Introduction

Gen Z, typically defined as those born between 1997 and 2012, are entering the workforce with distinct values and expectations. Contrary to misconceptions about their work ethic, Gen Z professionals are capable of taking responsibility and ownership of their work. However, their learning styles differ from previous generations, requiring innovative approaches to mentoring and training.

3. Problem Statement

1. Traditional methods of mentoring Chartered Accountants (CAs) are often ineffective for Gen Z professionals.
2. This generation prefers real-time feedback, interactive learning, and technology-driven processes. They also value work-life balance and purposeful engagement.
3. Conventional systems frequently fail to address these preferences, leading to communication gaps, reduced accountability, and disengagement.
4. These challenges can hinder productivity and delay the development of future-ready professionals.

4. AI Solution Overview

A web-based AI-powered application has been developed with the following features:

1. Role-play simulations powered by OpenAI's GPT API.
2. Natural Language Processing (NLP) to enable conversational interaction.
3. Real-time evaluation using rubrics with multi-dimensional scoring: completeness, depth, relevance, and practicality.
4. Personalized feedback, highlighting strengths, identifying gaps, and recommending improvements.
5. Instant query resolution using AI-assisted support.

5. Workflow

a. Input:

1. Standardized questions and evaluation rubrics stored in a MySQL database.
2. User responses submitted via the web interface.
3. Secure API authentication for safe access.

b. Processing:

1. Question selection from a pre-defined bank.
2. User response submission through the frontend.
3. AI evaluation against rubric criteria using GPT.
4. Secure API communication between frontend and backend.

c. Output:

1. Detailed multi-dimensional scoring (completeness, depth, relevance, practicality).
2. Strengths and improvement areas.
3. Analysis of missing or underdeveloped points.
4. All evaluation data stored securely in the database.

6. Application Architecture

1. Frontend: HTML, JavaScript, and CSS.
2. Backend: Python with Flask for route management, session handling, and processing.
3. LLM Integration: OpenAI GPT-3.5 Turbo via API for NLP.
4. Database: MySQL for persistent storage.
5. Deployment: Hosted on Heroku.com.
6. Security: Uses secure API keys and controlled access to rubrics and evaluation logic.

7. Conclusion

1. Effectively addresses the evolving mentoring needs of Gen Z Chartered Accountants.
2. Standardizes the assessment of audit and professional knowledge.
3. Delivers immediate, actionable feedback to promote learning.
4. Maintains structured records for training audits and progress tracking.