Keylime Interactive
AI Opportunities in Professional Upskilling
Experience Studio Project
Overview
In today's rapidly evolving job market, upskilling, or 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.
5 Key Opportunities
Discovered from research
5 Concepts
Translated to mid-fidelity prototypes
Timeline
Aug - Dec 2025
Key Areas
UI/UX Design, Research, AI tools, Prototyping, Usability Testing
Team
7 UX Designers
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.
This leads to
Design Question
How can AI be leveraged to create upskilling solutions that are effective, trusted, and address the nuanced needs of both students and professionals?
Project Goals
Communicate findings after investigating AI and upskilling, and exploring opportunities into where and how they intersect
Based on findings, design and iterate possible solutions combining AI and upskilling into mid fidelity prototypes
Approach
Research
This phase aimed to establish a foundational understanding of AI in the context of upskilling. This phase included secondary research, a comparative analysis of existing platforms, user surveys, and 12 interviews.
Guiding Questions
What are the core user needs and pain points in upskilling?
How do AI tools currently support or hinder progress toward user goals?
Goals
Develop a comprehensive understanding of AI and Upskilling tools
Analyze existing solutions in the market
Identify user motivations and pain points in the upskilling process
Secondary Research
Literature Review
I looked into traditional upskilling. I started by only researching academic articles however I learned that user opinions on sites like Reddit is a good resource to gather a wider swath of data.
Comparative Analysis
To gain insight into the tools that are currently available, we conducted a comparative analysis. I researched career coaching platforms that provide upskilling resources with features that include artificial intelligence.
Specialized Learning
Learning Systems
Skill Development
Career Coaching
SWOT Analysis
This analysis helped evaluate the effectiveness of existing AI-driven upskilling solutions, pinpoint gaps, and explore areas for innovation and improvement.
Primary Research
This sprint utilizes interviews and a survey. The interviews allow the collection of deep qualitative while the survey will allow the collection of quantitative data about our most available user group.
Survey
We did not get a representative sample from our target population to make solid claims. However, I learned that we can still leverage the data collected to explore them further with secondary research. The survey also provided possible contacts for interviews with an incentive.
Interviews
The team conducted 12 interviews in total to understand the role and perception of AI and key pain points in upskilling. I interviewed an upperclassman and a experienced professional.
Key Research Insights
01
Human Interaction is Essential: The most valuable learning experiences involve mentorship, peer collaboration, and direct feedback from managers. AI wasn't seen as a replacement.
02
Low Trust in AI for Critical Tasks: Users were comfortable using AI for basic, repetitive tasks but were highly skeptical of its ability to provide feedback, evaluate work, or teach topics.
03
Lack of Structure is a Major Barrier: Both students and professionals struggle with knowing what to learn. Current AI recommendations are too generic.
04
Soft Skills are Underdeveloped: A significant gap exists in developing crucial soft skills like communication and leadership through digital tools.
05
Practical Experience > Certifications: Hiring managers and professionals value hands-on, real-world project experience far more than certificates from online courses.
Opportunity Exploration and Ideation
The research phase revealed that a single one-size-fits-all platform would be ineffective. Instead, the team decided to focus on key opportunity areas and design targeted, AI-powered features. The goal was not to replace human interaction, but to enable it.
Guiding Question
How can we use our synthesized research to define our opportunities and ideate on potential solutions?
Goals
Define opportunities we identified through both primary and secondary research.
Ideate potential solutions to these opportunities.
Sketch initial low-fidelity solutions that addressed our gaps.
Identifying Gaps
Identified gaps and opportunities for ideation:
Crazy 8's Workshop
Each member of the team took a gap and drew one sketch per minute for 8 minutes. We put our sketches on our FigJam and voted via star stickers on the ideas/sketches that we determined the best. Three of my sketches were chosen.
User Feedback and Iteration
Taking our low-fi sketches, we looked for feedback through value proposition and usability testing. Sketches were translated into wireframes and to mid-fidelity prototypes.
Guiding Question
How can we use our previous insights and ideation to create and verify AI in upskilling solutions?
Goals
Gain feedback and insights on sketches through user testing.
Test, refine, and further iterate sketches.
Value Proposition and User Testing
Value Proposition Testing
Chosen sketches were presented to our user groups to gather quick qualitative and quantitative data. Concepts that scored the highest and new concepts generated from insights were refined.
User Testing
Refined and new concepts were presented again. Highest scored concepts were translated into mid-fidelity. I generated the highest scoring concept.
Final Solutions
AI Job Simulator
This feature addresses the need for practical experience. It assigns users realistic, task-based projects that mirror real-world workflows. Users "learn by doing" in a simulated professional environment, building a portfolio of tangible work.
AI Mock Interviewer
This tool focuses directly on soft skill development. Users can practice for interviews and receive real-time, AI-driven feedback on metrics like tone of voice, vocabulary, and response clarity, helping them build confidence and job-readiness.
AI Feedback Dashboard
To solve the problem of unstructured growth, this tool would integrate with performance reviews. It uses AI to analyze and summarize feedback from managers and peers, identifying strengths and weaknesses. It then generates a personalized "roadmap" with links to specific internal company resources, giving employees a clear, actionable path for improvement.
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.
Reflections
Importance of Research
This was my first exploratory, research-heavy project. I was slightly hesitant when I started this project since I wasn't well-versed in UX research. However, that meant that I had an incredible amount that I would be able to learn. I was very lucky to have great mentors in the team, where I learned so much by asking questions. I was exposed to many different research methods, where I learned how to preform them, what is gained from them, and why we preform them. Research provides the foundation for every project, it gives a starting point of validation for ideas.
Key learnings:
UX research is the process of replacing assumptions with objective evidence. It ensures that every design is backed with data-driven decisions in response to user needs rather than a speculative guess.
Scope
As an exploratory project, our direction was always changing. Our team really struggled with scope. We had started with the extremely broad subjects of both upskilling and AI. Everyone learns in life, what user group should we focus on? There are so many ways to utilize AI, what ways are we going to use it? These questions kept our scope incredibly big, and therefore there was a lot to research. As we went on, the team had to come together to make decisions to scope down. We realized that by trying to design for everyone, we were in danger of designing for no one. Ultimately, we learned that defining what the project wasn't was just as important as defining what it was, allowing us to transition from continued blind research to a focused direction.
Key learnings:
A project’s success is defined more by its focus than its features. In order to create a great solution, you must be willing to narrow the scope and solve one problem well instead of several problems poorly.
