Generative AI in Consulting – A fictitious case study

This case study examines the growing use of Generative Artificial Intelligence (GenAI) in management consulting and highlights the risks that arise when AI-generated outputs are used without adequate human oversight. Consulting firms increasingly adopt GenAI tools to accelerate report development by automating tasks such as research synthesis, data analysis, drafting report sections, and generating visual elements including charts, diagrams, and market forecasts. While these technologies improve efficiency and reduce project timelines, they also introduce challenges related to accuracy, transparency, and professional accountability. The case focuses on a fictitious consulting firm, Alpha Consulting, which used GenAI extensively to develop a market entry strategy report for its client, RetailCo. Although the report was delivered quickly, the client identified several issues, including fabricated references, inconsistent market statistics, generic analysis, and AI-generated images that did not meet consulting standards or reflect the client’s context. As a result, the client questioned the credibility of the report and refused to pay the consulting fee. The case highlights the socio-technical challenges associated with AI-augmented knowledge work and emphasizes the importance of AI governance, human validation, and contextualized visualizations. It argues that responsible adoption of GenAI in consulting requires strong quality control processes, transparent communication with clients, and careful integration of realistic, data-driven visual elements to maintain trust and professional integrity.

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Which IT roles will AI automate most

Specific IT roles are likely to be replaced with the advent of generative artificial intelligence. We wanted to undertake a brief survey of which roles are likely to be more impacted and hence, professionals in these roles should look into reskilling their portfolio and competency. Reskilling in AI/ML use could be a way to strengthen competency within this area itself.

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Case Study: Re-Architecting an IT Services Firm for AI-Native Software Engineering

Case Study: Re-Architecting an IT Services Firm for AI-Native Software Engineering

This fictitious case study examines the multi-year strategic transformation of NovaTech Solutions, a global IT services enterprise, as it repositions itself from a traditional labor-arbitrage model to an AI-augmented and AI-native software engineering organization. Confronted with margin compression, automation-driven competition, and client expectations for exponential productivity gains, NovaTech’s leadership initiated a comprehensive enterprise transformation centered on AI-assisted coding, AI-enabled DevOps, and advanced AIOps infrastructure. Over a three-year horizon, the company restructured operating models, redesigned performance metrics, recalibrated talent strategy, and invested heavily in AI tooling and cloud infrastructure. The transformation created measurable productivity improvements and margin recovery, yet introduced complex cultural, technical, and governance challenges. Individual contributors grappled with identity shifts and skill displacement anxieties, while managers struggled to redefine productivity metrics and performance systems. Integration challenges across legacy systems and toolchains proved more demanding than anticipated. DevOps pipelines required architectural reengineering, and AIOps deployment introduced model drift, alert fatigue, and operational risk considerations. This case provides a comprehensive examination of the organizational, technical, financial, and strategic implications of enterprise-scale AI adoption in IT services.

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FinAxis Technologies: A Case about Migrating from Monolithic ERP to Microservices in a Regulated Fintech Environment

FinAxis Technologies: A Case about Migrating from Monolithic ERP to Microservices in a Regulated Fintech Environment

Note: This is a hypothetical case study for classroom discussion in the course Management Information Systems. The objective is to teach students learn about cloud computing ERP and challenges in emerging models of ERP adoption in enterprise applications. This is not a real case study.

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Case Study: The Silent Signal—Addressing the Talent Exodus at NexaConnect Telecom

Case Study: The Silent Signal—Addressing the Talent Exodus at NexaConnect Telecom

I. The Context of Stagnation: A Cultural and Technical Autopsy

To understand why employees are leaving NexaConnect, one must first understand the “Telco Trap.” For decades, telecommunications companies operated as protected monopolies or oligopolies. Success was defined by uptime, regulatory compliance, and massive capital expenditure (CAPEX) in physical hardware. At NexaConnect, this history created a “Fortress Mentality.”

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What is Prompt Engineering: An overview

Prompt engineering refers to the practice of designing and structuring inputs to large language models so that they produce accurate, useful, and reliable outputs. As language models have grown more capable, the way prompts are written has become an important skill, blending aspects of linguistics, logic, and problem formulation. Over time, several distinct types of prompt engineering have emerged, each suited to different tasks and levels of model guidance. The following discussion presents the main types of prompt engineering in an essay-style narrative, with an example woven into each explanation.

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What is a Large Language Model for a Chatbot | TechMadeSimple

Generative artificial intelligence is the talk of the town, and everybody wants to know what is large language models that powers the generative artificial intelligence chatbots. However, understanding generative artificial intelligence requires a very technical understanding of deep learning models.And most of the time, practitioners were not coming from a computer science background are unable to understand what it exactly is. We try to simplify the tech for non tech users and have found a very nice video which does the same.

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4 Features of 5G Technology Explained

4 Features of 5G Technology Explained

The fifth generation of wireless technology marks a turning point in how devices talk to each other across networks. As this technology spreads across the globe, understanding its core mechanisms becomes increasingly vital for businesses and everyday users alike. This new wireless standard represents a fundamental shift in network architecture, capabilities, and potential applications.

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Why Tracking Near Misses Is Just as Important as Reporting Accidents

Why Tracking Near Misses Is Just as Important as Reporting Accidents

Workplace safety programs traditionally concentrate on recordable injuries and accidents. While this focus is necessary for compliance and immediate response, it often overlooks a rich source of preventative data: near misses. These events, which could have caused harm but did not, provide critical insights into operational risks. Ignoring them means missing valuable opportunities to prevent future accidents before they happen.

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