loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Tobias Eljasik-Swoboda 1 ; Christian Rathgeber 1 and Rainer Hasenauer 2

Affiliations: 1 ONTEC AG, Ernst-Melchior-Gasse 24/DG, Vienna and Austria ; 2 Marketing Management Institute, Wirtschaftsuniversität Wien and Hi-Tech Center, Vienna and Austria

Keyword(s): Artificial Intelligence Readiness, Technology Readiness, Market Readiness, Innovation, Innovation Management, Organizational Concepts and Best Practices, Data Privacy and Security, Data Management and Quality, Data and Information Quality.

Related Ontology Subjects/Areas/Topics: Data and Application Security and Privacy ; Data Engineering ; Data Management and Quality ; Data Privacy and Security ; Databases and Data Security ; Information and Systems Security ; Information Quality ; Organizational Concepts and Best Practices

Abstract: Every innovation begins with an idea. To make this idea a valuable novelty worth investing in requires identification, assessment and management of innovation projects under two primary aspects: The Market Readiness Level (MRL) measures if there is actually a market willing to buy the envisioned product. The Technology Readiness Level (TRL) measures the capability to produce the product. The READINESSnavigator is a state of the art software tool that supports innovators and investors in managing these aspects of innovation projects. The existing technology readiness levels neatly model the production of physical goods but fall short in assessing data based products such as those based on Artificial Intelligence (AI) and Machine Learning (ML). In this paper we describe our extension of the READINESSnavigator with AI and ML relevant readiness levels and evaluate its usefulness in the context of 25 different AI projects.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 13.58.82.79

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Eljasik-Swoboda, T.; Rathgeber, C. and Hasenauer, R. (2019). Assessing Technology Readiness for Artificial Intelligence and Machine Learning based Innovations. In Proceedings of the 8th International Conference on Data Science, Technology and Applications - DATA; ISBN 978-989-758-377-3; ISSN 2184-285X, SciTePress, pages 281-288. DOI: 10.5220/0007946802810288

@conference{data19,
author={Tobias Eljasik{-}Swoboda. and Christian Rathgeber. and Rainer Hasenauer.},
title={Assessing Technology Readiness for Artificial Intelligence and Machine Learning based Innovations},
booktitle={Proceedings of the 8th International Conference on Data Science, Technology and Applications - DATA},
year={2019},
pages={281-288},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007946802810288},
isbn={978-989-758-377-3},
issn={2184-285X},
}

TY - CONF

JO - Proceedings of the 8th International Conference on Data Science, Technology and Applications - DATA
TI - Assessing Technology Readiness for Artificial Intelligence and Machine Learning based Innovations
SN - 978-989-758-377-3
IS - 2184-285X
AU - Eljasik-Swoboda, T.
AU - Rathgeber, C.
AU - Hasenauer, R.
PY - 2019
SP - 281
EP - 288
DO - 10.5220/0007946802810288
PB - SciTePress