Artificial Intelligence (AI) Capability

An Artificial Intelligence (AI) Capability is a cognitive capability related to AI technologies (such as AI system).

• Context:
  • It can be referenced by an AI Capability Roadmap.
  • It can range from being a AI-based System AI Capability to being an Organizational AI Capability.
  • …
• Example(s):
  • an AI-based System AI Capability , such as: AlphaGo's superhuman capability to win Go Games.
  • an Organizational AI Capability, such as a: Legal Tech company AI capability (for a LegalTech company).
  • …
• Counter-Example(s):
  • Human Intelligence Capability.
• See: Narrow AI, General AI, Exponential Growth in AI Capability.

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References

2023

• (Chowdhury et al., 2023) ⇒ S. Chowdhury, P. Dey, and S. Joel-Edgar. (2023). "Unlocking the Value of Artificial Intelligence in Human Resource Management Through AI Capability Framework.” In: Human Resource Management Review.
  • QUOTE: “We propose AI capability framework to develop resources, skillsets and strategies that will … Section 4 will present the AI capability framework summarising the findings of the review and …”
  • NOTE: It discusses the development of an AI capability framework to enhance resources, skillsets, and strategies in the domain of human resource management.

2023

• (Kumar et al., 2023) ⇒ P. Kumar, S.K. Sharma, and V. Dutot. (2023). "Artificial Intelligence (AI)-Enabled CRM Capability in Healthcare: The Impact on Service Innovation.” In: International Journal of Information Management.
  • QUOTE: “...a framework for AI-enabled CRM capability and service … AI-enabled CRM capability, CSF, and service innovation. This study explains the formation of AI-enabled CRM capabilities to fill …”
  • NOTE: It presents a framework for AI-enabled CRM capability in healthcare, detailing how such capabilities can facilitate service innovation.

2018

• (Davenport, 2018) ⇒ T.H. Davenport. (2018). "From Analytics to Artificial Intelligence.” In: Journal of Business Analytics.
  • QUOTE: “… in building their capabilities for artificial intelligence (AI). Many AI systems, however, are based on statistics and other forms of analytics. Companies can get a “running start” on AI by …”
  • NOTE: It explores the transition from analytics to artificial intelligence, emphasizing how companies can leverage their existing analytics infrastructure to advance in the field of AI.

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