Evaluating The Opportunities and Risks of Artificial Intelligence In Strategic Management and Business Integration

Raghvendra; Tulika Saxena; Devesh Ranjan Tripathi; Rashi Jain

doi:10.69968/ijisem.2024v3si219-24

Authors

Raghvendra Research Scholar, Department of Business Administration Mahatma Jyotiba Phule Rohilkhand University, Bareilly, Uttar Pradesh India
Tulika Saxena Head & Dean, Faculty of Management Mahatma Jyotiba Phule Rohilkhand University, Bareilly, Uttar Pradesh India
Devesh Ranjan Tripathi Associate Professor, Business Management, School of Management Studies, UP Rajarshi Tandon Open University, Prayagraj, Uttar Pradesh
Rashi Jain Research Scholar MBA (Gold Medalist) Department of Business Administration Mahatma Jyotiba Phule Rohilkhand University, Bareilly, Uttar Pradesh India

DOI:

https://doi.org/10.69968/ijisem.2024v3si219-24

Keywords:

Artificial intelligence, machine learning, strategic management, business integration, crisis management, innovation, business competitiveness, predictive analysis, Big Data, CRM systems, process optimization, data quality, risk mitigation

Abstract

This study investigates the evolving trends and potential applications of artificial intelligence (AI) in strategic management, particularly under crisis conditions, to stabilize and enhance business competitiveness. It delves into the various areas where AI can be applied in business process management, with a special focus on how innovations driven by machine learning affect the strategic aspects of company operations. The research provides recommendations for securing competitive advantages and optimizing the use of limited resources.

The analysis demonstrates the positive impact of AI-driven innovations on business profitability, highlighting the key benefits of AI technologies and the factors propelling their growth. The study examines the role of AI in predictive analysis, aimed at improving strategic management and overall business performance. It also assesses AI's capability to enhance marketing and management functions, and its effectiveness in using Big Data to analyze competitive markets and customer behavior. The synergy between AI and modern CRM systems is explored, emphasizing how AI and machine learning can deliver a personalized customer experience, even amid changing conditions.

Furthermore, the paper addresses the key methods for integrating AI into enterprise business models during crises. It reviews the processes and principles of AI adoption within company operations, identifies critical data quality metrics to mitigate risks associated with innovation, and defines the conditions necessary for leveraging AI technologies to create competitive advantages. This enables businesses to swiftly adapt to the negative impacts of external environmental factors on established processes

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