Challenges of artificial intelligence in business curriculum
Artificial Intelligence (AI) is becoming an important component of various sectors and in decision-making in various domains. Research in AI has seen tremendous growth, thanks to big data, escalated processing speed, and innovations in AI-based models. McKinsey Global Institute predicts that by 2030, at least 70 percent of companies will have to adopt at least one type of AI technology and around 60 percent of the current occupations will be automated in the next ten years. Recognizing the importance of AI in almost every field, many countries have regarded AI as a national priority. To promote AI and the research involved, the USA launched the American Artificial Intelligence Initiative in 2019. Out of eight national strategies in this initiative, one strategy is to “provide training and education in AI for the American workforce” (National Science & Technology Council, 2019).
When it comes to AI education, the subject is in great demand by students from engineering or technical background, working professionals who are keen to adopt newer skills, etc. However, it is still a challenge in academia to introduce this very complex and important area of technology to audiences beyond students wit computing and engineering backgrounds. It has been observed that engineering students do not hesitate in opting for AI-related courses, but students from b-schools do hesitate and at the same time hope to remain relevant in the age of AI. According to industrialists and corporates, students from b-schools who are also aspiring managers, if equipped with highly sought-after AI and relevant skills can enhance their chance of employment now and in the future. According to academic researchers, industrialists, and corporates, AI technologies are going to be present in almost every field in the future, therefore business professionals must become familiar with the principles on which these technologies function and also the risks they carry.
To prepare aspiring students for the era of AI, educators have felt the need and importance of this facet of technology and have started to incorporate AI training in higher education curricula. However, a survey of business school deans shows that many business and management schools are finding it difficult to incorporate AI training in business education. One of the biggest challenges that b-schools face is the task of curriculum development due to the lack of pedagogical resources. According to a review of some scholars, most of the textbooks in AI are written for technical audiences and very few are targeted at business audiences.
Moreover, in this field, new techniques, libraries, as well as models get developed very rapidly making it a worthy, yet daunting task to keep the pace with latest innovations. On the other hand, skipping out some of the fundaments for the sake of students, who get a holistic view of AI and machine intelligence, will shortchange them in the future. Looking at the current demand for business managers with AI skills, most of the elite b-schools in India have started to make AI part of their curriculum.
However, these courses often focus on introducing statistical models and machine learning models concerning data analysis and hardly prepare students for future work environments where diverse AI technologies are used. The selection of effective teaching methods in curriculum development is yet another open question that remains unanswered. It remains unclear if coding-related assignments should be required for AI courses targeting business students.
