Digital Skills & AI for Business - CIS200/2 Spring 2026

Course

Ladislava Knihova

For information about registration please contact our admissions.

About

In a world shaped by rapid digital change, this course equips students with the essential digital skills and AI capabilities needed to thrive in today’s business landscape. It offers a comprehensive introduction to the practical use of digital tools and the transformative potential of artificial intelligence (AI) across key business functions—including marketing, core business operations such as workflow automation, logistics, and customer support, as well as strategic decision-making. Through hands-on projects, real-world case studies, and interactive discussions, students will develop the confidence and competence to apply digital and AI-driven solutions to real business challenges.

1. Student Learning Outcomes

Upon successful completion of this course, students will be able to:

● Identify and apply essential digital tools and AI technologies in business contexts, demonstrating awareness of their limitations in light of fundamental AI concepts.

● Analyse how digital transformation and AI can support business strategy and core business processes such as decision-making, marketing, and customer service.

● Collaborate effectively in teams to design AI-enhanced business solutions.

● Communicate complex AI concepts in a clear, accessible, and professional manner.

● Reflect critically on the ethical, strategic, and personal implications of using AI in business.

2. Reading Materials

Required Materials

● Textbooks

Maheshwari, A. Data Analytics Made Accessible. 2025 edition (Kindle Edition)

Harvard Business Review Press (Ed.). (2023). HBR guide to AI basics for managers. Harvard Business Review Press.

Graylin, A., W., Rosenberg, L. Our Next Reality: How the AI-powered Metaverse Will Reshape the World. 2024.

● Articles

Birkinshaw, J. (2025, April 15). Will AI Disrupt Your Business? Key Questions to Ask. MIT Sloan Management Review. https://sloanreview.mit.edu/article/will-ai-disrupt-your- business-key-questions-to-ask/

Harvard Business Review. (2023). Harvard Business Review, September/October 2023. HBR Store. https://store.hbr.org/product/harvard-business-review-september-october-2023/BR2305

McLaughlin, L. (2025, April 7). 10 Urgent AI Takeaways for Leaders. MIT Sloan Management Review. https://sloanreview.mit.edu/article/10-urgent-ai-takeaways-for-leaders/

Renieris, E. M., Kiron, D., & Mills, S. (2022). To Be a Responsible AI Leader, Focus on Being Responsible. MIT Sloan Management Review. https://sloanreview.mit.edu/projects/to-be-a- responsible-ai-leader-focus-on-being-responsible/

Wingate, D., Burns, B. L., & Barney, J. B. (2025). Why AI Will Not Provide Sustainable Competitive Advantage. MIT SloanManagement Review.

https://sloanreview.mit.edu/article/why-ai-will-not-provide-sustainable-competitive- advantage/

Wu, B. H. and L. (2025, June 25). Why Robots Will Displace Managers—And Create Other Jobs. MIT Sloan Management Review. https://sloanreview.mit.edu/article/why-robots-will- displace-managers-and-create-other-jobs/

Recommended Materials

3. Teaching methodology

This course applies a learner-centred, design-driven instructional approach that integrates design thinking principles with hands-on experimentation using digital tools and AI-driven applications. The learning environment is structured to foster curiosity, iteration, and problem-solving, enabling students to think critically and creatively about how technology can solve real-world business challenges.

Each session follows a pedagogical arc that mirrors the design thinking process:

● Empathise & Define: Students begin by exploring user needs, digital trends, and business pain points through real-world case studies and guided reflection.

● Ideate: In collaborative tasks, students generate potential AI-supported solutions and experiment with digital platforms such as ChatGPT, Canva, Trello, or GPT- integrated Sheets.

● Prototype: Teams create low-fidelity mock-ups, data visualisations, or chatbot scripts, engaging with tools and AI applications in ways that simulate actual business workflows.

● Test & Reflect: Students present ideas, receive peer and instructor feedback, and refine their solutions through iterative improvements.

The course further incorporates project-based learning and task-oriented seminars to build both foundational digital skills and strategic thinking. Throughout, students are encouraged to critically evaluate AI’s role in shaping business processes and to reflect on their personal AI readiness and ethical responsibility.

This methodology supports the development of critical thinking, effective communication, and responsible digital action, while preparing students to lead and contribute in AI-augmented business environments.

4. Course Schedule

Date

Class Agenda

Session 1

Tuesday Seminar Feb 03

Topic: Introduction to Digital Skills and AI for Business

Description: The first session introduces key concepts of digital transformation and the growing role of AI in business. Students explore why digital and AI skills are essential today and try out tools powered by large language models (LLMs), such as ChatGPT and/or Perplexity.ai, in a hands-on activity focused on team-based conflict resolution.

Tool of the Week: ChatGPT (Introduction to digital agents powered by LLMs); Perplexity.ai (LLM-powered research and fact-checking tool)

Mini-task: Describe digital transformation in a company of your choice. Seminar Activity: Map of essential digital skills (via Miro or Jamboard) Reading: Chapter 1: Wholeness of Data Analytics (Maheshwari, A. Data Analytics Made Accessible. 2025 edition), pp. 19 – 49 Assignments/deadlines:

N/A

Session 2

Tuesday Seminar Feb 10

Topic: Digital Tools for Productivity

Description: Session 2 introduces students to essential office and collaboration tools, with a focus on boosting productivity through AI- enhanced platforms and hands-on teamwork.

Tool of the Week: Notion AI

Mini-task: Design a team workspace for a small business.

Gamified Activity: Productivity challenge using AI-based tools.

Reading: Chapter 2: Business Intelligence Concepts and Applications (Maheshwari, A. Data Analytics Made Accessible. 2025 edition), pp. 50 – 72 Additional Reading: Gilbert, R. M. (2019). Inclusive Design for a Digital World: Designing with Accessibility in Mind. Apress. https://doi.org/10.1007/978-1-4842-5016-7

Assignments/deadlines:

CW1 / Deadline: From Feb 09, 11:59 PM to Apr 09, 11:59 PM (local time)

Session 3

Tuesday Seminar Feb 17

Topic: Data Literacy and Analysis

Description: Session 3 builds foundational data literacy by exploring key data concepts and hands-on analysis using Excel, Google Sheets with AI add- ons, and basic data visualization tools.

Tool of the Week: Google Sheets + GPT for Sheets Add-on

Mini-task: Visualize data from a business scenario (e.g., coffee shop sales).

Discussion: Is data the “new oil”?

Reading: Chapter 3: Data Warehousing (Maheshwari, A. Data Analytics Made Accessible. 2025 edition), pp. 73 - 84

Assignments/deadlines:

CW1 / Deadline: From Feb 09, 11:59 PM to Apr 09, 11:59 PM (local time)

Session 4

Tuesday Seminar
Feb 24

Topic: Fundamentals of Artificial Intelligence

Description: Session 4 introduces the fundamentals of artificial intelligence, with emphasis on prompt engineering and key terminology. Students explore how AI models respond to different types of inputs and how tone, clarity, and specificity influence outcomes. Through interactive tools, tonality-focused tasks, and creative explanation activities, the session guides students to develop effective and ethical prompting habits—essential for productive AI use in business and for understanding the shift from traditional SEO to Generative Engine Optimization (GEO) in the emerging competition for digital visibility.

Tool of the Week: OpenAI Prompt Generator inside ChatGPT (for Pro users)

Mini-task: Explain AI to a child, a grandparent, and a CEO.

Video Resource: “AI for Everyone” (Andrew Ng excerpts) & „Digital Marketing Foundations - How to get started with SEO and GEO (a LinkedIn Course)

Reading: Chapter 4: Data Mining (Maheshwari, A. Data Analytics Made
Accessible. 2025 edition), pp. 85 - 106

Assignments/deadlines: QUIZ 1

Session 5

Tuesday Seminar Mar 03

Topic: AI Applications in Business

Description: Through sector case studies and a practical SWOT, Session 5 shows where AI creates value in marketing, finance and operations. We spotlight agentic AI—AI systems that can reason, plan and take actions—to discuss opportunities, risks and guardrails.

Tool of the Week: ChatGPT + Browsing + Advanced Data Analysis (Pro)

Mini-task: Analyze one case using a SWOT framework.

Guest Content: McKinsey’s AI in business video

Voices from Experts: "Will AI Disrupt Your Business? Key Questions to Ask" by Julian Birkinshaw, MIT Sloan Management Review

Reading I: Chapter 5: Data Visualization (Maheshwari, A. Data Analytics Made Accessible. 2025 edition), pp. 107 - 122 Assignments/deadlines:

CW1 / Deadline: From Feb 09, 11:59 PM to Apr 09, 11:59 PM (local time)
CW2 / Deadline: Mar 03 by 11:59 PM (local time)

Session 6

Tuesday Seminar Mar 10

Topic: AI in Marketing and Customer Service

Description: Session 6 focuses on AI-driven personalization and customer interaction, offering hands-on practice with chatbot design and prompting critical discussion on the emotional limits of AI in customer service.

Mini-task: Design and test a basic customer service chatbot.

Discussion: Can AI truly empathize with customers?

Reading: Chapter 6: Decision Trees (Maheshwari, A. Data Analytics Made Accessible. 2025 edition), pp. 124 - 143

Assignments/deadlines:

CW1 / Deadline: From Feb 09, 11:59 PM to Apr 09, 11:59 PM (local time)

Session 7

Tuesday Seminar Mar 17

Topic: CW2 Prompt Engineering Presentations
Description: In this session, students will present the results of their CW2 assignment, demonstrating how tone influences AI-generated outputs. Individually, each student will showcase two prompts crafted in distinct tonalities, explain their rationale, and evaluate the generated responses in terms of effectiveness for a chosen business context. Presentations will be followed by peer feedback and short discussion. This session fosters critical thinking about prompt design, communication style, and the strategic use of generative AI in business communication.

Tool of the week: ChatGPT or similar LLM applications.

Peer Feedback: Structured feedback forms for review.

Reading: Chapter 7: Regression (Maheshwari, A. Data Analytics Made Accessible. 2025 edition), pp. 144 - 161

Assignments/deadlines:

N/A

Session 8

Tuesday Seminar Mar 24

Topic: E-commerce and Online Business Models

Description: Session 8 explores e-commerce and online business models, combining platform overviews with a hands-on task to design a digital storefront and visualize its structure using Canva and Miro.

Mini-task: Design a digital storefront with Canva + wireframe in Miro

Tools exploration: Shopify or similar demo

Reading: Chapter 8: Artificial Neural Networks (Maheshwari, A. Data Analytics Made Accessible. 2025 edition), pp. 162 - 172 Assignments/deadlines:

N/A

Mid-term break March 30– April 03 2026

Session 9

Tuesday Seminar Apr 07

Topic: Data Privacy & Ethical Use of AI

Description: Session 9 addresses data privacy and the ethical use of AI, engaging students in regulatory frameworks like GDPR and CCPA via roleplay and critical evaluation of AI tools using the AI Ethics Canvas.

Voices from Experts: "To Be a Responsible AI Leader, Focus on Being Responsible"by Elizabeth M. Renieris, David Kiron, and Steven Mills, MIT Sloan Management Review

Mini-task: Evaluate an AI tool using the AI Ethics Canvas

Roleplay: Business vs customer scenario regarding privacy

Reading: Chapter 9: Cluster Analysis (Maheshwari, A. Data Analytics Made Accessible. 2025 edition), pp. 173 – 190

Assignments/deadlines:

CW3a / Deadline: Apr 06 by 11:59 PM (local time)

Session 10

Tuesday Seminar Apr 14

Topic: AI and Decision Making

Description: Session 10 explores how AI supports business decision-making through predictive analytics and forecasting tools, encouraging students to experiment with data-driven insights and reflect on the role of human judgment.

Voices from Experts: "Why AI Will Not Provide Sustainable Competitive Advantage” by Wingate, Burns & Barney", MIT Sloan Management Review Mini-task: Forecast traffic for a retail website Tools: Power BI (demo), Google Sheets forecasting

Discussion: Can AI replace human judgment?

Reading: Chapter 10: Association Rule Mining (Maheshwari, A. Data Analytics Made Accessible. 2025 edition), pp. 191 – 203

„Managing AI Decision-Making Tools“, A Framework to Determine When and How Humans need to Say Involved.Harvard Business Review Press (Ed.). (2023). HBR guide to AI basics for managers. Harvard Business Review Press, pp. 139-145.

Assignments/deadlines:

CW3b / Deadline: Apr 14 by 11:59 PM (local time)

Session 11

Tuesday Seminar Apr 21

Topic: Project Management in a Digital Environment Description: Session 11 focuses on project management in a digital

environment, introducing AI-enhanced tools and techniques while guiding students through the creation of a Gantt chart and reflection on remote team collaboration.

Mini-task: Build a Gantt chart for a digital marketing campaign

Reflection: Managing teams remotely with AI

Reading: Chapter 11: Text Mining (Maheshwari, A. Data Analytics Made Accessible. 2025 edition), pp. 205 – 219

Assignments/deadlines:

N/A

Session 12

Tuesday Seminar Apr 28

Topic: Future Trends in Digital Business

Description: Session 12 looks ahead to future trends in digital business, with particular emphasis on Agentic AI and the emerging role of AI as a semi-autonomous business actor. Alongside agentic systems, the session also explores related developments such as AI co-workers, the metaverse, blockchain, and IoT. A creative task invites participants to envision their own AI-enhanced career path in a rapidly evolving business environment.

Voices from Experts: "10 Urgent AI Takeaways for Leaders" by

Laurianne McLaughlin, MIT Sloan Management Review
Assignments/deadlines:

N/A

Mini-task: Imagine and define your personal AI-enhanced career path

Exploration: Agentic AI, Metaverse, digital twins, AI co-workers

Reading: Chapter 12: Naïve Bayes Analysis (Maheshwari, A. Data Analytics Made Accessible. 2025 edition), pp. 205 – 219

Assignments/deadlines:

N/A

Session 13

Tuesday Seminar May 05

Topic: Final Project Workshop - Agentic AI for Business

Description: Session 13 is dedicated to final project development, providing structured peer review, instructor check-ins, and collaborative feedback to help teams refine their AI and digital tool-based solutions.
Session 13 is dedicated to final project development focused on the design of an Agentic AI business solution, providing structured peer review, instructor check-ins, and collaborative feedback.

Peer Review: Rubrics and structured feedback

Check-in: Team milestone updates with instructor guidance

Reading: Chapter 13: Web mining (Maheshwari, A. Data Analytics Made Accessible. 2025 edition), pp. 235 – 241

Assignments/deadlines:

CW4 – Draft / Deadline: May 04 11:59 (local time)

Session 14

Tuesday Seminar May 12

Topic: Final Project Presentations – Agentic AI for Business

Description: Session 14 features final team presentations of the Agentic AI projects. Each team will present a fully designed agentic AI concept that demonstrates how semi-autonomous AI systems can support business functions under human supervision. Presentations will focus on business logic, governance, value creation, and team collaboration rather than technical implementation.

Format: Team presentation (15 minutes + Q&A) supported by a structured PPT deck. Alternatively, apart from a PPT presentation, teams can present a demo or prototype, optional video.

Reflection Prompt (integrated into presentation): What did designing an Agentic AI system change about your understanding of managerial responsibility, teamwork, and decision-making in the AI era?

Reading: Chapter 14: Social Network Analysis (Maheshwari, A. Data Analytics Made Accessible. 2025 edition), pp. 242 – 255 Assignments/deadlines:

CW4 – Final version / Deadline: Dec 11 by 11:59 (local time)

5. Course Requirements and Assessment (with estimated workloads)

Assignment	Workload (hours)	Weight in Final Grade	Evaluated Course Specific Learning Outcomes	Evaluated Institutional Learning Outcomes*
Class Participation	42	10%	Active engagement in discussion, tool exploration, peer feedback, and teamwork.	3
CW1: AI Glossary (Pairs)	8	10%	Define and present 6 essential AI terms clearly and accessibly, based on literature research and real-world business relevance.	1,2
Quiz 1 Session 4 (Individual)	10	10%	Assess understanding of core digital tools, prompt design, and AI fundamentals.	1

CW2: Prompt Engineering Reflection (Individual)	10	10%	Explore how tone influences AI-generated responses by crafting and comparing prompts in two distinct tonalities and reflecting on their effectiveness in a business context.	1,2
CW3a: AI in Action: Solving a Real- World Challenge (Team Project)	20	25%	Apply digital and AI tools to address a practical business scenario in a team setting.	1,2,3
CW3b: AI in Action: Solving a Real- World Challenge (Individual Reflection on Team Project)	10	10%	Reflect critically on individual learning and contribution to the team project.	1
CW4: Agentic AI for Business – Design & Governance (Team Project)	50	25%	Design and present an Agentic AI system for a business context, demonstrating how semi-autonomous AI agents can support decision-making and business processes under human supervision, with clear governance, value creation, and team collaboration.	1,2,3
TOTAL	150	100%

*1 = Critical Thinking; 2 = Effective Communication; 3 = Effective and Responsible Action

6. Detailed description of the assignments

Assignment 1

CW1: AI Glossary (Pairs)

You will work in pairs to create a glossary of six essential AI terms relevant to digital skills and business applications. Each student is responsible for three terms, while the pair jointly prepares one presentation and presents together in class.

The goal of this assignment is to define and present six essential AI terms clearly and accessibly, grounded in literature research and real-world business relevance.

❖ Assignment Description

In this first coursework assignment, you will work in pairs to create a glossary of six essential AI terms that are shaping today’s business and digital landscape. The focus is on AI-related terminology such as concepts, tools, models, or processes that appear throughout the course.

Your goal is to deepen your understanding of foundational and emerging AI concepts, while learning to explain them clearly and accessibly—an essential digital competency for anyone working with or alongside intelligent technologies.

Start with a brief literature review, drawing on:

● Required course readings (e.g. Data Analytics Made Accessible, Our Next Reality)

● Curated articles from MIT Sloan Management Review, OpenAI, McKinsey, or similar

● Reputable sources such as academic journals, white papers, or industry blogs

Each of the six selected terms should include:

● A correct source citation in APA 7th format

● Each of the six selected terms should include:

● A clear and concise definition (max. 100 words)

● A real-world business example or application in context

● A correct source citation in APA 7th format

● Where appropriate, a simple self-explanatory visual (e.g. diagram, icon, process flow, or metaphorical illustration) to support understanding

Each pair will deliver a 5-minute joint in-class presentation, in which both students actively participate, explaining the relevance and real-world significance of their selected terms in business or marketing contexts. You may support your explanation with a short visual, metaphor, or analogy to aid understanding. Use simple visuals in a professional-looking PPT template.

Important rule on terminology selection: If a term has already been presented by another pair, subsequent teams must approach it from a different business perspective, industry, or managerial angle. Repeating an already presented explanation or example will not be accepted. A shared class glossary will be maintained during presentations to track covered terms and perspectives.

CW1: Assessment Criteria Breakdown

Assessed area	Percentage
1. Content: Accuracy and completeness of definitions, relevance of selected terms, and depth of understanding demonstrated in explanations.	40%
2. Presentation: Clarity, organization, and effectiveness of the in-class presentation; originality of perspective and avoidance of repetitive explanations; ability to engage with the audience and answer questions; and effective use of simple, self-explanatory visuals to support understanding where appropriate.	30%
3. Research and Examples: Use of appropriate examples or case studies to illustrate the terms.	20%
4. Professionalism and Timeliness: Adherence to formatting guidelines, timely submission of materials, and overall professionalism in both the written and presented work.	10%
TOTAL	100%

Assignment 2

CW2: Prompt Engineering Reflection – The Power of Tone (Individual)

This assignment focuses on developing your prompt engineering skills by exploring how variations in tone and style influence the quality and effectiveness of AI-generated output. You will practice crafting purpose-driven prompts, experiment with tonal differences, and reflect on their impact—essential competencies for effective AI-assisted communication in business contexts.

❖ Assignment Description

● ∙ Choose a realistic business use case (e.g., replying to a customer complaint, drafting a motivational message to your team, summarising an ESG report, creating a product pitch).

● Write a single prompt for that use case.

● Rewrite your prompt in two different tonalities using the combinations from the handout Tonality in Conversation with Generative Language Models (e.g., friendly + professional vs authoritative + expert).

● Run both prompts using ChatGPT or another AI language model. Save the responses.

● Write a short reflection (150–200 words) answering:

o How did the tonal differences affect the response?

o Which version better suited your intended business goal—and why?

o What did you learn about tone as a tool in AI communication?

o What does this teach you about communicating with AI in business settings?

CW2: Assessment Criteria Breakdown

Assessed area/Criterion	Description	Percentage
1. Reflection & Insight	Evidence of critical thinking, observation, and learning	40%
2. Prompt Quality	Clear, task-appropriate prompt with well-applied tonal variation	30%
3. Relevance of Tone Choices	Match of tone to business context, purpose, and medium	20%
4. Language & Structure	Professional formatting, coherence, and grammar	10%
TOTAL		100%

Assignment 3a

CW3a: AI in Action: Solving a Real-World Challenge (Team Project)

Assignment Description

In this team project, you will apply what you have learned so far to design a practical, AI- enhanced solution to a real-world business problem. Working in small teams (3–4 students), you will identify a challenge in marketing, operations, customer service, HR, or e-commerce—and use digital and AI tools to address it creatively and effectively.

Your task is to explore the potential of digital tools to streamline processes, improve decision- making, or add customer value. The outcome should be a short team presentation demonstrating your proposed solution, the tools used, and a simple prototype, demo, or mock-up.

This is your opportunity to experiment with tools, solve a relevant business scenario, and demonstrate your growing digital confidence in front of your peers.

What You Will Do:

1. Select a real or realistic business scenario (e.g., onboarding customers, streamlining internal processes, automating feedback collection).

2. Choose relevant tools introduced in class (e.g., ChatGPT, Canva Magic, Trello, GPT for Sheets, Intercom chatbot builder, Power BI, Copy.ai, etc.).

3. Design your AI-powered solution, clearly showing how the tool(s) improve a process, enhance decision-making, or create value.

4. Prepare a short team presentation (5–7 minutes) that includes:

o The problem you identified

o Your proposed solution

o Tools used and why

o A simple prototype, visual mockup, chatbot sample, or data example

o Lessons learned and challenges faced

Deliverables:

● Seminar presentation (PPT SLIDES)

● One-page concept summary outlining the business case, tools used, and key benefits

CW3a: Assessment Criteria Breakdown

Assessed area	Percentage
1. Relevance and originality of the business problem	20%
2. Effectiveness and creativity of the AI-based solution	30%
3. Quality and clarity of the presentation	25%
4. Use of appropriate tools and justification	15%
5. Teamwork and contribution balance	10%
TOTAL	100%

Assignment 3b

CW3b: Individual Reflection on the Team Project CW3a

After completing the group project, you will write a short individual reflection (300–400 words) that deepens your learning and connects your experience to your personal development. This reflection should capture what you contributed to the team, how the collaboration shaped your understanding of AI tools, and how the project helped you discover your personal AI-business advantage.

Assignment Description

After completing your group project, you will write an individual reflection (300–400 words) that covers two key areas:

1. Your experience and contribution to the team: What you learned from the collaborative process, challenges faced, and how your understanding of AI tools evolved through the project.

2. Your personal AI-business advantage: Based on the course so far, what do you see as your unique strength or opportunity when it comes to using AI in business contexts? How do you plan to apply this in your future studies or career?

This reflection helps consolidate learning, deepen your self-awareness, and highlight your ability to critically evaluate both teamwork and the role of AI in business.

CW3b: Individual Reflection on the Team Project CW3a – Assessment Criteria Breakdown

Assessed area	Percentage
1. Insightful reflection on personal learning, growth, and team contribution	35%
2. Critical evaluation of the team project solution and the use of AI tools	25%
3. Clarity and originality in identifying personal AI-business advantage	25%
4. Structure, language, and submission quality	15%
TOTAL	100%

Assignment 4

CW4: Agentic AI for Business – Design & Governance (Final Team Project)

❖ Assignment Description

This capstone team project reflects the latest evolution in applied artificial intelligence: Agentic AI — AI systems that can plan, decide, and act semi-autonomously while remaining under human supervision.

In teams of 3–4 students, you will design an Agentic AI system for a real or realistic business context, focusing on business value, decision logic, governance, and collaboration, not technical implementation.

You are not expected to code or build software. The emphasis is on managerial thinking, strategic design, and responsible AI use.

What You Will Do

Your team will:

1. Select a business context, such as:
  - Marketing & branding
  - Customer service
  - HR & recruitment
  - ESG & sustainability
  - Operations or internal processes
  - Education & training
2. Design an Agentic AI system, clearly defining:
  - The agent’s role and mission
  - What the agent can decide or do autonomously
  - What actions require human approval
  - How often and in what situations the agent acts
3. Define Human-in-the-Loop Governance, including:
  - Who supervises the agent
  - How escalation and intervention work
  - How errors, bias, or misuse are handled
  - Where responsibility and accountability lie
4. Explain Business Value, addressing:
  - Efficiency gains
  - Customer or employee experience
  - Strategic relevance
5. Reflect on Risks & Limits, such as:
  - Ethical concerns
  - Over-automation
  - Data sensitivity
  - Trust and transparency
6. Demonstrate Team Collaboration, explicitly describing:
  - Individual team roles
  - How responsibilities were divided
  - Key collaboration challenges
  - How the team resolved disagreements or coordination issues
7. Deliver a 15 minute team presentation during the final session. A live demo, prototype, or short video are encouraged but optional.

Required Output

Team Presentation (PPT)

● Length: 15 minutes (+ Q&A)

● Slides: approx. 12–15 slides

● Format: PowerPoint / Canva / PDF

Mandatory slide structure

1. Business context & problem
2. Why this problem matters
3. The Agentic AI concept (role & mission)
4. Agent capabilities (what it does autonomously)
5. Human-in-the-loop governance model
6. Decision boundaries (AI vs human)
7. Business value created
8. Ethical risks & safeguards
9. Team roles & responsibilities
10. Collaboration challenges & lessons learned
11. Limitations & open questions
12. Key takeaways for managers

CW4: Assessment Criteria Breakdown

Assessed area	Percentage
1. Quality of Agentic AI design & business logic: Relevance of problem, clarity of agent role, decision logic, business fit	30%
2. Governance, ethics & human oversight: Human-in-the-loop, responsibility, ethical risks, safeguards	20%
3. Team collaboration & role clarity: Defined roles, contribution balance, cooperation, conflict handling	20%
4. Presentation quality & structure: Logical structure, clarity, visual support, teamwork, and delivery	20%
5. Critical reflection & managerial insight: Lessons learned, limitations, managerial perspective, future implications	10%
TOTAL	100%

7. General Requirements and School Policies

General requirements

All coursework is governed by AAU’s academic rules. Students are expected to be familiar with the academic rules in the Academic Codex and Student Handbook and to maintain the highest standards of honesty and academic integrity in their work. Please see the AAU intranet for a summary of key policies regarding coursework.

Course-specific requirements

There are no special requirements or deviations from AAU policies for this course.

Lessons14

Here is the course outline:

The first session introduces key concepts of digital transformation and the growing role of AI in business. Students explore why digital and AI skills are essential today and try out tools powered by large language models (LLMs), such as ChatGPT and/or Perplexity.ai, in a hands-on activity focused on team-based conflict resolution. Tool of the Week: ChatGPT (Introduction to digital agents powered by LLMs); Perplexity.ai (LLM-powered research and fact-checking tool) Seminar Activity: AI Prompts for Conflict Resolution

Session 2 introduces students to essential office and collaboration tools, with a focus on boosting productivity through AI-enhanced platforms and hands-on teamwork. Tool of the Week: Notion AI

Session 3 builds foundational data literacy by exploring key data concepts and hands-on analysis using Excel, Google Sheets with AI add-ons, and basic data visualization tools. Tool of the Week: Google Sheets + GPT for Sheets Add-on

Session 4 introduces the fundamentals of artificial intelligence, with emphasis on prompt engineering and key terminology. Students explore how AI models respond to different types of inputs and how tone, clarity, and specificity influence outcomes. Through interactive tools, tonality-focused tasks, and creative explanation activities, the session guides students to develop effective and ethical prompting habits—essential for productive AI use in business and for understanding the shift from traditional SEO to Generative Engine Optimization (GEO) in the emerging competition for digital visibility. Tool of the Week: OpenAI Prompt Generator inside ChatGPT (for Pro users)

Through sector case studies and a practical SWOT, Session 5 shows where AI creates value in marketing, finance and operations. We spotlight agentic AI—AI systems that can reason, plan and take actions—to discuss opportunities, risks and guardrails. Tool of the Week: ChatGPT + Browsing + Advanced Data Analysis (Pro)

Session 6 focuses on AI-driven personalization and customer interaction, offering hands-on practice with chatbot design and prompting critical discussion on the emotional limits of AI in customer service. Tools of the week: Tidio / Smartsupp / HubSpot Free Chatbot Builder /Landbot

In this session, students will present the results of their CW2 assignment, demonstrating how tone influences AI-generated outputs. Individually, each student will showcase two prompts crafted in distinct tonalities, explain their rationale, and evaluate the generated responses in terms of effectiveness for a chosen business context. Presentations will be followed by peer feedback and short discussion. This session fosters critical thinking about prompt design, communication style, and the strategic use of generative AI in business communication. Tool of the week: ChatGPT or similar LLM applications.

Session 8 explores e-commerce and online business models, combining platform overviews with a hands-on task to design a digital storefront and visualize its structure using Canva and Miro. Tool of the Week: Shopify (Free Trial) / Canva / Miro

Description: Session 9 addresses data privacy and the ethical use of AI, engaging students in regulatory frameworks like GDPR and CCPA via roleplay and critical evaluation of AI tools using the AI Ethics Canvas. Tool of the Week: ForHumanity AI Ethics Canvas / OpenAI System Card / PrivacyTools.io

Session 10 explores how AI supports business decision-making through predictive analytics and forecasting tools, encouraging students to experiment with data-driven insights and reflect on the role of human judgment. Tool of the Week: Google Sheets Forecasting / Power BI (free desktop version)

Session 11 focuses on project management in a digital environment, introducing AI-enhanced tools and techniques while guiding students through the creation of a Gantt chart and reflection on remote team collaboration. Tool of the Week: Trello with AI Power-Ups / Asana (Free Plan)

Session 12 looks ahead to future trends in digital business, including blockchain, IoT, the metaverse, and AI co-workers, with a creative task to envision one’s own AI-enhanced career path. Tool of the Week: Canva AI / Miro (Free Plan)

Session 13 is dedicated to final project development, providing structured peer review, instructor check-ins, and collaborative feedback to help teams refine their AI and digital tool-based solutions.

Session 14 features final project presentations where students pitch their digital and AI-powered business solutions, followed by reflective discussion on their personal AI-business advantage and key takeaways from the course.

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Digital Skills & AI for Business - CIS200/2 Spring 2026

1. Student Learning Outcomes

2. Reading Materials

3. Teaching methodology

4. Course Schedule

6. Detailed description of the assignments

CW1: AI Glossary (Pairs)

❖ Assignment Description

CW1: Assessment Criteria Breakdown

CW2: Prompt Engineering Reflection – The Power of Tone (Individual)

❖ Assignment Description

CW2: Assessment Criteria Breakdown

CW3a: AI in Action: Solving a Real-World Challenge (Team Project)

What You Will Do:

Deliverables:

CW3a: Assessment Criteria Breakdown

CW3b: Individual Reflection on the Team Project CW3a

Assignment Description

CW3b: Individual Reflection on the Team Project CW3a – Assessment Criteria Breakdown

CW4: Agentic AI for Business – Design & Governance (Final Team Project)

What You Will Do

CW4: Assessment Criteria Breakdown

1. Introduction to Digital Skills & AI for Business

2. Digital Tools for Productivity

3. Data Literacy and Analysis

4. Fundamentals of Artificial Intelligence

5. AI Applications in Business

6. Topic: AI in Marketing and Customer Service

7. Prompt Engineering Reflection

8. E-commerce and Online Business Models

9. Data Privacy & Ethical Use of AI

10. AI and Decision Making

11. Project Management in a Digital Environment

12. Future Trends in Digital Business

13. Final Project Workshop

14. Topic: Final Project Presentations