Asking perplexity to refine initial MBA proposal draft: an illustration: : on AI, BPR and insurance service (information from perplexity.ai)
My question 1: "Please refine my preliminary MBA proposal ideas based on the following initial proposal draft and my additional proposal ideas as follows:
The reply: "This is an excellent and timely topic—AI-driven digitalization is dramatically reshaping the insurance sector, and your insider perspective as an experienced sales manager adds rare practical depth. Below is a refined and academically-oriented MBA proposal draft integrating your initial ideas, preferences (pragmatism, business process re-engineering, customer engagement), and clearer structure for objectives, research issues, and methodology.
Proposed Dissertation Title
“Re-engineering Professional Roles and Customer Engagement: The Impact of Artificial Intelligence–Enabled Digitalisation on Insurance Advisers in Hong Kong”
Background and Rationale
The Hong Kong insurance industry is experiencing rapid digital transformation, with Artificial Intelligence (AI) technologies—chatbots, predictive analytics, and automated advisory systems—altering both customer interactions and back-office operations. While AI promises enhanced efficiency and data-driven decision-making, it also disrupts traditional face-to-face advisory models and challenges advisers to redefine their professional roles.
Drawing from 15 years of industry experience, this research examines how AI adoption shapes advisory practices, skill requirements, and client engagement strategies among Hong Kong insurance professionals. The study contributes to both academic literature and managerial practice by integrating business process re-engineering (BPR) and customer engagement frameworks within a pragmatic research philosophy.
Research Aim
To investigate how AI-enabled digitalisation transforms professional roles, work processes, and customer engagement strategies among experienced insurance advisers in Hong Kong.
Research Objectives
To identify how AI technologies have altered the professional roles, responsibilities, and required competencies of Hong Kong insurance advisers.
To examine how AI-driven digital tools influence advisers’ approaches to customer engagement and relationship management.
To evaluate organisational strategies (including process changes and reskilling initiatives) that support advisers’ adaptation to digitalisation.
To recommend business process re-engineering and customer engagement strategies that can enhance both adviser performance and client satisfaction.
Research Issues / Key Questions
How have AI-driven tools (e.g. chatbots, CRM systems, predictive analytics) reshaped the daily workflows and decision-making processes of insurance advisers?
What challenges do advisers face in maintaining trust and personalization in AI-supported advisory interactions?
How does AI adoption influence customers’ perceptions of service quality and confidence in digital advisory models?
What organisational changes are required to reconcile traditional human-centred advisory values with digital transformation imperatives?
Theoretical Framework
The study will be anchored on:
Business Process Re-Engineering (Hammer & Champy, 1993): to analyse how advisory workflows are redesigned through AI adoption and process automation.
Customer Engagement Theory (Brodie et al., 2011): to explore how digital technologies transform the adviser–client relationship and emotional connection.
Technology Acceptance Model (Davis, 1989): to explain the behavioural intentions and perceived usefulness of AI tools among advisers.
Pragmatism as the guiding research philosophy, allowing mixed methods to capture both measurable impacts and lived experiences of practitioners.
Research Methodology
Research Design
A mixed-methods design following a pragmatic paradigm, combining quantitative and qualitative data for comprehensive understanding.
Quantitative Phase
Instrument: Online questionnaire with Likert-scale and categorical measures.
Sample: Approx. 150 insurance advisers and managers with 7+ years of experience, primarily from XYZ Insurance Company.
Focus: Perceived impacts of AI on efficiency, job satisfaction, client relationship quality, and skill evolution.
Analysis: Descriptive statistics, multiple regression, and ANOVA (where relevant).
Qualitative Phase
Semi-Structured Interviews:
6 interviews with experienced advisers to capture role transformation, resistance, and adaptation narratives.
4 interviews with clients to explore changing expectations, trust, and perceived service value under digitalisation.
Analysis: Thematic analysis using NVivo to identify emergent themes on digital transformation, emotional engagement, and task redefinition.
Secondary Data
Reports from the Hong Kong Insurance Authority (HKIA), InsurTech ecosystem studies, and industry surveys to triangulate and validate primary data.
Expected Contributions
Practical: Provide insights for insurance companies and policymakers in Hong Kong on tailoring digital transformation strategies that maintain human-centric service.
Academic: Extend understanding of AI-driven business process re-engineering within the service and financial sectors.
Methodological: Demonstrate a pragmatic mixed-methods approach applicable to other digitally disrupted industries."
A collection of blog notes on using chatgpt for research purpose.
