Högskolan i Skövde

his.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • apa-cv
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Scaling Up Data-Driven Pilot Projects
University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment. (Informationssystem, Information Systems)ORCID iD: 0000-0001-8362-3825
Ammizing Consulting.
Advectas AB.
2020 (English)In: The AI Magazine, ISSN 0738-4602, Vol. 41, no 3, p. 94-102Article in journal (Refereed) Published
Abstract [en]

Conducting pilot projects are a common approach among organizations to test and evaluate new technology. A pilot project is often conducted to remove uncertainties from a large-scale project and should be limited in time and scope. Nowadays, several organizations are testing and evaluating artificial intelligence techniques and more advanced forms of analytics via pilot projects. Unfortunately, many organizations are experiencing problems in scaling-up the findings from pilot projects to the rest of the organization. Hence, results from pilot projects become siloed with limited business value. In this article, we present an overview of barriers for conducting and scaling-up data-driven pilot projects. Lack of senior management support is a frequently mentioned top barrier in the literature. In response to this, we present our recommendations on what type of activities can be performed, to increase the chances of getting a positive response from senior management regarding scaling-up the usage of artificial intelligence and advanced analytics within an organization.

Place, publisher, year, edition, pages
Association for the Advancement of Artificial Intelligence , 2020. Vol. 41, no 3, p. 94-102
National Category
Other Computer and Information Science
Research subject
Information Systems
Identifiers
URN: urn:nbn:se:his:diva-19097DOI: 10.1609/aimag.v41i3.5307ISI: 000574631600007Scopus ID: 2-s2.0-85092796964OAI: oai:DiVA.org:his-19097DiVA, id: diva2:1470204
Available from: 2020-09-24 Created: 2020-09-24 Last updated: 2020-10-29Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Berndtsson, Mikael

Search in DiVA

By author/editor
Berndtsson, Mikael
By organisation
School of InformaticsInformatics Research Environment
In the same journal
The AI Magazine
Other Computer and Information Science

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 549 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • apa-cv
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf