Artificial Intelligence im strategischen Innovationsmanagement - der Beitrag KI-basierter Systeme zur Trendidentifikation

Abstract

Innovation is regarded as a driver of long-term competitiveness. At the same time, the pace and uncertainty of technological and societal change are rising, which means companies must detect trends earlier and assess them more systematically. In practice, this early sensing often happens in an ad-hoc manner. Artificial intelligence can help here, as it can process large data volumes and surface patterns. The findings are clear: companies are using AI, but the focus is on generative applications, while machine learning and natural language processing are used less frequently. AI creates the most value in research, scanning and scouting, and in structuring heterogeneous information. It speeds up idea generation, prototyping, and visualization, and condenses content into decision-ready summaries. This leads to greater speed, higher consistency, and better transparency in the early phases. Success factors include a robust infrastructure, clean and accessible data, skilled employees, and clear rules on data protection and security. Obstacles include bias and hallucinations, integration effort, costs, and user acceptance. Full automation is not expected; human judgment remains central. For implementation, small pilot projects with clear objectives and measurable outcomes have proven effective, along with step-by-step scaling into established processes and responsibilities. The practical value of this work lies in enabling earlier and more accurate trend identification. It shows how AI accelerates scouting and research, filters weak signals, and distills large volumes of text into usable decision briefs. The study provides clear entry points and criteria for data, roles, and infrastructure so that pilot projects can start in a targeted way and then be transferred into stable processes. As a result, search effort decreases, the time to a robust assessment shortens, and prioritization at early decision points becomes more transparent.

Date of Award	2025
Original language	German (Austria)
Supervisor	Patrick Brandtner (Supervisor)