Towards a Capability Assessment Model for the Comprehension and Adoption of AI in Organisations
This work addresses the problem of AI adoption for organizational stakeholders like business executives and technologists, providing incremental tools based on a comprehensive conception of AI compared to existing models.
The paper tackles the challenge of AI comprehension and adoption in organizations by developing a 5-level AI Capability Assessment Model (AI-CAM) and an AI Capabilities Matrix (AI-CM) as practical, open-source tools to assist practitioners in assessing and improving AI capabilities across business, data, technology, and ethical dimensions.
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.