[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/a/aza/airwa0/y2022v2i1p63-69.html
   My bibliography  Save this article

Six ways AI is delivering value for organisations drawing on real-world case studies and offering actionable insights

Author

Listed:
  • Mittal, Nitin

    (Deloitte, USA)

  • Saif, Irfan

    (US AI Co-leader, Deloitte Risk & Financial Advisory, USA)

Abstract
After decades as science fiction fantasy, artificial intelligence (AI) has made the leap to practical reality and is quickly becoming a competitive necessity. Yet, amid the current frenzy of AI advancement and adoption, many leaders and decision makers still have significant questions about what AI can actually do for their businesses. This paper highlights compelling, business-ready use cases for AI across six major industries: consumer; energy, resources and industrials; financial services; government and public services; life sciences and health care; and technology, media and telecommunications. The goal is to give readers a much clearer sense of what AI is capable of achieving in a business context — now, and over the next several years — so that business leaders and AI practitioners can make smart decisions about when, where and how to deploy AI within their own organisations and how much time, money and attention they should be investing in it today.

Suggested Citation

  • Mittal, Nitin & Saif, Irfan, 2022. "Six ways AI is delivering value for organisations drawing on real-world case studies and offering actionable insights," Journal of AI, Robotics & Workplace Automation, Henry Stewart Publications, vol. 2(1), pages 63-69, September.
    • Handle: RePEc:aza:airwa0:y:2022:v:2:i:1:p:63-69
    as

    Download full text from publisher

    File URL: https://hstalks.com/article/7362/download/
    Download Restriction: Requires a paid subscription for full access.
    File URL: https://hstalks.com/article/7362/
    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); machine learning (ML); innovation; automation; technology adoption;
    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:2022:v:2:i:1:p:63-69. 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.