Career Navigator
An AI-powered feature helping mid-career professionals navigate career growth, identify skill gaps, and connect with industry mentors.
Problem Statement
"How might we empower mid-career professionals to visualize and achieve long-term career growth using AI?"
Problem Background
Since the rise of AI-driven job tools, professionals now have access to job boards and networking platforms like LinkedIn. However, many mid-career professionals struggle with career transitions—they don’t know what their next step should be, what skills they need, or how to find mentorship.
Research Findings: Based on the research findings from surveys, it was discovered that 70% of surveyed professionals struggle to identify career transitions, 60% find it difficult to assess their skill gaps, and 50%+ lack mentorship opportunities.
The challenge?
There’s no AI-powered tool within LinkedIn that actively guides users through career transitions while providing personalized mentorship and job recommendations.
Research Insights
User Pain Points
Through user surveys and interviews, we identified common pain points for mid-career professionals:
- Lack of career clarity – Uncertainty about next steps and growth potential.
- Limited skill gap analysis – They don’t know which skills are required for specific roles.
- Networking difficulties – Difficulty finding mentors who have successfully transitioned into new career paths.
- Disconnected job search – Job recommendations are based on keywords, not career aspirations.
Supporting Data:
- 85% of professionals we surveyed were unhappy with the current career planning solutions available on LinkedIn and other platforms.
- Over 50% wanted a tool that integrates AI-driven mentorship recommendations.
Solution: AI Career Navigator
Landing on the Solution
To address these pain points, we designed AI Career Navigator as an extension within LinkedIn that:
- Uses AI-driven career path insights based on LinkedIn profiles.
- Analyzes skill gaps and suggests upskilling recommendations.
- Matches users with mentors who have successfully transitioned into their desired roles.
- Provides AI-powered job matching and resume optimization.
Why AI? AI allows us to generate recommendations at scale, ensuring career advice is tailored to each user’s unique background.
How the AI Career Navigator Gets Its Information
1️. User Inputs (How Users Provide Data)
When a user accesses the AI Career Navigator, they are prompted to provide key career details:
Questions Asked:
- What is your current role? (Dropdown selection based on LinkedIn profile)
- Which industries are you interested in? (Select multiple options)
- Are you considering a career pivot or growth within your field? (Yes/No)
- What are your top career goals? (E.g., “Increase salary,” “Become a manager,” “Change industries”)
- What skills do you already have? (Autofilled from LinkedIn profile but editable)
- What skills are you interested in developing? (User selects from AI-suggested skills list)
2️. AI Data Sources & How It Processes Information
- LinkedIn Profile Data
- Market Data & Job Trends
- Learning & Upskilling Resources
- Mentorship Data & Recommendations
3️. AI Decision-Making Process:
Example: A user is an HR Business Partner (HRBP) looking to transition into People Analytics.
The AI will:
- Identify transferable skills (e.g., HR Analytics, Workforce Planning).
- Compare skills to industry demand (e.g., SQL & Data Visualization are must-haves).
- Recommend certifications (e.g., People Analytics on Coursera).
- Suggest mentors who successfully moved from HRBP → People Analytics.
- Show job openings and provide resume & cover letter optimization tips.
User Flows & Mockups
- AI-Driven Career Recommendations
How it Works:
- AI analyzes a user’s LinkedIn profile (job history, skills, and interests).
- It suggests career paths based on industry trends and the user’s background.
2️. Skill Gap Analysis & Learning Recommendations
How it Works:
- AI scans target job descriptions and compares them to the user’s existing skill set.
- It highlights missing skills and suggests online courses & certifications.
3️. AI-Powered Mentorship Matching
How it Works:
- AI suggests mentors based on career trajectories similar to the user’s.
- Users can connect directly with mentors for career advice.
4️. AI-Driven Job Matching & Resume Optimization
How it Works:
- AI finds job opportunities that align with the user’s career aspirations.
- It optimizes resumes & cover letters for higher success rates.
Future Steps
Now that the AI Career Navigator prototype is live, the next steps include:
🔹 Refining AI career recommendations based on user testing.
🔹 Enhancing mentorship algorithms to improve match accuracy.
🔹 Exploring deeper integration into LinkedIn’s ecosystem.
Learnings
Product Manager Learnings:
Motunrayo Obembe
- User research is everything. Understanding user pain points led to a well-defined solution.
- AI-driven personalization matters. One-size-fits-all solutions don’t work—users need tailored recommendations.
- Prototyping & iteration drive impact. Early testing helped refine the AI’s recommendations before finalizing the solution.
This project has been an incredible learning experience in AI product management, UX research, and rapid prototyping. I’m excited to refine and expand this solution.
Designer Learnings:
Designer Learnings:
Jo Sturdivant
- Adapting to an Established Team: Joining the team in week 6 of 8 was challenging, as I had to quickly adapt to existing workflows, dynamics, and goals. This mirrors real-world situations where you often integrate into teams mid-project, and flexibility is essential.
- Work-Blocking for Efficiency: With only two weeks to complete the project, I learned the importance of a structured work-blocking system. This approach allowed me to manage my time effectively and meet deadlines under pressure.
- Making Data-Driven Design Decisions: Unlike my past projects, I had to rely on research conducted by others. This was a valuable experience in using pre-existing data to guide design decisions, helping me focus on the core insights without starting from scratch.
Developer Learnings:
Developer Learnings:
Vanady Beard
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As the back-end developer, I learned how important it is to create efficient and reliable systems that support the entire application. This experience also taught me the importance of optimising the database and ensuring the backend is scalable and easy to maintain.
Developer Learnings:
Stephen Asiedu
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As a back-end developer, I've come to understand the importance of being familiar with various database systems and modules. This knowledge enables me to build diverse applications and maintain versatility in my work. I've also learned that the responsibility for making the right choices rests on my shoulders, guided by my best judgement.
Developer Learnings:
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Developer Learnings:
Maurquise Williams
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- Process of Creating an MVP: Developing a Minimum Viable Product (MVP) taught me how to focus on delivering core functionalities balancing between essential features and avoiding scope creep.
- Collaboration in a Real-World Tech Setting: This experience taught me how to collaborate efficiently in a fast-paced tech environment, keeping the team aligned and productive, even while working remotely across time zones.
- Sharpening Critical Thinking and Problem-Solving Skills: This experience honed my ability to think critically and solve problems efficiently. By tackling challenges and finding quick solutions, I sharpened my decision-making and troubleshooting skills in a dynamic, real-world setting.
Developer Learnings:
Jeremiah Williams
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All in all this experience was very awesome I learned that in coding with others being transparent is key
Developers Learnings:
Justin Farley
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I learned how important communication is when working with a team. Communication provides understanding, advice, ideas, and much more. While working with the product team, I’ve found that communication keeps everything flowing smoothly. Working with a team also showed me that every member brings something different to the table and we all have to work together in order to align and meet our end goal.