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

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

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.

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

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

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

This paper aims to explore the dimensions that foster the accomplishment of goals of business ecosystems.

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

The paper suggests that entanglement with the customers, value sharing based on a holistic win-win approach, organizational entrepreneurship alignment and continuous smart learning are four dimensions of criticality for designing an effective business ecosystem. These four dimensions nurture the relationships between participants and external actors to make ecosystems successful. Entanglement with the customer is critical to the long-term relevance of the value proposition that reinforces companies’ relationships within the second pillar of value sharing in a win-win system. The development is structured in an organizational alignment where entrepreneurship is the engine, from the employees themselves to the largest corporations, and is enriched with continuous learning based on the exploitation of knowledge and big data.

The paper identifies a set of four pillars of business ecosystem design for further empirical analysis by ecosystem researchers.

The paper provides managers and professionals with strategies to develop effective growth within business ecosystems.

The authors contribute a fresh perspective to the business ecosystems literature by identifying four key pillars of success in the current business landscape.

This study aims to identify a new model of relative customer satisfaction translated into share of purchases (SOP) with the best-related metrics.

This study uses an online customer satisfaction survey to clients of a firm and with a comparative valuation with current competitors by customer. The model builds a weighting through a multiple regression analysis, obtaining β for each variable by relating the variables to the SOP, presenting the relative effect of the variables and the best global explanation of the model.

This new model has good prediction accuracy and shows a clear impact of different relative satisfaction indicators and, to a minor degree, business and relationship characteristics.

The main limitation of this model is that it is based on data from only one company, but it should have value in other sectors and provide full insight through its transversal application.

The involved advantages demonstrated better predictability and usefulness to decision-makers and determined how the improvements in customer satisfaction translate into business growth. The study shows that the relative evaluation of satisfaction carries different meanings for customers, while all of them are better than absolute satisfaction. It includes a more understandable indicator than other prior relative indicators, the difference in satisfaction and is more effective. Additionally, it guides how to take advantage of the knowledge of relative customer satisfaction before competitors and demonstrates the courses of action with the potential best results.