
Automotive AI is at the forefront of rapidly disrupting the business consulting industry by revitalizing core issues in strategy formulation and management, innovation, and process improvement. This technology helps consultants solve problems by dealing with large amounts of material, thinking outside the box regarding business solutions, and optimizing processes at a higher level than before. Businesses can benefit from AI technology because AI models can make a deeper data analysis, automate processes, improve decision-making, and provide the setting for future improvement. In this paper, the author looks at the essence of applying generative AI in business consultants, particularly analyzing its value for enhancing strategic execution and organizational performance. The study focuses on case analyses and interviews with 20 consulting practitioners on the effective and ineffective practices of applying AI. Research indicates that although generative AI POSs have enormous value for enhancing consulting models, there are challenges that organizations can observe, such as ethical issues and the requirement for specialized knowledge. This paper will make general recommendations for organizations interested in deploying AI at its full potential, discussing the proper and improper ways of AI integration.
AI Revolution, Generative AI, AI Solutions, AI Adoption, Ethical Issues
AI Revolution, Generative AI, AI Solutions, AI Adoption, Ethical Issues
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
