Reference no: EM133770975

Artificial Intelligence for Business

Assessment 1 - Problem Solving

This document provides you with information about the requirements for your assessment. Detailed instructions and resources are included for completing the task. The Criterion Reference Assessment

Learning Outcome 1: Analyse the various types of AI and evaluate their potential applications in different business contexts.
Learning Outcome 2: Apply data pre-processing techniques to prepare data for use in machine learning models and evaluate the impact of these techniques on model performance.

Task description In this assessment, you will create a strategic AI plan to address customer churn for Gigantic Telco Ltd, a leading telecommunications company. Using the provided "Telco Customer Churn" dataset, you will identify the key factors contributing to customer attrition and propose AI-driven solutions to enhance customer retention.
This assessment is designed to bridge the gap between theoretical AI concepts and their practical application in a real-world business scenario. It aims to develop your critical thinking and problem-solving skills, equipping you with industry-relevant expertise and the ability to apply AI strategically within a business context. By completing this task, you will advance your digital literacy and research skills, aligning with USQ's Graduate Attributes, and prepare yourself for future professional roles where AI is increasingly integral to decision-making processes.

Task details

Overview:
Artificial Intelligence (AI) has become a transformative force across various industries, enabling organisations to solve complex problems, make data-driven decisions, and enhance their competitive edge. As future business leaders, understanding how to analyse, plan, and implement AI solutions is crucial. This assessment is designed to introduce you to the practical application of AI in a real-world business context, focusing on the critical stages of problem identification, data preparation, and strategic decision- making.

Scenario:
Gigantic Telco Ltd, a large telecommunications company, is facing a challenge with customer retention. In a highly competitive market, the company's management has identified customer churn as a key issue that needs to be addressed to maintain profitability and growth. Gigantic Telco Ltd has decided to leverage AI to predict which customers are likely to churn, allowing them to proactively design strategies to retain these customers.

To support this initiative, Gigantic Telco Ltd has collected a comprehensive dataset that includes customer demographics, account information, the services they have subscribed to, and customer feedback from surveys. The company's leadership team has tasked you with exploring how AI can be utilised to address this challenge and improve customer retention.

subscribed to, and whether they have churned. It provides a realistic scenario for applying AI in a business context and will serve as the basis for your analysis and planning.
Your insights and recommendations will contribute to Gigantic Telco Limited's decision- making process, helping the company harness the power of AI effectively and ethically. This assessment not only tests your understanding of AI concepts but also challenges you to think critically about their application in a dynamic business environment.

AI Analysis and Application
Identify two different types of AI that could be used to address the business problem of customer churn at Gigantic Telco Ltd (e.g., machine learning for churn prediction, natural language processing for analysing customer feedback).
Analyse the strengths and limitations of each AI type in the context of Gigantic
Telco Limited's goals and challenges.
Suggest which AI type is more suitable and justify your choice with specific references to the scenario and potential business outcomes.

Report: A 350-word analysis discussing the potential application of AI types in the given scenario, addressing CLO1.

Data Preprocessing and Critical Analysis
Review the "Telco Customer Churn" dataset and evaluate whether the existing data is sufficient for building an effective AI model. Consider the completeness, relevance, and quality of the data.
Identify key data preprocessing techniques that should be applied to prepare the data for analysis (e.g., handling missing values, normalisation, feature selection). Discuss why these techniques are necessary.
Critically assess whether additional data might be needed or if certain data modifications are required to improve the model's performance. Provide suggestions for additional data sources or modifications that could enhance the predictive accuracy.
Plan the input and output structure of a machine learning model, detailing what features (inputs) would be used and what the expected outputs would be.

Report: A 350-word analysis that includes:
An evaluation of the dataset's sufficiency for the AI task.
A brief overview of the suggested preprocessing techniques.
A critical assessment of any data gaps or the need for additional data.
A proposed input and output structure for the machine learning model, addressing CLO2.

Data Interpretation and Recommendations
Based on your planning and analysis, provide recommendations for Gigantic Telco Ltd on how to implement the AI model to reduce customer churn.
Discuss how the preprocessing steps and the planned AI model could be adapted for use in other business contexts.

Report: A 150-word recommendation that provides actionable insights and generalises the planning to broader business contexts.