Enhancing transparency in AI-powered customer engagement

Tara Dezao
Additional contact information
Tara Dezao: Director of Product Marketing, AdTech and MarTech, Pegasystems, USA

Journal of AI, Robotics & Workplace Automation, 2024, vol. 3, issue 2, 134-141

Abstract: This paper addresses the critical challenge of building consumer trust in AI-powered customer engagement by emphasising the necessity for transparency and accountability. Despite the potential of AI to revolutionise business operations and enhance customer experiences, widespread concerns about misinformation and the opacity of AI decision-making processes hinder trust. Surveys highlight a significant lack of awareness among consumers regarding their interactions with AI, alongside apprehensions about bias and fairness in AI algorithms. The paper advocates for the development of explainable AI models that are transparent and understandable to both consumers and organisational leaders, thereby mitigating potential biases and ensuring ethical use. It underscores the importance of organisational commitment to transparency practices beyond mere regulatory compliance, including fostering a culture of accountability, prioritising clear data policies and maintaining active engagement with stakeholders. By adopting a holistic approach to transparency and explainability, businesses can cultivate trust in AI technologies, bridging the gap between technological innovation and consumer acceptance, and paving the way for more ethical and effective AI-powered customer engagements.

Keywords: artificial intelligence (AI); transparency; consumer trust; ethical concerns; AI explainability; organisational accountability; regulatory compliance (search for similar items in EconPapers)
JEL-codes: G2 M15 (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
https://hstalks.com/article/8574/download/ (application/pdf)
https://hstalks.com/article/8574/ (text/html)
Requires a paid subscription for full access.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:aza:airwa0:y:2024:v:3:i:2:p:134-141

Access Statistics for this article

More articles in Journal of AI, Robotics & Workplace Automation from Henry Stewart Publications
Bibliographic data for series maintained by Henry Stewart Talks ().