IDEAS home Printed from https://ideas.repec.org/h/spr/mgmchp/978-3-030-57642-4_18.html
   My bibliography  Save this book chapter

The Five Elements of AI to Leverage Data and Dominate Your Industry

In: Creating Innovation Spaces

Author

Listed:
  • Alexander Thamm

    (Alexander Thamm GmbH)

Abstract

Using data to make better decisions has been a formula for success for almost two decades now. We went from business analytics to predictive analytics, Big Data and now artificial intelligence (AI). Industry experts predict that within this decade we will see the second wave of AI companies generating $13 trillion GDP growth (Ng, AI transformation playbook. How to lead your company into the AI era, 2018). This growth will be dominated by industry incumbents who understand how to innovate their business model and thus outgrow their industry rivals. Winners will build AI assets to defend against challengers while others will vanish from the market. In this article, you will learn the recipe to generate value from data and AI by combining five main ingredients. After reading you understand what AI really is and how to build an effective AI product portfolio, an engaging AI culture and organizational structure, professionally train and hire AI experts, built a hands-on data governance and a solid data and AI technology platform.

Suggested Citation

  • Alexander Thamm, 2021. "The Five Elements of AI to Leverage Data and Dominate Your Industry," Management for Professionals, in: Volker Nestle & Patrick Glauner & Philipp Plugmann (ed.), Creating Innovation Spaces, chapter 18, pages 235-258, Springer.
  • Handle: RePEc:spr:mgmchp:978-3-030-57642-4_18
    DOI: 10.1007/978-3-030-57642-4_18
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    More about this item

    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:spr:mgmchp:978-3-030-57642-4_18. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.