AI Implementation Capability Assessment and Development Planning: Towards a Tool for SMEs
Publiceringsår
2025
Upphovspersoner
Kudryavtsev, Dmitry; Moilanen, Teemu; Laatikainen, Elisa; Khan, Umair Ali
Abstrakt
Small and medium-sized enterprises (SMEs) lag behind in AI adoption and require support to assess and enhance their AI implementation capabilities. Such support is often provided via advisory sessions, but there is a potential to automate these tasks partially. Needs analysis identified the following key requirements for the supporting tool: 1. Ability to suggest and select improvement actions (prescriptive functionality) in addition to the assessment of current state (descriptive functionality); 2. SMEs-focus, which is mostly reflected in the selection of maturity assessment indicators and emphasis on low maturity levels; 3. Completeness justification of AI implementation capability assessment. The existing AI maturity models do not satisfy all these requirements, so there is a need to develop a new tool. The paper presents an ongoing research project aiming to create an AI implementation capability development planning tool for SMEs (AICapDev). This tool will include a prescriptive maturity model for AI implementation capability and roadmap drafting component to prioritise and plan improvement action. The current paper presents the preliminary research results, more specifically problem definition and requirements specification, description of the AICapDev tool and its usage demonstration. The future work presented in the conclusion.
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Publikationstyp
Publikationsform
Artikel
Moderpublikationens typ
Konferens
Artikelstyp
Annan artikel
Målgrupp
VetenskapligKollegialt utvärderad
Kollegialt utvärderadUKM:s publikationstyp
A4 Artikel i en konferenspublikationPublikationskanalens uppgifter
Moderpublikationens namn
2025 IEEE 23rd World Symposium on Applied Machine Intelligence and Informatics (SAMI)
Sidor
000471-000476
ISSN
ISBN
Publikationsforum
Publikationsforumsnivå
1
Öppen tillgång
Öppen tillgänglighet i förläggarens tjänst
Nej
Parallellsparad
Nej
Övriga uppgifter
Vetenskapsområden
Data- och informationsvetenskap
Nyckelord
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Publiceringsland
Förenta staterna (USA)
Förlagets internationalitet
Internationell
Språk
engelska
Internationell sampublikation
Nej
Sampublikation med ett företag
Nej
DOI
10.1109/sami63904.2025.10883262
Publikationen ingår i undervisnings- och kulturministeriets datainsamling
Ja