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Digital Skills & AI for Business - CIS200/1 Fall 2025
Course
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Ladislava Knihova
COURSE SYLLABUS
Digital Skills & AI for Business
CIS200/1 Fall 2025
Course code: CIS 200
Term and year: Fall 2025
Day and time: Mondays 8:00-10:45
Instructor: PhDr. Ladislava Knihová, Ph.D., MBA
Instructor contact: ladislava.knihova@aauni.edu
Consultation hours: Tuesday 10:45 – 11:15; Tuesday 14:00 – 14:30
|
Credits US/ECTS |
3/6 |
Level |
Bachelor |
|
Length |
15 weeks |
Pre-requisite |
CIS 200 |
|
Contact hours |
42 hours |
Grading |
Letter grade |
1. Course Description
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.
2. 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.
3. Reading Material
Required Materials
· Textbook Required:
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.
Recommended:
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
Graylin, A., W., Rosenberg, L. Our Next Reality: How the AI-powered Metaverse Will Reshape the World. 2024.
How AI is Transforming Customer Service. Harvard Business Review, 2023.
· List of required 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 Press (Ed.). (2023). HBR guide to AI basics for managers. Harvard Business Review Press.
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 Sloan Management 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
· LinkedIn Learning & Coursera Educational Courses on relevant topics
4. 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.
5. Course Schedule
|
Date |
Class Agenda |
|
Session 1 Monday Seminar Sep 01 |
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: CW1 / Deadline: Sep 01 by 00:00 |
|
Session 2 Monday Seminar Sep 08 |
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: Sep 08 by 00:00 |
|
Session 3 Monday Seminar Sep 15 |
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: Sep 15 by 00:00 |
|
Session 4 Monday Seminar Sep 22 |
Topic: Fundamentals of Artificial Intelligence Description: Session 4 introduces the fundamentals of artificial intelligence, with emphasis on prompt engineering and key terminology. Students will explore how AI models respond to different types of inputs and how tone, clarity, and specificity influence outcomes. Interactive tools, tonality-focused tasks, and creative explanation activities guide students to develop effective and ethical prompting habits—essential for productive AI use in business. From SEO to GEO: A New Battle for 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) - Reading: Chapter 4: Data Mining (Maheshwari, A. Data Analytics Made Accessible. 2025 edition), pp. 85 - 106 Assignments/deadlines: QUIZ 1 |
|
Session 5 Monday Seminar Sep 29 |
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: Sep 29 by 00:00 |
|
Session 6 Monday Seminar Oct 06 |
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: Oct 06 by 00:00 |
|
Session 7 Monday Seminar Oct 13 |
Topic: CW2 Prompt Engineering Presentations 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:
|
|
Session 8 Monday Seminar Oct 20 |
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: CW1 / Deadline: Oct 20 by 00:00 CW3a / Deadline: October 20 by 00:00 |
|
|
Mid-term break 27th – 31st October 2025 |
|
Session 9 Monday Seminar Nov 03 |
Topic: Data Privacy and Ethics in AI Description: Session 9 addresses data privacy and the ethical use of AI, engaging students in regulatory frameworks like GDPR and CCPA through 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: CW1 / Deadline: Nov 03 by 00:00 CW3b / Deadline: Nov 03 by 00:00 |
|
Session 10 Monday Seminar Nov 10 |
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: CW1 / Deadline: Nov 10 by 00:00 |
|
Session 11 Monday Seminar Nov 24 |
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: CW1 / Deadline: Nov 18 by 00:00 / Nov 24 by 00:00 |
|
Session 12 Monday Seminar Dec 01 |
Topic: Future Trends in Digital Business Description: 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. Voices from Experts: "10 Urgent AI Takeaways for Leaders" by Laurianne McLaughlin, MIT Sloan Management Review |
|
|
Mini-task: Imagine and define your personal AI-enhanced career path Exploration: 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: CW1 / Deadline: Oct 25 by 00:00 / Dec 01 by 00:00 |
|
Session 13 Monday Seminar Dec 08 |
Topic: Final Project Workshop 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. 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: Dec 02 by 00:00 / Dec 08 by 00:00 |
|
Session 14 Monday Seminar Dec 15 |
Topic: Final Project Presentations Description: 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. Format: 5-slide pitch deck 1. Problem – What specific challenge or need are you addressing? 2. Solution – What is your proposed solution and how does it work? 3. Tool/Technology – Which digital or AI tools are you using, and why? 4. Benefit – What value does your solution bring to the business or customer? 5. Challenge – What is one limitation or open question that remains? Alternatively, demo or prototype, optional video. Reflection Prompt: What is your personal AI-business advantage? Reading: Chapter 14: Social Network Analysis (Maheshwari, A. Data Analytics Made Accessible. 2025 edition), pp. 242 – 255 Assignments/deadlines: CW4 / Deadline: Dec 09 by 00:00 / Dec 15 by 00:00 |
6. 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 (Individual) |
8 |
10% |
Define and present 5 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: AI Agent in Action: From Tools to Solution (Team Project) |
50 |
25% |
Design and present an AI- powered agent or solution, demonstrating how digital and AI tools can be implemented to address a business need. |
1,2,3 |
|
TOTAL |
150 |
100% |
|
|
*1 = Critical Thinking; 2 = Effective Communication; 3 = Effective and Responsible Action
7. Detailed description of the assignments
Assignment 1
CW1: AI Glossary (Individual)
You will work individually to create a glossary of five essential AI terms relevant to digital skills and business applications. The goal is to deepen your understanding of key terminology and your ability to explain it clearly and accessibly. You will present your glossary in class.
v Assignment Description
In this first coursework assignment, you will work in pairs to create a glossary of five essential AI terms that are shaping today's business and digital landscape. The focus is specifically 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 your 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
You will also present the five terms in a 5 minute in-class presentation, where you will explain its relevance and real-world significance in business or marketing contexts. You may support your explanation with a short visual, metaphor, or analogy to aid understanding. Use simple visuals or analogies to support your explanation in a professional-looking PPT template.
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. Ability to engage with the audience and answer questions. |
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 |
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.
v 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 + Individual Reflection)
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 Team Project
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 Team Project – 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: The AI Advantage Project (Final Team Project)
v Assignment Description
This capstone project is your team’s opportunity to demonstrate how digital and AI-driven tools can be strategically applied to address a real-world business need. In teams of 3–4 students, you will design and present an AI-powered concept, prototype, or agent that delivers clear value to a company, customer, or internal business function.
You are expected to creatively integrate course knowledge, showcase practical tool use, and communicate your solution with clarity and impact.
What You Will Do
1. Identify a business opportunity or challenge in areas such as marketing, operations, customer experience, e-commerce, HR, or digital communication.
2. Design an AI-powered solution that addresses this need (e.g., chatbot, smart recommendation system, automated dashboard, AI-driven campaign, etc.).
3. Select and document at least one AI tool introduced during the course (e.g.,
ChatGPT, Canva Magic, Copy.ai, DALL·E, ElevenLabs, GPT for Sheets, etc.).
4. Prepare a 5-slide pitch deck (or visual presentation) answering:
o What is the business problem?
o What is your proposed solution and how does it work?
o What AI tools are used and why?
o What benefits does it bring to users or the business?
o What was one key challenge or limitation you encountered?
5. Deliver a 6–8 minute team presentation during the final session. A live demo or short video is encouraged but optional.
Deliverables
· Seminar pitch deck (5 slides, PDF or Canva/PowerPoint)
· Optional: demo, prototype, or short video
CW4: Assessment Criteria Breakdown
|
Assessed area |
Percentage |
|
1. Problem-Solution Fit: Clear identification of a relevant business challenge and logical, innovative AI-powered solution |
30% |
|
2. Effective Use of AI Tools: Appropriate, justified, and creative use of digital and AI tools |
25% |
|
3. Presentation Quality: Structure, clarity, visual support, teamwork, and delivery |
25% |
|
4. Prototype or Concept Depth: Demonstration of feasibility, value creation, or interactivity of proposed solution |
20% |
|
TOTAL |
100% |
8. 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.
Here is the course outline:
1. Introduction to Digital Skills & AI for Business
Sep 1 8am .. 10:45am
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 |
2. Digital Tools for Productivity
Sep 8 8am .. 10:45am
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 |
3. Data Literacy and Analysis
Sep 15 8am .. 10:45am
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 |
4. Fundamentals of Artificial Intelligence
Sep 22 8am .. 10:45am
Session 4 introduces the fundamentals of artificial intelligence, with emphasis on prompt engineering and key terminology. Students will explore how AI models respond to different types of inputs and how tone, clarity, and specificity influence outcomes. Interactive tools, tonality-focused tasks, and creative explanation activities guide students to develop effective and ethical prompting habits—essential for productive AI use in business. From SEO to GEO: A New Battle for Visibility. Tool of the Week: OpenAI Prompt Generator inside ChatGPT (for Pro users) |
5. AI Applications in Business
Sep 29 8am .. 10:45am
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) |
6. Topic: AI in Marketing and Customer Service
Oct 6 8am .. 10:45am
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 |
7. Prompt Engineering Reflection
Oct 13 8am .. 10:45am
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. |
8. E-commerce and Online Business Models
Oct 20 8am .. 10:45am
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 |
9. Data Privacy and Ethics in AI
Nov 3 8am .. 10:45am
Description: Session 9 addresses data privacy and the ethical use of AI, engaging students in regulatory frameworks like GDPR and CCPA through 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 |
10. AI and Decision Making
Nov 10 8am .. 10:45am
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) |
11. Project Management in a Digital Environment
Nov 24 8am .. 10:45am
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) |
12. Future Trends in Digital Business
Dec 1 8am .. 10:45am
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) |
13. Final Project Workshop
Dec 8 8am .. 10:45am
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. |
14. Topic: Final Project Presentations
Dec 15 8am .. 10:45am
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. |