International Journal on Media Management

Media Management Education in the Age of Artificial Intelligence: Curricula, Pedagogies and Partnerships

Background and Rationale

Media management education has expanded worldwide over the past two decades. Programmes at undergraduate and graduate level now exist across the globe, spanning departments of communication, media studies and journalism as well as business schools and interdisciplinary units. After this long phase of growth, however, the field seems to have entered a period of consolidation. Student numbers are stagnating or declining in several countries, and the question is no longer whether media management should be taught, but which knowledge domains, competencies and thematic priorities are appropriate, in which formats they are best delivered, and by whom.

These questions have become urgent because the industries that media management programmes prepare students for are themselves being restructured by artificial intelligence and further digital transformation in general. Generative and analytical AI is transforming content creation, distribution, audience measurement, advertising, product development and the organisation of creative work. Job profiles are being redefined, some roles are disappearing, and new ones demand a combination of managerial judgement, data literacy, technological understanding and critical reflection. At the same time, AI has entered the classroom, changing how students learn, how instructors teach and assess, and what kinds of academic work remain meaningful.

Recent comparative research on media management curricula shows that programmes acknowledge digital transformation but frequently address technological and societal challenges in a fragmented way. Curricular patterns cut across national boundaries, yet the causes of these patterns, the didactic formats through which they are delivered, and their fit with a labour market reshaped by AI remain largely unexplored.

This special issue invites contributions on what is taught in media management and related fields, on how it is taught, and on the institutional and industry constellations within which teaching takes place, with a particular emphasis on the role of AI in all three dimensions. We welcome work from all disciplinary perspectives also beyond media management and economics.  

Aims and Scope

The special issue seeks to showcase research that examines media management education along three interrelated dimensions:

·      What is taught: curricular content, knowledge domains, competencies and learning outcomes, and their alignment with the evolving requirements of media and creative industries.

·      How it is taught: didactic formats, pedagogical approaches, assessment practices and learning technologies, including the use of AI as a teaching and learning tool.

·      In which constellations it is taught: institutional settings, disciplinary affiliations, partnerships with industry, professional bodies and other stakeholders, and the wider ecosystem of formal, executive and continuing education.

Across these dimensions, the special issue places particular emphasis on artificial intelligence in three respects: AI as a subject and tool of teaching; the competencies that media managers need in times of AI; and the transformation of the academic field itself as AI-driven change in media industries alters student demand, programme portfolios, faculty roles and the relationship between academia and practice.

We invite conceptual, empirical, comparative, historical, methodological and critical contributions, as well as rigorously documented case studies and evaluations of teaching innovations. Cross-national and cross-institutional comparisons, studies from regions beyond Europe and North America, and work that connects educational research with media management scholarship are especially encouraged. 

Specific Areas of Interest

Topics of interest for this special issue include, but are not limited to, the following:

Curricula, content and competencies

·      Comparative analyses of media management curricula across countries, degree levels, institutional types and disciplinary traditions

·      The evolution of media management as a taught subject and its relationship to media economics, journalism, communication and business education

·      Curriculum development as a social process: stakeholders, accreditation, quality management and the politics of curricular change

·      Integration of data literacy, quantitative methods, coding and computational thinking into media management programmes

·      Coverage of platforms, algorithms, datafication, sustainability, ethics and regulation in curricula

·      Alignment and misalignment between curricular content and labour-market requirements in media and creative industries

Didactic formats and pedagogy

·      Project-based, problem-based, studio and experiential learning in media management education

·      Case teaching, simulations, serious games, hackathons and entrepreneurship formats

·      Assessment practices and learning outcomes in media management programmes, including their validity in an AI-saturated environment

·      Online, hybrid and lifelong-learning formats, micro-credentials and executive education

·      Evaluations of teaching innovations and their effects on student learning and employability

Constellations and partnerships

·      Models of collaboration between universities and media companies, agencies, start-ups, public service media and industry associations

·      Industry involvement in curriculum design, teaching, mentoring, internships and capstone projects, and the tensions this may create with academic autonomy

·      Media management education outside traditional degree programmes: corporate academies, professional training, incubators and continuing education

·      Interdisciplinary and cross-faculty programme designs (e.g. media and computer science, media and business, media and design)

·      Institutional positioning of media management within universities and the consequences for content, staffing and student recruitment

AI in teaching and learning

·      Uses of generative and analytical AI as tools for teaching, tutoring, feedback, assessment and course design in media management education

·      Student and faculty practices, attitudes and literacies regarding AI, and their implications for academic integrity and learning quality

·      Teaching AI as a subject: strategy, business models, ethics, governance and the economics of AI in media industries

·      Didactic frameworks and institutional policies for integrating AI into programmes

Competencies in times of AI

·      Which competencies media managers need when AI automates or augments creative, analytical and managerial work

·      Meta-competencies such as critical thinking, adaptability, judgement, self-reflection and ethical reasoning as complements to technical skills

·      Employer expectations, graduate trajectories and changing job profiles in AI-transformed media organisations

·      Competency frameworks and their translation into learning outcomes, modules and programme structures

Transformation of the academic field

·      How AI-driven change in media industries affects demand for media management programmes, programme portfolios and institutional strategies

·      Changing roles of faculty, the academic labour market and the research-teaching nexus in media management

·      Consolidation, closure and repositioning of programmes, and the future identity of media management as an academic field

·      Historical, epistemological, cultural and media-system explanations of national and institutional differences in media management education

·      Scenarios and normative visions for the future of media management education