Creator
Michel MalaraMBA (PhD in AI, Cand.)
Michel Malara teaches how an organisation governs AI in practice: who decides, who carries the accountability, and how that is written into leadership routines. His doctoral research at Signum Magnum College examines AI-supported decision and steering logic in DACH organisations, and produced the SFV model, linking algorithmic steering, ethical reflection and organisational accountability, validated with fsQCA and quantitative methods. He has run his own HR consultancy since 1996, covering HR strategy, executive search and AI-supported talent management. He lectures at Swiss professional schools in leadership and HR management, and holds an MBA and the SVEB-1 teaching qualification.
- Based in
- Zug, Switzerland
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Background
Experience and context
Education and professional work that shape this creator's modules.
Education
- Doctoral candidate in Artificial Intelligence, Signum Magnum College
Enrolled November 2023, with completion planned for December 2026. Classified at EQF level 8.
- Master of Business Administration
MBA; SVEB-1 (2024).
Industry
- More than 25 years of entrepreneurial leadership and organisational development
Über 25 Jahre unternehmerische Verantwortung, People Leadership und strategische Organisationsentwicklung.
Workshops
- Designs executive education formats and speaks on AI governance
Entwirft skalierbare Executive-Education-Formate; Speaker.
Certifications
- SVEB-1 certificate in adult education, 2024
The Swiss entry qualification for course leaders and trainers working with adult learners.
Career
- Lecturer and mentor at Swiss professional schools
Teaches accounting, leadership, business administration, economics, human resources and financial management at HSO Wirtschafts- und Informatikschule, and HR management at SIU Schweizerisches Institut für Unternehmerschulung.
- Runs his own HR consultancy since 1996
mp-beratung GmbH works on HR strategy, executive search and recruiting, employer branding, and AI-supported talent management.
Regulatory
- AI governance model built for regulated and hybrid organisations
The SFV model is written for settings where an AI-supported decision has to withstand internal review, with an owner named for every step.