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Article summary:
1. AI technology can provide the foundation for successful digital servitization and business model innovation, but it requires more than just spending money on digital infrastructure, technologies, and data.
2. There is a need to further understand how AI capabilities can be developed in manufacturing firms and how AI can be used to drive business model innovation on a larger scale.
3. AI holds the potential to provide multiple business model benefits for customers such as cutting costs, enhancing the quality of services, increasing coordination and productivity, and boosting delivery efficiencies.
Article analysis:
The article “How AI Capabilities Enable Business Model Innovation: Scaling AI Through Co-Evolutionary Processes and Feedback Loops” by Elsevier Enhanced Reader provides an overview of how Artificial Intelligence (AI) technology can be used to create value for customers through digital servitization and business model innovation. The article is well-written and provides a comprehensive overview of the topic with relevant examples from research studies. However, there are some areas where the article could have been improved upon in terms of trustworthiness and reliability.
First, the article does not explore any counterarguments or alternative perspectives on the use of AI technology for business model innovation. While it does mention that there are challenges associated with integrating AI into value creation activities, it does not discuss any potential risks or drawbacks associated with using this technology. Additionally, while the article mentions that executives often have high expectations for AI that exceed their companies’ capabilities, it does not provide any evidence or examples to support this claim.
Second, while the article does provide some insights into how firms can develop their AI capabilities in order to benefit from digitalization and AI technology, it does not discuss any strategies or best practices for doing so. Furthermore, while it mentions that data competencies and analytics capabilities are important for successful implementation of AI at scale, it does not provide any details about what these competencies entail or how they should be developed within an organization.
Finally, while the article provides some examples of how firms can leverage new ways of creating value through their use of AI technology (e.g., cutting costs), it fails to mention any other potential benefits such as increased customer satisfaction or improved customer experience that may result from using this technology in business models.
In conclusion, while this article provides a comprehensive overview of how businesses can use Artificial Intelligence (AI) technology to create value through digital servitization and business model innovation, there are some areas where its trustworthiness and reliability could have been improved upon by exploring counterarguments or alternative perspectives on the topic as well as providing more details about developing data competencies within organizations and other potential benefits associated with using this technology in business models.