Towards a Capability Assessment Model for the Comprehension and Adoption of AI in Organisations

TL;DR

This paper introduces a comprehensive 5-level AI Capability Assessment Model and a capabilities matrix to help organizations understand and improve their AI comprehension and adoption, addressing practical and ethical challenges.

Contribution

It presents a novel, open-source assessment framework and matrix that integrate diverse AI capabilities for organizational adoption and comprehension.

Findings

The AI-CAM covers core capability dimensions across five maturity levels.

The tools are developed with input from practitioners and are openly accessible.

They support decision-making for AI use cases involving data analytics, semantic technologies, and human-like AI solutions.

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.