IDEAS home Printed from https://ideas.repec.org/p/osf/osfxxx/8jqzu.html
   My bibliography  Save this paper

Starting Slowly to Go Fast Deep Dive in the Context of AI Pilot Projects

Author

Listed:
  • Pletcher, Scott Nicholas

Abstract

For many organizations, artificial intelligence and its subsets of machine learning and deep learning hold great potential for improving efficiency, creating new capabilities and launching new business models. Accordingly, many organizations are attempting to harness these technologies through prototyping and pilot projects. However, many organizations struggle to move past the pilot phase, despite heavy investment in time, data infrastructure and training. In their book Strategic Doing, Morrison et al. (2019) provide a framework to help organizations brainstorm, organize and launch innovation using ten skills of agile leadership. A specific step in the described approach is to Start Slowly to Go Fast. This simple statement holds some deep implications, with many of the principles contained within that philosophy shown to improve innovation outcomes. This paper will examine some of those principles in the context of AI projects.

Suggested Citation

  • Pletcher, Scott Nicholas, 2023. "Starting Slowly to Go Fast Deep Dive in the Context of AI Pilot Projects," OSF Preprints 8jqzu, Center for Open Science.
    • Handle: RePEc:osf:osfxxx:8jqzu
    DOI: 10.31219/osf.io/8jqzu
    as

    Download full text from publisher

    File URL: https://osf.io/download/64f21f22989de60d05dd1437/
    Download Restriction: no
    File URL: https://libkey.io/10.31219/osf.io/8jqzu?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:osf:osfxxx:8jqzu. 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: OSF (email available below). General contact details of provider: https://osf.io/preprints/ .

    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.