing
User Testing & Feedback Analysis
Documentation & Reporting
Design Space
Problem Statement
Professionals at all levels know they need to keep learning, but the path is often unclear. Early-career professionals feel overwhelmed by resources, while students struggle to bridge the gap between academic theory and real-world application. Companies invest in learning platforms, but these often fail to address the core human needs for guidance, feedback, and practical experience.
User Group
Upperclassmen Students
Early-Career Professionals
Research & Discovery
Our approach was a deep, multi-phase investigation to build a comprehensive understanding from the ground up. We conducted secondary research, a comparative analysis of existing platforms, user surveys, and 12 in-depth interviews across four key groups:
Upperclassmen Students
Early-Career Professionals
Experienced Professionals
Hiring Managers
Key Research Insights
Across all groups, a clear narrative emerged. While AI is seen as a useful tool for efficiency, it is not yet trusted as a teacher.
Human Interaction is Essential: The most valuable learning experiences involve mentorship, peer collaboration, and direct feedback from managers. AI was not seen as a replacement for this.
Low Trust in AI for Critical Tasks: Users were comfortable using AI for basic, repetitive tasks (summarizing, ideating) but were highly skeptical of its ability to provide nuanced feedback, evaluate complex work, or teach unfamiliar topics.
Lack of Structure is a Major Barrier: Both students and professionals struggle with knowing what to learn next. They desire clear, personalized roadmaps but find current AI recommendations too generic.
Soft Skills are Underdeveloped: A significant gap exists in developing crucial soft skills like communication and leadership through digital tools.
Practical Experience > Certifications: Hiring managers and professionals alike value hands-on, real-world project experience far more than certificates from online courses.
Ideation & Solutions
Our research revealed that a single "one-size-fits-all" platform would be ineffective. Instead, we identified key opportunity areas and designed a suite of targeted, AI-powered features that could be integrated into a cohesive upskilling ecosystem. The goal was not to replace human interaction, but to augment it.
After extensive ideation, including Crazy 8s workshops and user testing of low-fi sketches, we refined our concepts into several key features:
Design Rationale
Building Trust
`We position AI as a supportive assistant rather than an authoritative judge. It analyzes data, suggests paths, and provides practice, but the critical feedback and decision-making loops still involve humans (managers, mentors, peers).
Fostering Competence
By focusing on hands-on simulators and personalized roadmaps, our features help users build tangible skills and see their progress clearly, directly addressing the desire for real-world application.
Shopper Experience
The Feedback Dashboard and Job Simulator provide the clear guidance users are missing, while still allowing them the autonomy to choose which skills to focus on and how to learn them.
Limitations
Potential for AI Bias: Our participants were largely familiar with AI tools. This may have skewed our findings, as their perceptions might not reflect those of professionals who are less experienced or more skeptical of AI.
Limited Industry Input: As a student-led project, our access to a broad spectrum of industry professionals was limited. Deeper collaboration with more companies would be necessary to fully understand specific corporate upskilling needs.
Next Steps
Refine and Integrate Prototypes:
Develop the proposed features into a single, high-fidelity, and functional prototype to test the cohesive user journey.
Conduct Broader User Testing: Validate the solutions with a larger, more diverse user pool to ensure the features are effective and trusted across different industries and roles.
Explore AI Ethics and Feasibility:
Conduct a deeper investigation into the technical and ethical implications of implementing these AI models, ensuring fairness, transparency, and data privacy.