Table 2 The criteria used in the preliminary questionnaire and finalized questionnaire

(A) AI application strategy

AI competencies

c₁

▲

a₁

▲

Atmaca and Karadaş (2020), Gil et al. (2020), Jarrahi (2018), McCollum (2017), Pelletier (2017), Rodríguez et al. (2016), Schotten and Morais (2019), Tredinnick (2017)

AI risks and opportunities

c₂

▲

–

△

AI outcomes and expected level

c₃

▲

a₂

▲

The ability of AI provider

c₄

▲

a₃

▲

AI cognition of senior executives

c₅

▲

a₄

▲

(B) AI governance

The techniques of AI governance

c₆

▲

b₁

▲

Hesami and Jones (2020), Negnevitsky (2005), Pelletier (2017), Bizarro and Dorian (2017), Länsiluoto et al. (2016), Schmitt (2022)

AI activities and decisions

c₇

▲

b₂

▲

AI policies and procedures

c₈

▲

–

△

AI accountability and oversight

c₉

▲

b₃

▲

AI monitor

c₁₀

▲

–

△

The necessary skills and expertise of AI responsibilities

c₁₁

▲

b₄

▲

(C) Data infrastructure and data quality

Data accessibility

c₁₂

▲

c₁

▲

Hirsch (2018), Kou et al. (2021a, b), Pelletier (2017), Tredinnick (2017), Vial et al. 2021

Information privacy and security

c₁₃

▲

c₂

▲

Roles and responsibilities for data ownership and use

c₁₄

▲

–

△

The completeness, accuracy, and reliability of the data

c₁₅

▲

c₃

▲

Data reconciliation, synthesis, and validation

c₁₆

▲

–

△

Cyber resilience

c₁₇

▲

–

△

(D) Human factor

AI design

c₁₈

▲

–

△

Dignum et al. (2004), IIA (2017a), Scherer (2016), Srinivasan and González 2022

AI test

c₁₉

▲

d₁

▲

AI technologies

c₂₀

▲

–

△

AI output

c₂₁

▲

–

△

Human error and biases

c₂₂

▲

d₂

▲

Black box elements

c₂₃

▲

d₃

▲