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Artificial Intelligence for Business: From Idea to Implementation

This MOOC teaches participants how to strategically apply AI as part of a broader digital innovation journey, transforming promising opportunities into practical, value-generating organizational solutions.

   
    

Course description

This course is designed to equip non-technical professionals with the knowledge and frameworks needed to lead AI readiness initiatives within their organizations. Participants will explore how to evaluate AI technologies, develop strategies for responsible adoption, and establish governance practices that support sustainable and effective implementation.

Recognizing the rapidly evolving nature of the AI landscape, the course provides a strong foundational understanding of key concepts, opportunities, and limitations. Participants will learn to distinguish between technological hype and practical applications, assess organizational preparedness for AI adoption, and apply a structured, critical approach to the selection, implementation, and governance of AI systems.

By the end of the course, participants will be better prepared to make informed decisions about AI, contribute to organizational AI strategy, and help ensure that AI initiatives generate meaningful and measurable business outcomes.

The course is divided into four modules, guiding participants through a structured learning path to understand AI fundamentals and its business applications.

The course is divided into four modules, guiding participants through a structured learning path to understand AI fundamentals and its business applications.

Module 1 – AI FUNDAMENTALS

  • Introduction to the fundamentals of AI and clarification of the differences between traditional AI and generative AI
  • Focus on the principle of the right tool for the right job
  • Exploration of AI use cases, using examples from real-world organizations
  • Addressing the challenge of translating promising technologies into effective solutions

Module 2 – AI STRATEGY

  • Presentation of the AI innovation journey: from early exploration to use cases
  • AI innovation simulation: practice in launch and scouting processes
  • AI innovation simulation: identifying business priorities
  • AI innovation simulation: identifying use cases

Module 3 – AI IMPLEMENTATION

  • Exploration of the AI implementation lifecycle
  • Comparison of different implementation approaches: make, buy or hybrid
  • Analysis of the evolving market for AI tools and platforms
  • Strategizing the choice and combination of AI tools

Module 4 – AI GOVERNANCE

  • Review of AI-related risks: technical, organizational and reputational
  • Breakdown of competencies, structures and governance required for AI
  • Summary of key takeaways into an AI innovation framework for organizations in the design an effective AI innovation approach

Each module includes videos, video transcripts, interactive activities, infographics, readings, and self-assessment quizzes.

Total workload of the course: 50 hours

This MOOC was produced as part of the Edvance project – Digital Education Hub per la Cultura Digitale Avanzata. The project is funded by the European Union – Next Generation EU, Component 1, Investment 3.4 “Didattica e competenze universitarie avanzate".

EDDIE, Edvance
bocconi
Finanziato EU MUR, Ministero Università e Ricerca Italia Domani Edvance

Intended Learning Outcomes

By actively participating in this MOOC, you will achieve different intended learning outcomes (ILOs).

  1. Differentiate between traditional AI and Generative AI technologies, and match specific AI capabilities to appropriate business use cases.
  2. Correctly sequence and execute all phases of the AI innovation journey, including scouting, identifying business priorities, and prioritizing use cases.
  3. Analyze business scenarios and recommend appropriate AI implementation approaches (make, buy, or hybrid) based on organizational context, resources, and strategic priorities.
  4. Recognize common AI implementation challenges in real-world scenarios and propose evidence-based mitigation strategies.
  5. Develop a comprehensive AI governance framework that addresses risks, competencies, and organizational structures to sustain AI innovation.

Prerequisites

No prerequisites are required to participate in this course.

Activities

Throughout the course, you will find activities to help consolidate your understanding, to practice translating abstract concepts into practical applications in the real-world, and to hone your skills in assessing AI tools and applications with a critical eye and from a managerial perspective.
Furthermore, at the end of each week, you will encounter a Reflection Point, designed to let you check that you have indeed learned to:

  • evaluate AI technologies
  • develop strategies for responsible AI adoption within organisations
  • establish governance practices that support sustainable and effective AI implementation.

Section outline

  • Week 0 - Introduction to Artificial Intelligence for Business

    Content available if you are enrolled in this course

  • Week 1 - Artificial Intelligence for Business: AI Fundamentals

    In week one of the course 'Artificial Intelligence for Business: from idea to implementation', we take a comprehensive look at the fundamentals of Artificial Intelligence, emphasizing the critical distinctions between traditional AI and generative AI.
    Another key focus of week one is the principle of selecting the right tool for the right job. That means understanding the unique capabilities and limitations of various AI technologies - essential for effective implementation.
    Moving from theory to concrete real-world use cases, we'll discover how leading organizations from a wide spectrum of industrial sectors selected and implemented AI into their operations, giving insights into best practices and potential pitfalls in AI adoption.
    Finally, in week one, we'll take an objective look at the very real challenge of translating promising technologies into effective solutions. By equipping participants with the knowledge and tools to navigate these challenges, the aim is to empower course participants to lead their organizations in harnessing the full potential of AI technologies.

    Content available if you are enrolled in this course

  • Week 2 - Artificial Intelligence for Business: AI Strategy

    During week two of the course, participants will be led through the various stages of AI innovation, starting from the initial exploration of AI technologies and concepts to the practical application of these technologies in real-world business scenarios. Participants will learn how to identify potential opportunities for AI integration within their organizations and understand the critical steps involved in transforming innovative ideas into actionable use cases.
    This will be followed by a three-phase simulation, providing participants with the opportunity to engage in practical exercises focused first on the launch and scouting processes of AI initiatives, then on the identification of business priorities through the evaluation of organizational goals, market demands, and resource availability, and, finally, on the identification of use cases within an organisation.
    By the end of this simulation, participants will be equipped with the skills to articulate clear and actionable AI use cases that align with their organization's strategic vision.

    Content available if you are enrolled in this course

  • Week 3 - Artificial Intelligence for Business: AI Implementation

    In week three of the course, we'll examine the AI implementation lifecycle as an essential step in integrating AI solutions successfully into business operations.
    We'll do this by comparing different implementation approaches—make, buy, or hybrid—which will provide us with insights into the strategic decisions organizations must make.
    Also, in week three, we'll explore the ever-evolving market for AI tools and platforms, since an understanding of these market dynamics is crucial for organizations to make informed decisions about which tools to adopt and how to integrate them effectively.
    Finally, we'll see how strategizing the choice and combination of AI tools involves evaluating organizational needs, existing infrastructure, and long-term goals, without losing sight of the strengths and limitations of various AI solutions and the potential challenges in implementation.

    Content available if you are enrolled in this course

  • Week 4 - Artificial Intelligence for Business: AI Governance

    In the final section of the course - week four - we'll spend some time looking at AI-related risks to organisations, including technical challenges, organizational issues, and reputational risks from ethical concerns and public perception.
    We'll then break down the essential competencies, organizational structures, and governance frameworks needed for effective AI implementation within a company, before, finally, summarizing the key takeaways that capture the critical elements of an AI innovation framework for organizations.

  • Final Quiz

    Content available if you are enrolled in this course

  • Open Badge

    Content available if
    • the activity Introduction to the course is marked complete
    • the activity AI Fundamentals is marked complete
    • the activity AI Strategy is marked complete
    • the activity AI Implementation is marked complete
    • the activity AI Governance is marked complete
    • The activity Final Quiz is complete and passed
    • the activity Final survey is marked complete

  • Additional resources

    • Folder icon
      Video transcripts Folder
      Content available if you are enrolled in this course

Assessment

Your final grade for the course will be based on the results of your answers to the assessed quizzes. You have an unlimited number of attempts at each quiz, but you must wait 15 minutes before you can try again. You will have successfully completed the course if you score 60% (or higher) in each one of the assessed quizzes. The maximum score possible for each quiz is given at the beginning of the quiz. You can view your score in the quiz on your last attempt or on the 'Grades' page.

Certificate

You can achieve a certificate in the form of an Open Badge for this course, if you reach at least 60% of the total score in each one of the assessed quizzes and fill in the final survey. 

Once you have completed the required tasks, you will be able to access ‘Get the Open Badge’ and start issuing the badge. Instructions on how to access the badge will be sent to your e-mail address. 

The Badge does not confer any academic credit, grade or degree.  

Information about fees and access to materials

The course is delivered in online mode and is available free of charge.

Course faculty

Name Surname

Lorenzo Diaferia

lorenzo.diaferia@sdabocconi.it

Lecturer, SDA Bocconi School of Management

Recent publications
DE ROSSI L., DIAFERIA L.Dall’hype tecnologico alla realtà: l’applicabilità a tre dimensioniEconomia & Management, 2024, no. 4, pp.19-26
DIAFERIA L., DE ROSSI L., SALVIOTTI G., AI Management. Strategie e Approcci in AziendaEgea, Milano, Italia, 2024
ARMENI P., POLAT I., DE ROSSI L., DIAFERIA L., MEREGALLI S., GATTI A., Exploring the potential of digital therapeutics: An assessment of progress and promiseDigital Health, 2024, vol.10
DIAFERIA L., Qui la penna, ChatGPT! L’AI generativa alla prova del testoEconomia & Management, 2023, no. 3, pp.72-77
ARMENI P., POLAT I., DE ROSSI L., DIAFERIA L., MEREGALLI S., GATTI A., Digital Twins in Healthcare: Is It the Beginning of a New Era of Evidence-Based Medicine? A Critical ReviewJournal of Personalized Medicine, 2022, vol.12, no. 8, pp.1255
CENNAMO C., DIAFERIA L., GAUR A., SALVIOTTI G., Assessing Incumbents’ Risk of Digital Platform DisruptionMIS Quarterly Executive, 2022, vol.21, no. 1, pp.55-74

Michele Russo

Michele Russo

michele.russo@sdabocconi.it

Fellow, SDA Bocconi School of Management

Recent publications
RUSSO M., PRIX S., GOERGEN J., DE BELLIS E., The 3 Types of Customers Who Buy Smart Products—and How to Market to ThemHarvard Business Review, 4 Novembre, 2025
GABBI G., TONINI D., RUSSO M.A Novel Supervised-Unsupervised Approach for Past-Due PredictionRisk Management Magazine Aifirm, 2024, vol.19, no. 02, pp.4-21
CASELLI S., GABBI G., DE ROSSI L., ABBATEMARCO N., RUSSO M., MORETTI S., For a digital euro that citizens will embrace - Per un euro digitale che piaccia ai cittadini2025, SDA Bocconi Insight, Milano, Italia
TAVA L. V., RUSSO M.IDRO - Negotiation Exercise2023, The Case Centre, Gran Bretagna

Contact details

If you have any enquiries about the course or if you need technical assistance please contact pok@polimi.it. For further information, see FAQ page.

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