Effective integration of artificial intelligence: key axes for business strategy

Abstract

Purpose

This paper aims to explore the dimensions that foster the effectiveness of artificial intelligence (AI) within a business strategy.

Design/methodology/approach

The paper reviews recent contributions to AI and business success and identifies the key pillars that support the achievement of good results.

Findings

The paper proposes that there are four critical dimensions for developing an effective business strategy with AI. This research finds that AI has the potential to drive significant development when it is leveraged along four main axes: a focused strategy for AI, knowledge of the customers, effective interactions with customers and effective implementation of AI. These four dimensions are essential for nurturing the critical dimensions of AI that enable successful integration with the business strategy. To achieve this integration, the business strategy must take advantage of the insights and capabilities provided by AI while also understanding and deeply knowing the customers through effective interactions with them. The development is structured in an organizational alignment where AI helps employees and learns from them. By continuously learning from the exploitation of knowledge and big data, the organization can enrich its use of AI.

Research limitations/implications

The paper identifies four pillars of AI integration with the development of business strategy as areas for further empirical analysis by business researchers.

Practical implications

This paper offers strategies for managers and professionals to effectively integrate AI into business strategy.

Originality/value

The authors provide a novel perspective on using AI in business strategy by identifying four key axes of success in the current business landscape.

Citation

Alet, J. (2024), "Effective integration of artificial intelligence: key axes for business strategy", Journal of Business Strategy, Vol. 45 No. 2, pp. 107-114. https://doi.org/10.1108/JBS-01-2023-0005