Towards a Capability Assessment Model for the Comprehension and Adoption of AI in Organisations
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ID: 283224
2023
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Abstract
The comprehension and adoption of Artificial Intelligence (AI) are beset with
practical and ethical problems. This article presents a 5-level AI Capability
Assessment Model (AI-CAM) and a related AI Capabilities Matrix (AI-CM) to
assist practitioners in AI comprehension and adoption. These practical tools
were developed with business executives, technologists, and other
organisational stakeholders in mind. They are founded on a comprehensive
conception of AI compared to those in other AI adoption models and are also
open-source artefacts. Thus, the AI-CAM and AI-CM present an accessible
resource to help inform organisational decision-makers on the capability
requirements for (1) AI-based data analytics use cases based on machine
learning technologies; (2) Knowledge representation to engineer and represent
data, information and knowledge using semantic technologies; and (3) AI-based
solutions that seek to emulate human reasoning and decision-making. The AI-CAM
covers the core capability dimensions (business, data, technology,
organisation, AI skills, risks, and ethical considerations) required at the
five capability maturity levels to achieve optimal use of AI in organisations.
| Reference Key |
selja2023towards
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|---|---|
| Authors | Butler; Tom; Espinoza-Limón; Angelina; Seppälä; Selja |
| Journal | arXiv |
| Year | 2023 |
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