INVESTIGATING THE NEXUS BETWEEN ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING TECHNOLOGIES IN THE CASE OF INDIAN SERVICES INDUSTRY Cover Image

INVESTIGATING THE NEXUS BETWEEN ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING TECHNOLOGIES IN THE CASE OF INDIAN SERVICES INDUSTRY
INVESTIGATING THE NEXUS BETWEEN ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING TECHNOLOGIES IN THE CASE OF INDIAN SERVICES INDUSTRY

Author(s): Mithun S. Ullal, Pushparaj M. Nayak, Ren Trevor Dais, Cristi Spulbăr, Ramona Birau
Subject(s): National Economy, Human Resources in Economy, ICT Information and Communications Technologies
Published by: Vilnius Gediminas Technical University
Keywords: Artificial Intelligence (AI); machine learning; human intelligence; big data; robots; automation; service sector; consumer;

Summary/Abstract: The future in the services industry belongs to Artificial Intelligence (AI) driven machines, which is a major source of worry for the job market in India. Over 50% of India’s GDP constitutes services, and it is a major source of employment for the skilled manpower of India. The research measures the impact of AI on service jobs in India based on qualitative parameters such as logical, natural, physical, and compassion; and finds which aspect serves the jobs better between machines and humans. The jobs taken over by AI are primarily at the task level more than the job level and for the basic tasks predominantly. The replacement starts with the basic tasks involved in providing service and then it grows to perform all the tasks involved in services. The research finds out that the logical aspects of the service will slowly reduce in the coming 5–10 years as AI will perform all the logic-related tasks leaving more emotional tasks such as compassion for humans. Finally, even these emotional-related tasks will be taken over by the AI which provides us with a very interesting combination of man and machine in the Indian scenario still threatening human employment.

  • Issue Year: 23/2022
  • Issue No: 2
  • Page Range: 323-333
  • Page Count: 11
  • Language: English