Artificial Intelligence for Innovation in Austria

• Main Author: Erich Prem
• Format: Article
• Language: English
• Published: Carleton University 2019-12-01
• Series: Technology Innovation Management Review
• Subjects: ai; ai innovation management; artificial intelligence; austria; innovation; sme
• Online Access: https://timreview.ca/timreview.ca/article/1287

It has been claimed that Artificial Intelligence (AI) carries enormous potential for service and product innovation. Policy makers world-wide nowadays aim to foster environments conducive for AI-based innovation. This paper addresses the current lack of empirical data for evidence-based innovation policies and the management of AI-based innovation. It focuses on “AI and innovation management” in addressing the question whether innovation that is based on new AI technology requires a management approach different from other forms of IT innovation. We present results from a study of Austrian companies on the degree of use and implementation of AI, and on challenges related to AI-based innovation management. This study used a keyword-list approach to define “Artificial Intelligence” and to find AI-based innovation projects in research databases. These projects facilitated the identification of experts from organisations developing AI-based innovation. In total, eleven experts were interviewed about their AI-based innovation activities. The results show that AI is a very fast emerging technology that is being applied in many sectors. A broad range of innovative solutions are being developed and some have already reached the market. Specific AI business models are, however, less clear and still developing. Companies are facing multiple challenges from regulation to human resources and data collection. Managing AI-based innovation will be particularly difficult for smaller enterprises, where problems are often more pronounced than in larger industries. Explicit challenges for managing AI-based innovations include the necessary attention to managing expectations and ensuring historic metadata expertise essential for many AI-based solutions. Policies to support AI-based innovation therefore should focus on human aspects. This includes increasing the availability of AI experts, but also concerns the development of new job profiles, such as experts in AI training. AI innovators also require clear AI regulation and research investments in key challenges, such as explainable AI.