AI Models in Management

MGMT

Automation of Operations at Scale

Generative AI can potentially automate up to ~70% of routine business activities by 2030, handling tasks like data entry and standard document drafting, freeing employees for complex work.

Estimated $2.6–$4.4 trillion annual global economic boost. [Source] Internal knowledge search (~60% of analyst time) can be automated. [Source]

MGMT

Content Generation & SEO

AI tools like GPT-3.5 can auto-generate web page content, summaries, and SEO-optimized text, drastically reducing content production time.

CarMax generated 5,000+ pages in months (vs. estimated 11 years manually), boosting traffic and revenue. [Source] [Source]

MGMT

Customer Service and Sales Enhancement

AI chatbots and assistants handle common inquiries, personalize responses, and support sales efforts by tailoring outreach based on customer data.

Potential for 50% automation in customer care, yielding 30–45% productivity increase. AI campaigns may lift revenues 3–5%. [Source]

MGMT

Software Development and IT Efficiency

AI coding assistants (e.g., GitHub Copilot) automate code generation, debugging, and translation, speeding up development cycles and automating routine IT support.

Boosts developer productivity by 20–45% on average. [Source]

MGMT

Automating Analysis & Decision Support

Generative AI assists in decision-making by synthesizing vast amounts of information, such as internal reports and market data, providing instant insights.

Morgan Stanley's GPT-4 tool helps specific staff analyze research (70k+ reports/yr)[Source] AI accelerates tasks in marketing, operations, R&D. [Source]

MGMT

AI as a Cybernetic Teammate

Beyond individual productivity tools, AI can function as a virtual team member, collaborating with professionals across specialties and enhancing cross-functional collaboration in product development, strategy, and other complex tasks.

P&G study showed teams with AI produced top-tier solutions and worked 12-16% faster. AI-enabled individuals performed equivalent to traditional two-person teams. [Source]

REAL

Real Estate Listings & Marketing

AI generates property descriptions, social media content, and marketing materials in seconds, saving agents significant time.

Tasks taking hours manually done in seconds. AI-generated listing led to 25 open house attendees and 10% above asking price sale. [Source] [Source]

REAL

AI-Assisted Property Search

Platforms like Zillow integrate AI (e.g., ChatGPT plugins) to allow natural language searches, making property discovery more intuitive for buyers.

Enhances user experience on major real estate portals through conversational search queries. [Source]

REAL

Property Visualization

AI generates virtual renovations and staging, allowing prospective tenants/buyers to visualize different styles and possibilities within a property.

Improves conversion rates and informs development decisions by showing popular design options. Enables furniture/appliance recommendations. [Source]

REAL MGMT

Investment Analysis & Design Automation

AI analyzes unstructured data (market reports, demographics) to identify high-potential real estate assets and generates draft floor plans or building designs optimized for specific outcomes.

Saves weeks of analyst work in identifying assets. Accelerates architectural groundwork for layouts maximizing light or optimizing traffic flow. [Source]

ENTR

Startup Ideation & Business Planning

Generative AI brainstorms venture ideas, drafts business plans, creates product mockups, and generates marketing visuals, accelerating early-stage startup processes.

ChatGPT-4 generated higher quality ideas than MBA students. Potential for 10x productivity gains in innovation. [Source]

ENTR

Rapid Prototyping and Launch

AI tools dramatically speed up experimentation and launch planning, generating business plans, websites, marketing materials, and scripts in minutes or hours instead of weeks.

Demonstrated creation of a full launch plan (9.2k words, website, etc.) in 30 minutes. [Source] Key for cheap, quick experimentation. [Source]

HRM

Recruiting and Hiring Automation

AI streamlines hiring by writing job descriptions (77% of users), drafting interview questions (66%), and interacting with applicants (65%), sometimes replacing certain HR tasks.

49% of companies used ChatGPT in Feb 2023, mostly for recruitment. 93% plan to expand AI use in HR. [Source]

HRM

Employee Communications and Training

AI "copilots" generate policy summaries, FAQs, performance review drafts, and personalized training content, improving internal HR operations and communication efficiency.

Up to 3x faster HR content creation, 50%+ automation in onboarding. 2x higher response rates with AI-personalized recruitment messages. [Source]

HRM MGMT

HR Analytics and Cost Savings

AI automates HR admin tasks (resume screening, scheduling, payroll queries) and optimizes workforce planning, leading to budget reductions and productivity gains.

Early adopter reduced HR budget by 10% YoY for 3 years. Freed 25-30% of HRBP time from admin tasks. [Source]

HRM MGMT

Democratizing Specialized Knowledge

AI helps bridge functional knowledge gaps, allowing employees to contribute beyond their specialized training. Less experienced staff with AI access can perform at levels comparable to teams with experienced members.

Research shows AI effectively eliminated traditional expertise boundaries between R&D and Commercial specialists, producing balanced solutions that integrated both technical and market perspectives. [Source]

MGMT

Global Strategy and Innovation

Tech service providers are leveraging generative AI through "use case families" - interconnected processes that deliver comprehensive business transformation rather than isolated improvements.

85% of companies rank generative AI as a top five priority, with increasing investments planned for 2024. [Source]

INTL

Multilingual Operations & Collaboration

AI tools understand and generate text in dozens of languages (95+), facilitating cross-border communication, customer service, research, and report drafting for international businesses.

PwC rolling out ChatGPT Enterprise to 100k+ employees globally. [Source]

INTL

Global Marketing & Customer Engagement

Multinational brands leverage generative AI for interactive, localized campaigns across diverse markets, allowing consumers to personalize brand experiences.

Coca-Cola used an AI card generator in 40+ markets for personalized holiday content, driving global engagement. [Source]

Recent Applications

Case MGMT

2025

Procter & Gamble's AI-Enhanced Product Development

Randomized controlled trial with 776 professionals across Europe and US
AI-enabled teams produced 39% better solutions than non-AI individuals
Teams with AI were significantly more likely to produce top 10% quality solutions
AI bridged expertise gaps between R&D and Commercial specialists

P&G's experiment demonstrated that AI functions more like a teammate than a tool, replicating core benefits of teamwork—improved performance, expertise sharing, and positive emotional experiences—while challenging traditional boundaries between specialties.

Source: Dell'Acqua, Ayoubi, Lakhani et al., "The Cybernetic Teammate: A Field Experiment on Generative AI Reshaping Teamwork and Expertise," 2025

Case MGMT

Ongoing

Morgan Stanley's AI Research Assistant

Deployed OpenAI GPT-4 powered assistant "AskResearchGPT"
Provides access to more than 70,000 proprietary research reports published annually
Enables Investment Banking, Sales & Trading and Research staff to efficiently query and summarize vast information
Synthesizes insights from multiple research products to address complex questions seamlessly

Morgan Stanley implemented an AI tool enabling institutional client-facing teams to rapidly access and synthesize extensive internal research, boosting productivity and providing higher quality service to institutional clients.

Source: Morgan Stanley Press Release

Case HRM

Ongoing

AI Streamlining HR Processes

McDonald's cut time-to-hire from 21 days to <3 days using Paradox Olivia AI
AI assistants write job descriptions, draft interview questions, screen resumes, schedule interviews
AI chatbots answer employee FAQs, generate policy summaries, draft performance reviews
Potential to reduce HR operating budgets (e.g., 10% YoY) and free up HRBP time (25-30%)

HR departments are using AI assistants like Paradox Olivia and internal copilots to automate recruitment tasks, employee communications, and administrative work, leading to significant efficiency gains, cost savings, and improved candidate/employee experiences.

Source: Paradox AI (McDonald's), Clearstar, BCG

Case INTL

Ongoing

AI Enabling Global Operations & Strategy

AI tools (DeepL) reduce internal document translation time by 90%, yielding significant ROI (e.g., 345%)
PwC deploys ChatGPT Enterprise to 100,000+ employees for global collaboration
BloombergGPT & AlphaSense analyze global financial data and news for strategic insights
Coca-Cola ran localized AI campaigns across 40+ markets

Generative AI is crucial for international management, enabling seamless multilingual communication, accelerating global strategy development through data synthesis, and facilitating localized marketing campaigns at scale.

Source: IT Brief UK (DeepL), TechCrunch (PwC), Coca-Cola

INTL Research

2024

Embracing Generative AI in International Business Research

Addresses disruption of GenAI in international business research
Notes ChatGPT catapulted GenAI to top of academic/practitioner discussions
Examines how AI changes organizing, governing, learning, and researching globally
Proposes initial guidelines ('guardrails') for using GenAI in IB research

This editorial tackles the profound impact of generative AI on the field of international business studies, discussing the disruption to traditional research practices and proposing necessary guidelines for responsible AI adoption in global contexts.

Source: Delios, Tung & van Witteloostuijn, Journal of International Business Studies, 2024

Teaching MGMT

The Expertise Paradox

Generative AI handles lower-level tasks, potentially freeing novices for complex problems, but over-reliance may impede the development of higher-order thinking skills if foundational knowledge is skipped.

Risk: AI use might stunt deeper learning. [Source: Valcea et al., 2024]

Teaching MGMT

The Innovation Paradox

AI tools can spur creativity by automating routine work, allowing focus on novel ideas. However, they might also stifle originality by convincingly remixing existing content.

AI can both inspire and inadvertently limit true originality. [Source: Valcea et al., 2024]

Teaching MGMT

The Equity Paradox

While AI might democratize information, it could widen skill gaps. Experienced users augment expertise, while less-skilled users might become overly dependent and fall behind.

Raises fairness concerns: AI might upskill experts but deskill novices. [Source: Valcea et al., 2024]

Teaching ENTR

AI in Entrepreneurship Workshop

Undergrad students used ChatGPT-3/4 as a creative partner during a 3-day business model innovation workshop, assisting with idea generation, refinement, and transformation.

LLM assistance enabled faster, more accurate business model prototyping without superficiality. [Source: Mueller-Saegebrecht & Lippert, 2024]

Teaching MGMT

AI in Managerial Communication Course

A qualitative study examined integrating ChatGPT into a graduate management communication course, performing a SWOT analysis via focus groups and netnography.

Strengths: Personalized feedback, practice dialog. Weaknesses: Reduced originality, over-reliance. Calls for reimagined pedagogy. [Source: Sharma & Pandey, 2023]

Teaching MGMT

Reimagining Pedagogy

Educators suggest weaving AI into the learning process through new types of assignments: AI-generated summaries for critique, refining AI-drafted work, collaborative prompting, and focusing assessment on critical evaluation of AI output.

Shift focus from content creation to critical thinking, strategic improvement, and ethical AI usage.

Agentic

2025

What Is Agentic AI?

Agentic AI represents the next evolution beyond generative AI, featuring proactive intelligent agents that work through steps toward a goal. Based on robotic process automation principles, these AI agents can understand objectives, plan actions, and execute tasks with minimal human intervention.

Goal-oriented approach: Comprehends high-level goals and the AI agent's defined role
Multistep problem solving: Devises plans to reach objectives through logical steps
Self-directed execution: Takes tactical action, working with other tools, applications, and workflows
Adaptability: Flexibly handles trial-and-error and adapts to changing conditions

Source: Bain & Company, 2024

Agentic

Barriers to Adoption

• Limited generalization beyond narrow scopes
• Difficulty explaining AI decisions
• Challenges with undocumented workflows
• Poor cooperation among multiple agents
• Limited access to clean data and integrated tools

Organizations must address these barriers to successfully implement agentic AI solutions.

Agentic HRM

Workforce Impact

• Productivity increases as employees become AI supervisors
• Roles shift as agents democratize technical skills
• Decision-making cycles accelerate
• Human collaboration remains critical
• Risk management becomes more complex

Economic shifts will occur as agentic AI transforms job functions and organizational structures.

Prompting

Prompting for Complex Tasks

Following are steps to take when prompting for complex tasks

Not all steps are necessary for every task

Define the Objective:

Clearly state the main research question or task (e.g., analyze operational efficiency, draft a strategic plan).
Specify the desired outcome (e.g., detailed analysis, comparison, recommendations).

Gather Context and Background:

Include relevant background info, definitions, and data/documents (e.g., financial reports, HR policies, market data).
Specify boundaries (e.g., scope, timeframes, departments).

Use Specific and Clear Language:

Provide precise wording and define key terms (e.g., ROI, employee engagement, market share).
Avoid vague or ambiguous language.

Set a Role or Perspective:

Assign a role (e.g., "act as a management consultant," "assume the perspective of an HR director," "act as a financial analyst").

Provide Step-by-Step Guidance:

Break the task into sequential steps (e.g., data analysis -> strategic options -> recommendation).
Organize instructions using bullet points or numbered lists.

Specify Details of the Output Format:

Describe required format (e.g., executive summary, SWOT analysis, formal report, presentation slides).
Include specific formatting (headings, tables, charts).

Balance Detail with Flexibility:

Offer enough detail but allow room for novel insights or approaches.
Avoid over-constraining if exploration is desired.

Incorporate Iterative Refinement:

Test the prompt and refine based on initial outputs.
Allow for follow-up instructions to adjust or expand.

Solicit Questions for Clarifying Ambiguities:

Ask the AI what is unclear before it proceeds.
Iteratively refine based on AI's clarifying questions.

Consider Your Task's Complexity:

Is the task too complex for one prompt?
If so, break it into multiple steps/prompts.

Apply Proven Techniques:

Use chain-of-thought ("think step by step") for complex reasoning.
Encourage breaking down problems into intermediate steps.

Avoid Overloading the Prompt:

Focus on one primary objective per prompt if possible.
Break multiple distinct questions into separate prompts.

Request Justification and References:

Instruct the AI to support claims with evidence or reference sources.
Enhance credibility and verifiability (especially important for business decisions).

Review and Edit Thoroughly:

Ensure the final prompt is clear, logical, and complete.
Remove ambiguous or redundant instructions.

Prompting

Clear Context Setting

Define the AI's role clearly (e.g., strategic planner, HR analyst)
Specify the desired output format (e.g., report, memo, presentation)
Provide relevant background (e.g., company context, market conditions)
State constraints or requirements (e.g., budget, timeline, compliance)

Effective prompting begins with clear context setting, significantly improving the quality and relevance of AI responses for management tasks.

"As a management consultant, evaluate {attached operational performance data 2020-2025} for Company XYZ to identify key areas for efficiency improvement.

Analyze how operational bottlenecks correlate with changes in supply chain disruptions and staffing levels, focusing on:
1) Process cycle times in key departments
2) Resource utilization rates
3) Quality control failure points across the value chain

Present your analysis with three key visuals: a process map highlighting inefficiencies, a resource allocation chart, and a forecast of potential cost savings with 90% confidence intervals."

Prompting

Specific Instructions

Break down complex tasks into clear steps
Use clear, actionable language relevant to management
Include example outputs if helpful (e.g., sample report section)
Specify evaluation criteria (e.g., ROI, feasibility, strategic alignment)

Detailed instructions help ensure the AI's output aligns perfectly with your management needs and requirements.

"As a strategic planning director, analyze {attached market analysis report} and {current financial performance indicators}.

Develop a comprehensive 3-year strategic growth plan that:
1) Identifies key growth initiatives (organic & inorganic) with the highest potential ROI based on market opportunities
2) Quantifies required investments and resources for each initiative compared to internal capacity
3) Evaluates potential risks (market, operational, financial) and proposes mitigation strategies
4) Recommends optimal resource allocation with specific KPI targets for year 1, 2, and 3

Include a sensitivity analysis for three economic scenarios: baseline growth, recession, and rapid expansion."

Prompting MGMT

General Management Role Prompting

Operations Manager: Improving process efficiency, resource allocation
Strategy Consultant: Developing business plans, competitive analysis
Project Manager: Planning timelines, risk assessment, resource needs
Financial Analyst: Budgeting, forecasting, investment appraisal

Specifying general management roles helps frame the context and expertise level for AI responses related to operations, strategy, and finance.

"As an operations manager, analyze {attached production workflow data} and {employee feedback on process issues} to develop an improvement plan.

Your plan should:
1) Identify the top 3 bottlenecks impacting throughput and quality
2) Propose specific changes to streamline workflows, including technology adoption or process redesign
3) Estimate the potential impact on cycle time, cost reduction, and employee satisfaction
4) Outline key steps for implementation, including required training and resources
5) Compare your recommendations with industry best practices from {attached benchmarking study}

Include statistical analysis where applicable and clearly articulate the rationale for each recommendation."

Prompting HRM

Human Resource Management Role Prompting

Recruitment Specialist: Drafting job descriptions, screening candidates
Compensation Analyst: Benchmarking salaries, designing incentive plans
Training & Development Manager: Creating learning modules, assessing skill gaps
HR Business Partner: Advising on employee relations, performance management

Using specific HRM roles helps focus the AI on relevant domain expertise like talent acquisition, compensation, learning, and employee relations.

"As a Training & Development Manager, analyze {attached employee performance reviews} and {company strategic goals for next year}.

Develop a comprehensive training program proposal that:
1) Identifies critical skill gaps hindering strategic goal achievement
2) Proposes specific training modules (topics, formats, duration) to address these gaps
3) Recommends delivery methods (e-learning, workshops, mentoring) suited for different employee groups
4) Outlines a budget and timeline for program rollout
5) Defines metrics to measure training effectiveness and ROI (e.g., skill improvement, performance impact)

Structure the proposal with clear sections for Needs Analysis, Program Design, Implementation Plan, and Evaluation Strategy."

Prompting MGMT

Problem Decomposition (Management Context)

Break down complex business problems (e.g., declining profitability)
Identify key drivers and variables (e.g., costs, revenue streams, market factors)
Create logical sequences for analysis (e.g., cost analysis -> revenue analysis -> strategic options)
Build step-by-step solution approaches

Chain-of-thought prompting helps tackle complex management problems by breaking them down into logical analytical steps.

"Let's analyze the root causes of declining profitability in Division X using {attached financial statements} and {operational reports} step-by-step:

1) First, break down the cost structure. Identify trends in major cost categories (COGS, SG&A, R&D) over the last 3 years.
2) Next, analyze revenue streams. Which product lines or customer segments are underperforming? Examine pricing and volume trends.
3) Then, evaluate operational efficiency metrics. Are there increases in waste, downtime, or returns impacting costs?
4) Consider external market factors. Has competition intensified? Are there regulatory changes impacting the business?
5) Synthesize these findings. What are the primary drivers of the profitability decline?
6) Finally, propose 3 potential strategic responses based on this analysis, evaluating the pros and cons of each.

For each step, provide specific data points and logical reasoning."

Prompting MGMT

Solution Validation (Management Context)

Verify logical consistency in strategic recommendations
Check alignment with original business objectives and constraints
Test assumptions and potential unintended consequences
Review feasibility and resource implications of proposed solutions

Systematic validation ensures management solutions are robust, feasible, and meet strategic requirements.

"Critically evaluate the proposed {new market entry strategy document} using the following framework:

1) Assess the market analysis assumptions. Are the market size, growth rate, and competitive landscape assessments realistic?
2) Review the financial projections. Are the revenue forecasts, cost estimates, and ROI calculations sound? Check key assumptions.
3) Evaluate the operational plan. Is the timeline feasible? Are resource requirements accurately estimated? What are the key operational risks?
4) Consider the strategic fit. Does this initiative align with the company's overall mission and core competencies?
5) Identify potential implementation challenges (e.g., cultural barriers, regulatory hurdles, internal resistance).
6) Perform a sensitivity analysis on key variables (e.g., market adoption rate, cost overruns).
7) Compare this strategy against alternative options (e.g., organic growth, acquisition).
8) Provide a final recommendation: Proceed, revise, or reject the strategy, with clear justification."

Prompting MGMT

Few-Shot Learning Approach (Management)

Provide examples of desired input-output pairs (e.g., raw data -> formatted report section)
Demonstrate patterns through multiple examples (e.g., analyzing different types of reports)
Include edge cases (e.g., handling missing data, unusual trends)
Show variations in acceptable outputs (e.g., different summary lengths or chart types)

Using examples helps the AI understand exactly what kind of management report, analysis, or communication style you need.

"I've provided {three examples of well-structured quarterly business review (QBR) summaries}. Using these as reference models, transform {attached raw departmental performance data} into a concise QBR summary for senior leadership.

Your summary should follow the structure of the examples and include:
1) Key Performance Indicators (KPIs) vs. Target, with brief commentary on variances
2) Major achievements and milestones for the quarter
3) Significant challenges encountered and mitigation actions taken
4) Financial overview (Budget vs. Actual)
5) Strategic priorities for the next quarter
6) Required decisions or support needed from leadership

Maintain a professional tone and focus on strategic implications, similar to the provided examples."

Prompting

Best Practice

Output Formatting (Management)

Specify exact output structure (e.g., memo, report sections, presentation outline)
Define templates or required formats (e.g., SWOT analysis table, balanced scorecard)
Include required metadata (e.g., date, author, confidentiality level)
Set clear style guidelines (e.g., tone, level of detail, use of jargon)

Clear output specifications ensure AI-generated management documents are immediately usable and meet organizational standards.

"Generate a formal business proposal for {Project Alpha initiative} following this structured format for board approval:

I. Executive Summary: (Max 1 page) Overview, key objectives, expected outcomes, required investment.
II. Problem Statement / Opportunity: Market context, business need, strategic alignment.
III. Proposed Solution: Detailed description of Project Alpha, methodology, key features/activities.
IV. Implementation Plan: Phased timeline, key milestones, resource requirements (personnel, budget, technology).
V. Financial Analysis: Cost breakdown, projected ROI, key financial assumptions, sensitivity analysis.
VI. Risk Assessment: Potential risks (market, operational, financial, execution) and mitigation strategies.
VII. Team & Governance: Project lead, key team members, reporting structure.
VIII. Conclusion & Recommendation: Summary of benefits, formal request for approval.

Use {attached financial model} and {market research summary} to inform sections V and II respectively. Ensure professional tone and data-driven arguments throughout."

Research

Research Flow [Visit Platform]

A visual research engine that creates interactive mind maps from academic papers and research materials. Features include connection identification between papers and concept visualization.

Enables visual exploration of research connections

Research

Consensus [Visit Platform]

An academic search engine powered by AI that searches over 200M research papers. Uses language models and vector search to surface relevant papers, synthesize insights, and provide evidence-based answers to research questions.

Delivers research-backed answers with direct links to source papers

Research

Mapify [Visit Platform]

Converts various content formats (YouTube, PDFs, documents, URLs, emails, recordings) into structured mind maps using advanced language models. Supports multiple LLM backends including GPT-4 and Claude.

Automates content visualization and summarization

Research

Napkin AI [Visit Platform]

A document editing platform that specializes in transforming text into visual content. The platform offers AI-powered tools that convert written content into graphics, diagrams, and video snippets, enhancing communication and idea clarity.

Transforms text into visual elements for enhanced communication

Research

AnswerThis [Visit Platform]

A research assistant platform that processes academic papers and research documents to provide verified, source-based answers to specific queries. Includes comprehensive summarization capabilities.

Facilitates source-verified research inquiry

Beginner Exercise

Research Paper Analysis

Learn to extract key information from academic papers (e.g., management journals) using structured prompting with PDF documents.

⏱️

Duration: 20 mins

👥

Format: Individual

📄

File: PDF/Word

Exercise Steps:
1. Upload a management research paper
2. Extract key sections (Abstract, Intro, Methods, Results, Conclusion)
3. Analyze methodology & theoretical framework
4. Identify limitations & research gaps
5. Generate future research directions relevant to management practice

"Analyze this management research paper and provide: 1) Key findings summary, 2) Methodology assessment & theoretical contribution, 3) Research gaps cited, 4) Potential future research directions for managers. Format as a structured report..."

Intermediate Exercise Teaching

Course Material Enhancement (Management)

Transform existing lecture notes, case studies, and syllabi for management courses into enhanced learning materials with AI assistance.

⏱️

Duration: 25 mins

👥

Format: Individual

📄

File: Word/PDF

Source Materials:
- Management course syllabus (e.g., OB, Strategy, HRM)
- Lecture slides/notes
- Case study descriptions
- Reading materials (e.g., HBR articles)

"Using this management course material, help me: 1) Create engaging discussion questions linking theory to practice, 2) Develop mini case studies illustrating key concepts, 3) Design practical application exercises, 4) Generate assessment rubrics for case analyses..."

Intermediate Exercise MGMT

Business Data Visualization

Transform raw business data (e.g., sales, operations, HR metrics) into meaningful visualizations and insights using AI-assisted analysis.

⏱️

Duration: 30 mins

👥

Format: Individual/Pairs

📄

File: CSV/Excel

Data Analysis Steps:
1. Data cleaning suggestions
2. Descriptive statistics & analysis
3. Visualization recommendations (e.g., trend charts, dashboards)
4. Key insight generation for management
5. Draft executive summary of findings

"Analyze this business dataset and: 1) Suggest appropriate visualizations for a management dashboard, 2) Identify key trends, correlations, and outliers, 3) Recommend relevant statistical tests, 4) Generate a summary report highlighting actionable insights..."

Advanced Exercise Research

Literature Review Assistant (Management)

Organize and synthesize multiple research papers from management journals for comprehensive literature reviews on a specific topic (e.g., leadership styles, organizational change).

⏱️

Duration: 35 mins

👥

Format: Individual

📄

File: PDF/Word (Multiple)

Review Process:
1. Extract key theoretical frameworks & findings
2. Compare methodologies & sample characteristics
3. Identify common themes & conflicting results
4. Synthesize major contributions & debates
5. Generate thematic map or research matrix

"Review these management papers on [Topic] and create: 1) A comparison matrix of theories, methods, and findings, 2) Thematic analysis of the literature, 3) Identification of key debates and research gaps, 4) Synthesis of the current state of knowledge..."

Intermediate Exercise Research

Grant Proposal Enhancement (Management)

Improve grant proposals related to management research (e.g., organizational behavior study, strategy implementation project) with AI-assisted analysis and recommendations.

⏱️

Duration: 30 mins

👥

Format: Individual

📄

File: Word/PDF

Enhancement Areas:
1. Strengthening practical/theoretical impact statement
2. Refining research questions & methodology
3. Improving budget justification & resource planning
4. Optimizing project timeline & milestones
5. Enhancing writing clarity & persuasiveness

"Review this management research grant proposal and provide feedback on: 1) Strengthening the significance and impact, 2) Improving methodological rigor, 3) Optimizing the budget and timeline justification, 4) Enhancing clarity, focusing on criteria for [Funding Agency, e.g., NSF, SSHRC]..."

Advanced Exercise Research

Semantic Search Setup (Management Research)

Conceptualize setting up a semantic search system for your personal library of management research papers and documents.

⏱️

Duration: 40 mins

👥

Format: Small Groups (Discussing Approach)

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File: N/A (Conceptual)

Conceptual Steps:
1. Document preprocessing (chunking, cleaning)
2. Vector embedding generation
3. Vector database selection/setup
4. Query formulation & optimization
5. Results ranking & relevance tuning

"Help me brainstorm effective semantic search queries for my management research library that can: 1) Find papers using similar theoretical frameworks, 2) Identify studies with contradictory findings on [Topic], 3) Discover methodological gaps related to [Method], 4) Connect related concepts across different sub-disciplines..."

Wrap-up and Next Steps

Bridging Theory and Practice in the AI Era of Management

Key Takeaways

Integration of AI across Management functions (Ops, HR, Strategy, Finance)
Practical prompting strategies for analysis, planning, and decision support
Research opportunities in AI-driven organizational behavior and strategy
Pedagogical approaches for Management education facing AI paradoxes

Next Steps

Implement AI tools in Management course materials and case studies
Develop domain-specific prompting guidelines for management tasks
Create AI-enhanced strategic analysis or operational simulation exercises
Foster collaborative AI research in areas like leadership or organizational change

Impact Metrics

85%

Expected Faculty Adoption

70%

Course Integration

100%

Student AI Exposure

Resources Available

Workshop materials, prompts library, and implementation guides

Support Network

Faculty community and ongoing technical assistance

"Embracing AI in academia isn't just about adopting new tools—it's about reimagining education for the future."

Recent Applications

Key Takeaways

Next Steps

Impact Metrics

Dr. Murtaza Nasir

Dr. Ross Gruetzemacher