Leveraging artificial intelligence for enhanced innovation management in start-ups : a case study
Said, Said (2025)
2025
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2025112730177
https://urn.fi/URN:NBN:fi:amk-2025112730177
Tiivistelmä
This thesis examines how small and medium enterprises (SMEs) can leverage artificial intelligence (AI) adoption in their innovation management processes. The Technology-Organisation-Environment (TOE) framework, along with Diffusion of Innovation (DOI) and Open Innovation theories were used to analyse the study’s dual survey approach, which combines internal case company insights with external expert views and practices. The study focuses on a case company, a Finnish climate-tech startup, to explore how AI can enhance its innovation capability, intellectual property development, and overall organisational readiness.
The internal survey results revealed a strong innovation culture supported by collaboration and adaptability, which facilitated AI adoption, but were limited by common SME constraints such as time, resources, and data-driven decision making. External practitioners similarly highlighted the potential of AI to improve operational and process efficiency, idea generation, and patent activities, while cautioning that user trust, governance, and data management re-main key barriers to adoption.
In light of these findings, the thesis proposes a five-step AI adoption roadmap tailored for the case company, covering aspects from initial awareness and comprehension to scaling and ecosystem expansion of AI. The roadmap provides a structured model for SMEs to implement AI responsibly and effectively with continuous governance to reduce ethical, legal, and operational risks.
By extending the TOE-DOI framework with Open Innovation perspective in the context of AI-enabled innovation, this research not only offers a tailored framework to guide SMEs in transitioning from exploratory AI use to strategic, organisation-wide adoption but also towards strengthening external partner-ships.
The internal survey results revealed a strong innovation culture supported by collaboration and adaptability, which facilitated AI adoption, but were limited by common SME constraints such as time, resources, and data-driven decision making. External practitioners similarly highlighted the potential of AI to improve operational and process efficiency, idea generation, and patent activities, while cautioning that user trust, governance, and data management re-main key barriers to adoption.
In light of these findings, the thesis proposes a five-step AI adoption roadmap tailored for the case company, covering aspects from initial awareness and comprehension to scaling and ecosystem expansion of AI. The roadmap provides a structured model for SMEs to implement AI responsibly and effectively with continuous governance to reduce ethical, legal, and operational risks.
By extending the TOE-DOI framework with Open Innovation perspective in the context of AI-enabled innovation, this research not only offers a tailored framework to guide SMEs in transitioning from exploratory AI use to strategic, organisation-wide adoption but also towards strengthening external partner-ships.