AI-Capability Assessment Model

Thomas Butler; Angelina Espinoza; Selja Seppälä

AI-Capability Assessment Model

Thomas Butler
, Angelina Espinoza
, Selja Seppälä

Cork University Business School

University College Cork

Research output: Other output › peer-review

Abstract

The comprehension and adoption of artificial intelligence (AI) is beset with practical as well as ethical problems. This project presents a 5-level AI Capability Assessment Model (AI-CAM) and a related AI Capabilities Matrix (AI-CM) aimed at assisting practitioners in AI comprehension and adoption.

The AI-CAM is composed of 12 tables, of which 4 are in a reader-friendly format:

the AI-CAM Level Criteria table, which defines the capability requirements that an organization should fulfil to achieve its AI comprehension and adoption objectives;
the AI Capability Assessment Model (AI-CAM): Core Areas, which provides guidance on the core areas, including capabilities (i.e., knowledge and skills), required at different stages and levels in AI comprehension and adoption;
the AI Proficiency Levels, which defines three levels of AI proficiency corresponding to the level of interaction with AI technologies for different types of roles within an organization;
the AI Capabilities Matrix, which details the individual and team-level capabilities needed to reach each level in organizational AI capability.
The remaining 8 tables contain the information in a coded format.

These 12 AI-CAM tables are presented as separate tabs in the AI-CAM_2021-03-04.xlsx file.

Original language	English (Ireland)
Publication status	Published - 2021

Cite this

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title = "AI-Capability Assessment Model",

abstract = "The comprehension and adoption of artificial intelligence (AI) is beset with practical as well as ethical problems. This project presents a 5-level AI Capability Assessment Model (AI-CAM) and a related AI Capabilities Matrix (AI-CM) aimed at assisting practitioners in AI comprehension and adoption. The AI-CAM is composed of 12 tables, of which 4 are in a reader-friendly format: the AI-CAM Level Criteria table, which defines the capability requirements that an organization should fulfil to achieve its AI comprehension and adoption objectives; the AI Capability Assessment Model (AI-CAM): Core Areas, which provides guidance on the core areas, including capabilities (i.e., knowledge and skills), required at different stages and levels in AI comprehension and adoption; the AI Proficiency Levels, which defines three levels of AI proficiency corresponding to the level of interaction with AI technologies for different types of roles within an organization; the AI Capabilities Matrix, which details the individual and team-level capabilities needed to reach each level in organizational AI capability. The remaining 8 tables contain the information in a coded format. These 12 AI-CAM tables are presented as separate tabs in the AI-CAM\_2021-03-04.xlsx file.",

author = "Thomas Butler and Angelina Espinoza and Selja Sepp{\"a}l{\"a}",

year = "2021",

language = "English (Ireland)",

type = "Other",

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T1 - AI-Capability Assessment Model

AU - Butler, Thomas

AU - Espinoza, Angelina

AU - Seppälä, Selja

PY - 2021

Y1 - 2021

N2 - The comprehension and adoption of artificial intelligence (AI) is beset with practical as well as ethical problems. This project presents a 5-level AI Capability Assessment Model (AI-CAM) and a related AI Capabilities Matrix (AI-CM) aimed at assisting practitioners in AI comprehension and adoption. The AI-CAM is composed of 12 tables, of which 4 are in a reader-friendly format: the AI-CAM Level Criteria table, which defines the capability requirements that an organization should fulfil to achieve its AI comprehension and adoption objectives; the AI Capability Assessment Model (AI-CAM): Core Areas, which provides guidance on the core areas, including capabilities (i.e., knowledge and skills), required at different stages and levels in AI comprehension and adoption; the AI Proficiency Levels, which defines three levels of AI proficiency corresponding to the level of interaction with AI technologies for different types of roles within an organization; the AI Capabilities Matrix, which details the individual and team-level capabilities needed to reach each level in organizational AI capability. The remaining 8 tables contain the information in a coded format. These 12 AI-CAM tables are presented as separate tabs in the AI-CAM_2021-03-04.xlsx file.

AB - The comprehension and adoption of artificial intelligence (AI) is beset with practical as well as ethical problems. This project presents a 5-level AI Capability Assessment Model (AI-CAM) and a related AI Capabilities Matrix (AI-CM) aimed at assisting practitioners in AI comprehension and adoption. The AI-CAM is composed of 12 tables, of which 4 are in a reader-friendly format: the AI-CAM Level Criteria table, which defines the capability requirements that an organization should fulfil to achieve its AI comprehension and adoption objectives; the AI Capability Assessment Model (AI-CAM): Core Areas, which provides guidance on the core areas, including capabilities (i.e., knowledge and skills), required at different stages and levels in AI comprehension and adoption; the AI Proficiency Levels, which defines three levels of AI proficiency corresponding to the level of interaction with AI technologies for different types of roles within an organization; the AI Capabilities Matrix, which details the individual and team-level capabilities needed to reach each level in organizational AI capability. The remaining 8 tables contain the information in a coded format. These 12 AI-CAM tables are presented as separate tabs in the AI-CAM_2021-03-04.xlsx file.

UR - https://github.com/tgbutler/AI-Capability-Assessment-Model-

M3 - Other output

ER -

AI-Capability Assessment Model

Abstract

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