AI-Powered Recruitment Portal

Stage 1. Usability Audit

Before designing the new AI-driven recruitment portal, I conducted a usability audit to identify pain points in existing hiring tools and workflows.

The goal was to understand how recruiters interact with current systems, where inefficiencies occur, and how AI could improve the experience.

Key Focus Areas:

1. Navigation & Information Architecture – Are recruiters able to find key information quickly?

2. Efficiency & Task Completion – How much time do recruiters spend on repetitive tasks like scheduling interviews or formatting CVs?

3. AI Integration & Usability – Do existing AI-powered features add value, or are they underutilised due to complexity or inaccuracy?

4. Candidate Pipeline Visibility – How clear and intuitive is the current hiring pipeline for tracking candidates?

5. Data & Insights Accessibility – Can recruiters easily access and interpret hiring metrics and statistics?

Research Methods:

• User Interviews: Conducted sessions with recruiters to understand their daily workflows and challenges.

• Heuristic Evaluation: Assessed existing recruitment tools for usability flaws, friction points, and inconsistencies.

• Competitor Analysis: Reviewed other AI-powered hiring platforms to identify best practices and industry standards.

• Analytics Review: Examined usage data from current tools to detect bottlenecks and underused features.


Key Findings:

• Recruiters often struggle with manual data entry and CV formatting, which slows down hiring.

• The candidate pipeline lacks clarity, making it difficult to track progress.

• Scheduling work interviews is time-consuming, with back-and-forth emails delaying the process.

• Recruiters need real-time insights on hiring trends but find current dashboards overwhelming.

Stage 2. Design Strategy

With insights from the usability audit, I developed a design strategy focused on streamlining the hiring process, improving AI adoption, and enhancing recruiter efficiency. The strategy centered on creating an intuitive, data-driven, and AI-powered platform that reduces manual work and enhances decision-making.

Design Goals:

1. Simplify Workflow Efficiency – Reduce recruiters’ manual tasks by automating scheduling, CV formatting, and candidate tracking.

2. Enhance AI Usability & Trust – Design AI-driven features that feel reliable, transparent, and easy to use.

3. Improve Pipeline Visibility – Create a clear, Kanban-style workflow for tracking candidates at different hiring stages.

4. Optimize Data Accessibility – Design dashboards that present key hiring metrics in a digestible format.

5. Seamless Integration with Existing Tools – Ensure compatibility with LinkedIn, applicant tracking systems (ATS), and email platforms.


Key Design Decisions:

• Kanban-Based Hiring Pipeline: A visual, drag-and-drop interface for recruiters to track candidates from “applied” to “hired.”

• AI-Powered Quick Search: A natural language search allowing recruiters to find the best position match for a candidate instantly.

• Automated AI Interview Scheduling: A system that suggests optimal interview slots and facilitates AI-avatar-led interviews.

• CV Auto-Formatting: A feature that transforms raw text resumes into company-branded CVs.

• Data-Driven Dashboard: A customisable analytics hub displaying key hiring trends, recruiter performance, and candidate insights.

Stage 3. Prototype Development

• Wire-framing: To establish a clear information hierarchy and user flow, I started with low-fidelity wireframes. These wireframes mapped out the key functionalities, such as the Kanban-style hiring pipeline, AI-powered search, and automated interview scheduling. The focus was on simplifying navigation and ensuring that recruiters could efficiently access essential features with minimal effort. By conducting early usability tests with recruiters, I refined the wireframes based on their feedback, ensuring that key interactions felt intuitive before moving into high-fidelity design.
  
  

• High-Fidelity Prototyping: After finalising the wireframes, I developed interactive high-fidelity prototypes to simulate real user interactions. This included designing clickable AI-driven features, such as instant job matching and automated CV formatting, to test their effectiveness in real-world scenarios. The prototype also incorporated recruiter dashboards with real-time hiring metrics to validate how easily users could interpret and act on data insights. Usability testing with recruiters helped refine the workflow efficiency, ensuring that AI automation seamlessly enhanced, rather than complicated, the hiring process.
  
  

• User Interface Design: The UI design focused on creating a modern, clean, and recruiter-friendly aesthetic. I selected a minimalist color palette with clear visual hierarchies, ensuring that critical data—such as candidate status, interview schedules, and AI recommendations—stood out. I also incorporated micro-interactions to enhance usability, such as smooth drag-and-drop functionality in the hiring pipeline and animated feedback for AI-driven actions. Accessibility was a priority, ensuring that text, buttons, and interactive elements met WCAG guidelines for inclusivity. The final UI design balanced functionality and aesthetics, making the platform both powerful and easy to navigate.