From Information Overload to Knowledge Integration: Generative AI as an AI-Enabled Information Management Capability in Science–Industry Innovation Ecosystems
Year: 2026
Type: preprint
Abstract: Science–industry collaboration increasingly depends on the ability of innovation ecosystem actors to identify, integrate, evaluate, and mobilise knowledge distributed across organisational and digital boundaries. Although generative artificial intelligence (GenAI) offers new capabilities for processing and synthesising heterogeneous information, its potential role in supporting ecosystem-level knowledge integration remains conceptually underdeveloped and empirically underexplored. This study examines how innovation ecosystem stakeholders perceive the information management challenges constraining science–industry collaboration and which AI-enabled capabilities they consider important for supporting knowledge integration and collaborative decision-making. The study draws on 24 semi-structured interviews with researchers, industry representatives, and policymakers in Slovenia, analysed using reflexive thematic analysis. The findings indicate that collaboration challenges arise less from information scarcity than from ecosystem fragmentation, information overload, limited visibility and evaluability of competencies, and uncertainty regarding potential partners. Stakeholders identified five complementary GenAI-enabled capability areas: partner and competency matching, funding opportunity analysis, competency and reference visibility, proposal development support, and decision support. Across these capabilities, transparency and explainability, traceability of AI-supported recommendations, data protection and security, and human oversight and accountability emerged as cross-cutting governance conditions. The study develops an empirically grounded conceptualisation of GenAI as an AI-enabled information management capability for ecosystem knowledge integration. Rather than positioning GenAI as an autonomous innovation intermediary, the findings indicate that its potential value lies in augmenting information-intensive intermediary functions by making distributed ecosystem knowledge more accessible, connected, evaluable, and actionable while preserving human judgement and decision authority. By integrating perspectives from knowledge management, innovation intermediation, and AI-enabled information systems, the study provides a theoretical foundation for understanding and subsequently testing the role of GenAI in ecosystem knowledge integration and informs the design of human-governed AI-enabled collaboration infrastructures.
Source: Research Square
Language: English
Subfield: Management of Technology and Innovation
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7204197845