Skip to content
Open access

Managerial attitudes toward AI: evaluating transparency, sense of control and fairness perceptions

Jul 2026 · Journal of Business & Industrial Marketing · Vol 41, pp. 267-281 · 0 citations · 90 references

TL;DR

How attitudes toward AI and control over it affect its expected performance in B2B marketing is shown, contributing to a deeper understanding of AI’s role in this context.

Abstract

Little research has explored the relationship between artificial intelligence (AI) and marketing performance, particularly regarding managers’ perceptions and attitudes toward AI. This paper aims to investigate the impact of AI fairness and transparency on business-to-business (B2B) marketing managers’ attitudes toward AI. From a marketing manager’s human-oriented perspective, this study proposes three scientific contributions. The research presents a conceptual framework for examining marketing professionals’ attitudes toward AI in marketing. Two studies involving 233 marketing managers provide insights into the drivers of AI adoption. Industrial managers view AI primarily as a tool to enhance efficiency, improve lead generation and support complex decision-making processes, demonstrating a pragmatic and utility-focused attitude. B2B firms should leverage AI for lead qualification, predictive analytics and account-based marketing, allowing businesses to benefit from its potential. AI competence must be considered a core competency for all involved organizations to ensure the creative deployment of AI. This study shows how attitudes toward AI and control over it affect its expected performance in B2B marketing, contributing to a deeper understanding of AI’s role in this context.

Read PDF

Similar papers

Review Open access Jul 2026

AI Trustworthness in Managerial Decision-Making: Ethics, Transparency, and Explainability as Key Drivers

The findings suggest that perceived AI trustworthiness is positively associated with responsible AI adoption and higher perceived decision efficacy, while decision complexity is an important boundary condition associated with the perceived efficacy of GAI in managerial decision processes.

Guangming Cao, Yanqing Duan, John S. Edwards · 0 citations
Review Jul 2026

Creating and consuming AI-generated content: ethical challenges of trust and transparency

A gap between professional and public expectations regarding AI use and responsible AI practices is revealed, and trust is identified as a central factor linking AI knowledge to positive evaluations of AI-assisted content across both audiences.

R. Avidar, Itzhak Mashiah · 1 citation
Conference Open access Aug 2026

Duality of AI in Knowledge Management: Correlating Utility Perceptions with Implementation Challenges

A dual perception is revealed in which optimism regarding AI’s potential coexists with recognition of the organizational adjustments it demands, revealing a dual perception in which optimism regarding AI’s potential coexists with recognition of the organizational adjustments it demands.

M. Nakash, E. Bolisani · 0 citations
#generative ai Review Open access Aug 2026

Does AI strengthen business leadership decision making: literature review

AI does not replace the role of executive leaders; instead, it serves as a cognitive aid that frees up a leader's capacity from routine operational tasks, yet it still requires the contextual intuition and ethical governance of human leaders.

Alifah Widya Rachmawati, Syamsul Hadi, Eni Purnasari et al. · 0 citations
Review

Does AI Strengthen Business Leardership Decision Making: Literature Review

AI does not replace the role of executive leaders; instead, it serves as a cognitive aid that frees up a leader's capacity from routine operational tasks, yet it still requires the contextual intuition and ethical governance of human leaders.

Alifah Widya Rachmawati, Syamsul Hadi, Eni Purnasari et al. · 0 citations
Review Aug 2026

Human-Ai Interface: Assessing The Role Of Explainable Ai (Xai) In Mitigating Knowledge Worker Resistance And Fostering Trust During Ai-Driven Business Process Automation

The study concludes that Explainable AI is not only a technological enhancement but also a strategic tool for promoting employee trust and supporting effective digital transformation and recommends that organizations prioritize explainability, invest in AI literacy and training, and develop transparent AI governance fr...

Evelyn Chichi Otuya, A. Ayegba · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.