Artificial Intelligence and Corporate Communication

Università IULM

Course Description

  • Course Name

    Artificial Intelligence and Corporate Communication

  • Host University

    Università IULM

  • Location

    Milan, Italy

  • Area of Study

    Communication Studies

  • Language Level

    Taught In English

    Hours & Credits

  • Contact Hours

    48
  • Recommended U.S. Semester Credits
    3
  • Recommended U.S. Quarter Units
    4
  • Overview

    Course Goals 

    At the end of the course, the student should:

    • Understand the fundamental principles, generalizations, theories, and concepts of Artificial Intelligence (AI) and its application in corporate communication.
    • Understand the characteristics, needs, and constraints of internal and external communication processes managed through AI.
    • Understand the functioning of a company that uses AI for process management, communication, and content production.
    • Be able to apply AI knowledge to specific corporate communication problems.
    • Be able to select AI principles useful for solving communication problems.
    • Be able to use and explain the meaning of factual knowledge in the field of AI, such as terminology, classifications, and methods.
    • Be capable of using AI software for communication management and content production.
    • Be able to design AI-based communication strategies.
    • In addition, presentation activities will be proposed to the class to enhance the ability to speak in public and effectively communicate ideas.

    Course Objectives 

    • The essential content of the course will consist of an exploration of AI and its application in corporate communication. The contents will be structured as follows:
    • Introduction to generative AI and value creation for the company.
    • AI for process management, internal communication, and HR.
    • Impact of AI on the world of information (media system, journalism, etc.).
    • Stakeholder and reputation management through AI (analysis, message management).
    • AI and applications for Marketing.
    • AI, social media, platforms, and content creators.
    • "Augmented" events; ideation, management, and production through artificial intelligence.
    • Support in content production (AI for press releases, videos, social content).
    • Crowdsourcing and AI-based projects.
    • Data ownership and Privacy.
    • Transparency, ethics, and responsibility.
    • Evolutionary trends, risks, and opportunities.
    • Each topic will provide students with a comprehensive understanding of the role of AI in different aspects of corporate communication.

    Teaching Methods

    In line with the learning objectives of the "Artificial Intelligence and Corporate Communication" course, the teaching will be organized as follows:

    • Lectures: to present the key concepts of AI and its application in corporate communication.
    • Expert evidence: to provide students with a practical view of the use of AI in the real world, through the presentation of case studies and expert guests in the field.
    • Workshop activities: students will have the opportunity to apply the concepts learned through practical exercises and group projects. These activities could include designing AI-based communication strategies, using AI software for communication management and content production, and discussing ethical and legal issues related to AI.
    • Teamworking and focus groups: to promote collaboration and discussion among students, thus enhancing their all-round skills.
    • These teaching methods aim to provide students with a comprehensive and practical understanding of AI in corporate communication.

    Assessment

    The assessment of learning for the "Artificial Intelligence and Corporate Communication" course will consist of the following:

    • The exam will consist of a written test composed of open-ended questions, lasting 60 minutes (75 minutes for SLD students). The result of the written test is evaluated out of thirty.
    • Group projects will be carried out that will contribute to the acquisition of the overall grade. Students not participating in such work can alternatively be evaluated on the application and study of a supplementary part supported by bibliographic references or other multimedia supports.
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