AI-enabled dynamic capabilities for transforming digital business models to smart business models

AI as the most important general-purpose technology of the day with its innumerable possibilities is on its way to become a key technology for the digital transformation. Algorithms especially for ML usually perform various tasks outstandingly. Hybrid models of AI, if put into business models, would help in improving the match making between actors of the ecosystems.

However, many aspiring digital platforms lack effective strategies to establish profitable digital business models. Emerging digital healthcare market is shifting from traditional hospital-centric care to a more virtual, and personalized care that heavily leverages the latest technologies around AI, DL, DA, genomics, home-based healthcare, robotics, and three-dimensional printing of tissue and implants.

This emerging digital healthcare market requires a profound, yet little understood perspective of transformation of digital business model by identifying the AI-enabled dynamic capabilities that could serve as a strong competitive differentiator. This understanding would help in value capture and value creation for companies who are developing digital platform to pull insights from data, and secure competitive advantage.

The aim of this dissertation is to identify the AI-enabled dynamic capabilities that companies need for the transformation of their digital business models to smart business models in the emerging digital healthcare market.

The findings of the study reveal that orchestration as one of the AI-enabled dynamic capabilities could be categorized as Capability to install desired information behaviors and values, Leadership capabilities, Capability to develop appropriate information management processes, and Information analytics capabilities. Also, these dynamic capabilities could be categorized as assisting, augmenting, and automating meaning that taking specific orchestrator roles (e.g., operational role implementation or role switching, role augmentation, and role automation).

These three important observations are aligned with the preceding discussions in the literatures and utilizing them would explicate how different types of dynamic capabilities allow orchestrators to adopt different roles and succeed in conducting the focal activities of a company.

However, the goal of this study is not to integrate or bridge specific paradigms, but to identify the AI-enabled dynamic capabilities. So, this dissertation further argues and conclude that the digital business model is a higher-level strategic AI-enabled dynamic capability that can serve as a tool for sensing, seizing, and transforming in the company business ecosystems through opportunity exploration and exploitation, value creation and capture, advantage exploration and exploitation functions to respond to the company’s digital business model transformation. Businesses can move along these two identified AI-enabled dynamic capabilities (digital business model itself and orchestration) for the transformation of their current digital business models from AI perspective and target smart business model vision in the emerging digital healthcare market.

Effective and efficient implementation of AI in the transformation of the companies’ digital business models would enhance the competitiveness of many businesses. However, it won’t help some other businesses drive value, opportunity, and advantage by improving the process through automation to win the market. In most cases, AI augments rather than replacing the human effort.