Systematic prioritization of AI initiatives: implementation factors and achievable value

Artificial intelligence has yet again surged in popularity, especially after recent breakthroughs in generative artificial intelligence technology. As organizations rush to implement artificial intelligence in their processes, the question of how and why to prioritize use cases over another is raise...

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Main Author: Ahti, Joona Oliver Andreas
Other Authors: Informaatioteknologian tiedekunta, Faculty of Information Technology, University of Jyväskylä, Jyväskylän yliopisto
Format: Master's thesis
Language:eng
Published: 2024
Online Access: https://jyx.jyu.fi/handle/123456789/96123
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author Ahti, Joona Oliver Andreas
author2 Informaatioteknologian tiedekunta Faculty of Information Technology University of Jyväskylä Jyväskylän yliopisto
author_facet Ahti, Joona Oliver Andreas Informaatioteknologian tiedekunta Faculty of Information Technology University of Jyväskylä Jyväskylän yliopisto Ahti, Joona Oliver Andreas Informaatioteknologian tiedekunta Faculty of Information Technology University of Jyväskylä Jyväskylän yliopisto
author_sort Ahti, Joona Oliver Andreas
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description Artificial intelligence has yet again surged in popularity, especially after recent breakthroughs in generative artificial intelligence technology. As organizations rush to implement artificial intelligence in their processes, the question of how and why to prioritize use cases over another is raised. To answer this, this the-sis explores both the factors affecting the organizational implementation of arti-ficial intelligence, as well as what types of value and how that value is achieva-ble with the utilization of artificial intelligence. Researching these aspects of artificial intelligence initiatives allows for the development of a value-feasibility matrix, which can provide additional guidance to organizational de-cision-makers facing the issue. This study was conducted in two parts. First, a literature review on both the factors and enablers affecting the implementation of artificial intelligence, and the types of value achievable and the mechanisms used to create that value with artificial intelligence. This literature review pro-vided the theoretical basis for the development of the value-feasibility matrix. Then, an empirical qualitative study was carried out to validate the model. 11 semi-structured interviews were conducted, with interviewees representing both industrial companies as well as technology providers. The findings from the interviews aligned strongly with existing research and the proposed value-feasibility matrix. This thesis was able to address the research gap on the sys-tematic prioritization of artificial intelligence initiatives, and also contribute to existing research by providing new empirical findings. The developed and val-idated value-feasibility matrix can serve as a guiding tool for organizational leaders struggling with the prioritization of artificial intelligence initiatives. Tekoäly on jälleen noussut pinnalle, etenkin generatiivisen tekoälyn tuomien uusien mahdollisuuksien kautta. Organisaatiot pyrkivät ottamaan tekoälyä käyttöön eri liiketoimintaprosesseissaan nopealla tahdilla. Nopea käyttöönot-totahti kuitenkin herättää kysymyksen siitä, voisiko eri hankkeiden priorisoin-tiin olla systemaattinen ratkaisu. Vastatakseen tähän kysymykseen, tämä tut-kielma käsittelee tekoälyhankkeiden käyttöönottoon vaikuttavia tekijöitä, yri-tystason arvoa jota tekoälysovellukset voivat luoda organisaatiossa, sekä pro-sessitason vaikutuksia, joilla arvoa luodaan. Näiden näkökulmien tutkiminen mahdollistaa arvo-toteutettavuus-matriisin kehittämisen, jota hyödyntämällä päätöksentekijät voivat saada lisäohjausta hankkeiden priorisointiin. Tämä tutkielma toteutettiin kahdessa osassa. Teoreettinen perusta matriisille raken-nettiin sekä tekoälyhankkeiden käyttöönottoon vaikuttavien tekijöiden että tekoälyn luoman yritysarvon tutkivaa kirjallisuuskatsauksen varaan. Tämän jälkeen toteutettiin empiirinen tutkimus, jonka kautta kirjallisuuskatsauksen löydökset sekä arvo-toteutettavuus-matriisi validoitiin. Kvalitatiivisessa tut-kimuksessa toteutettiin 11 puolistrukturoitua asiantuntijahaastattelua. Haasta-teltavat edustivat niin teollisuusyrityksiä kuin teknologiapalveluntarjoajia. Kvalitatiivisen tutkimuksen tulokset korreloivat vahvasti olemassa olevan kir-jallisuuden sekä ehdotetun arvo-toteutettavuus-matriisin kanssa. Tämä tut-kielma kykeni osaltaan vastaamaan systemaattisen tekoälyhankkeiden priori-siointiin liittyvään tutkimusaukkoon, sekä tuottamaan uutta tietoa olemassa olevaan kirjallisuuteen niin tekoälyhankkeiden käyttöönottoon vaikuttavien tekijöiden, kuin myös tekoälysovellusten luoman arvon saralla tuottamalla lisää empiiristä dataa. Tutkielmassa kehitetty arvo-toteutettavuus-matriisi voi toimia ohjaavana työkaluna tekoälyhankkeiden systemaattista priorisointia suunnitteleville organisaatiojohtajille.
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spellingShingle Ahti, Joona Oliver Andreas Systematic prioritization of AI initiatives: implementation factors and achievable value
title Systematic prioritization of AI initiatives: implementation factors and achievable value
title_full Systematic prioritization of AI initiatives: implementation factors and achievable value
title_fullStr Systematic prioritization of AI initiatives: implementation factors and achievable value Systematic prioritization of AI initiatives: implementation factors and achievable value
title_full_unstemmed Systematic prioritization of AI initiatives: implementation factors and achievable value Systematic prioritization of AI initiatives: implementation factors and achievable value
title_short Systematic prioritization of AI initiatives: implementation factors and achievable value
title_sort systematic prioritization of ai initiatives implementation factors and achievable value
title_txtP Systematic prioritization of AI initiatives: implementation factors and achievable value
url https://jyx.jyu.fi/handle/123456789/96123 http://www.urn.fi/URN:NBN:fi:jyu-202406244969
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