IDEAS home Printed from https://ideas.repec.org/a/aza/airwa0/y2024v3i2p134-141.html
   My bibliography  Save this article

Enhancing transparency in AI-powered customer engagement

Author

Listed:
  • Dezao, Tara

    (Director of Product Marketing, AdTech and MarTech, Pegasystems, USA)

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.

Suggested Citation

  • Dezao, Tara, 2024. "Enhancing transparency in AI-powered customer engagement," Journal of AI, Robotics & Workplace Automation, Henry Stewart Publications, vol. 3(2), pages 134-141, March.
  • Handle: RePEc:aza:airwa0:y:2024:v:3:i:2:p:134-141
    as

    Download full text from publisher

    File URL: https://hstalks.com/article/8574/download/
    Download Restriction: Requires a paid subscription for full access.

    File URL: https://hstalks.com/article/8574/
    Download Restriction: Requires a paid subscription for full access.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Keywords

    artificial intelligence (AI); transparency; consumer trust; ethical concerns; AI explainability; organisational accountability; regulatory compliance;
    All these keywords.

    JEL classification:

    • M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management
    • G2 - Financial Economics - - Financial Institutions and Services

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:aza:airwa0:y:2024:v:3:i:2:p:134-141. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Henry Stewart Talks (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.