As escolas de gestão são, na sua maioria, cautelosas a adoptar e a adequar-se às necessidades prementes de estudantes, trabalhadores e organizações para o trabalho no futuro.
Isso gera uma questão essencial: como é que os MBAs de hoje a serem ensinados com métodos do passado terão lugar nos empregos do futuro?
A questão é apontada por Anne Trumbore, directora senior da Wharton Online, na Wharton School of the University of Pennsylvania, e uma das co-autoras do estudo “Implications of Artificial Intelligence on Business Schools and Lifelong Learning”.
A “grande ameaça” da inteligência artificial (IA) para as instituições será “a relevância do MBA” e o seu respectivo valor, nomeadamente na formação em tópicos e capacidades que as organizações não são internamente capazes de suprir.
Para sobreviverem neste ambiente dinamizado pela IA, as escolas devem ter:
– New methods of knowledge creation that speed up the research cycle. Working with industry data and collaborating with industry experts for teaching and research, collaborating with other schools such as engineering, computer science, education or medical schools, and finding alternative, reputable outlets for publication beyond peer reviewed academic journals all promise to make relevant content more quickly.
– More data-driven, personalized and effective learning experiences for students. Future MBA candidates will be exposed to AI-enabled education K-12, at university or in the workplace. It is reasonable to assume that they will have similar expectations of business education — and that it will be customizable, adaptive and immersive — and delivered both inside and outside the classroom.
– Taking AI technologies seriously and making related investments. Since most business schools will be unable to devote the necessary resources to develop their own AI capabilities, it will be critical to partner with technology vendors to provide personalized learning experiences that support existing students and offer alumni and others relevant lifelong learning.
– Immediately addressing AI’s challenges: ethics, privacy, quality of training data, transparency of algorithms and data security. Rather than letting AI’s risks become a barrier to adoption, business schools can take the lead on developing a coalition for shared governance, empowering faculty, talented staff, students, and experts to work together to develop school and university policies and solutions to address these concerns. Creating a coalition of business schools is another option to explore, as is working with government policymakers to develop sustainable and thoughtful solutions.