Exam 1- A.I.

THIS EXAM QUESTION IS BASED ON THE FOLLLOWING HBR article: “Wilson, H. James, and Paul R. Daugherty. “Embracing Gen AI at Work: The Skills You Need to Succeed in the Era of Large Language Models.” Harvard Business Review, SeptemberOctober 2024, pp. 151-155.

I. Article Summary:

The article discusses how generative AI, particularly large language models (LLMs) like ChatGPT, are transforming workplaces. Generative AI

Chatgpt, Gemini, Llama, Grok, Claude, Grok, etc.

can now be utilized by a wide range of professionals across various industries, making it crucial for workers to develop specific “Fusion Skills” ( The term comes from the idea of “fusing” human intelligence with AI capabilities to achieve better outcomes than either could alone. to effectively collaborate with AI). These fusion skills include:

1. Intelligent Interrogation: Prompting AI in ways that produce better reasoning and outcomes.
2. Judgment Integration: Using human discernment to make AI outputs more reliable, accurate, and ethical.
3. Reciprocal Apprenticing: Training AI to learn about specific business tasks while simultaneously learning from the AI.

The article emphasizes that as AI becomes more integrated into business processes, mastering these skills will be essential for professional success. Techniques like step-by-step reasoning and providing thought demonstrations can significantly improve AI output. Furthermore, ensuring AI outputs are trustworthy and free from bias is critical to leveraging AIs potential effectively. The article also highlight the importance of continuous learning and adaptation, as generative AI technologies evolve rapidly.

II. To better understand the roles that generative AI will play in reshaping the management landscape, it is helpful to consider the traditional responsibilities of middle and senior management:

• Middle management typically involves managers responsible for overseeing daily operations and managing teams or departments. They serve as a bridge between front-line employees and senior management, focusing on executing organizational policies, handling performance evaluations, and coordinating resources to meet company goals.
• Senior management, on the other hand, consists of executives such as CEOs, CFOs, and VPs, who set the overall direction and strategy of the organization, focusing on long-term goals, strategic planning, and high-level decision-making.

Below are common areas under the purview of middle and senior management, with brief definitions:

Middle Management Areas:

1. Operational efficiency and workflow management: Overseeing day-to-day processes to ensure they run smoothly and efficiently, optimizing resources, and minimizing waste.
2. Team performance and productivity monitoring: Tracking and evaluating employee performance to enhance productivity and meet departmental goals.
3. Employee training and development: Identifying training needs, facilitating professional growth, and ensuring employees acquire necessary skills.
4. Implementation of departmental strategies: Executing strategic plans set by senior management within specific departments.
5. Handling customer complaints and escalations: Managing customer issues effectively to ensure satisfaction and maintain the company’s reputation.

Senior Management Areas:

1. Organizational vision and strategic planning: Defining the long-term goals and direction of the organization, aligning resources to achieve these objectives.
2. Financial oversight and budgeting: Managing the organization’s finances, including budgeting, forecasting, and ensuring financial stability.
3. Corporate governance and compliance: Ensuring the organization adheres to laws, regulations, and ethical standards.
4. Market expansion and innovation: Identifying new markets, fostering innovation, and driving growth initiatives to maintain competitive advantage.
5. Risk management and crisis response: Identifying potential risks, developing mitigation strategies, and managing responses to crises to protect the organization.

III. QUESTION:

Read the above and the complete HBR article. Considering the advent of generative AI and its ability to automate and augment various tasks, choose two management areas from the list above (One from middle management, and one from senior management). For each of these two areas, discuss how generative AI could transform these functions by applying the three fusion skills of: a) intelligent interrogation, b) judgment integration, and c) reciprocal apprenticing. Provide specific examples to illustrate your points.

Be Original, you may use the internet, or experience from your work world. Ensure you include citation (APA style) for any of the examples or supplemental information you may have found via the general internet or the SSU library databases.

Also, please ensure that you do not give AI generated response as based on the AI Policy, you may forfeit your grade. The other real danger is that you will have added to the confirmation that you can be replaced by AI.

EXAMPLE OF THREE FUSION SKILLS IN A FICTITIOUS RETAIL SETTING:

A retail manager at a large department store is preparing to use a Large Language Model (LLM) to enhance their store’s performance during the upcoming holiday season. With access to three years of historical sales data, customer feedback, inventory records, and promotional campaign results, they see an opportunity to leverage AI for better decision-making. Having read about the three fusion skills – intelligent interrogation, judgment integration, and reciprocal apprenticing – they understand that success with the LLM will require more than just feeding it data. The manager needs to strategically interact with the AI to improve store performance while maintaining brand standards and customer relationships. Their goal is to optimize holiday promotions, product placements, and inventory management while balancing profitability with customer experience. Here’s how they implement each fusion skill:

Intelligent Interrogation: The retail manager understands that getting better outcomes from AI requires thoughtful, structured prompting. Instead of asking broad questions about Black Friday sales, they break down their inquiry methodically: “Analyze last year’s Black Friday sales hour by hour, show how early-morning doorbusters influenced later purchases, and explain the reasoning behind each significant sales spike.” When the AI responds, they dig deeper with focused follow-up questions about specific time periods, customer segments, and purchase patterns. For instance, discovering a sales spike at 9AM leads to questions about basket composition, cross-category purchases, and comparison with normal shopping days. This methodical questioning process helps the AI provide increasingly sophisticated analysis and clearer reasoning about customer behavior. The manager continuously refines their questions based on each response, building a more comprehensive understanding of shopping patterns and driving better outcomes from the AI’s analysis.

Judgment Integration: When analyzing AI recommendations, human judgment becomes crucial for ensuring outputs are reliable and aligned with business realities. For example, when AI suggests maximizing profits by moving luxury brands to the back of the store and filling front spaces with deep-discount items, the manager must evaluate this through multiple business lenses. They consider brand partnership requirements, the store’s upscale image and its impact on long-term customer value, potential damage to market positioning, staff insights about customer behavior, and the competitive landscape. By integrating these human factors with the AI’s data-driven insights, the manager develops a more nuanced solution: maintaining premium brand positioning up front while strategically incorporating value sections throughout the store. This approach makes the AI’s output more reliable and aligned with business realities while maintaining ethical considerations and important business relationships.

Reciprocal Apprenticing: The power of reciprocal apprenticing lies in its two-way learning process that develops over time. The manager begins by teaching the AI about their store’s specific context, inputting detailed data about past promotional successes and failures, local market nuances, and unique customer preferences. As the AI processes this information, it starts identifying patterns the manager hadn’t noticed – like unexpected product affinities or subtle timing patterns in shopping behavior. The manager then tests these AI-generated insights through real merchandising experiments, carefully documenting the results and feeding them back into the AI system. This creates a continuous learning cycle where each party’s capabilities grow: the manager discovers new merchandising strategies they wouldn’t have considered, while the AI’s recommendations become increasingly sophisticated and tailored to the store’s specific context. Through each iteration, both the human’s merchandising expertise and the AI’s analytical capabilities improve, creating a truly collaborative learning relationship that enhances overall business performance.

Submission Link:

Upload:

Your analysis in ‘Word”. There is no word length limit, but it would help you to organize your response to first pick the management area from the list of Middle management, then discuss the transformation by each of the three fusion skills. Then do this for the next management area of Senior Management. discuss the transformation by each of the three fusion skills. Use paragraphs and appropriate headings. Do not submit less that 3 pages, or more than 5 pages. Get straight to putting your analysis, Keep yout introduction short (1-3 sentences). Have a conclusion at the end that will basically be a “so what”.