Can Artificial Intelligence Accelerate Technological Progress? Researchers' Perspectives on AI in Manufacturing and Materials Science
arXiv:2511.14007v3 Announce Type: replace-cross Abstract: Artificial intelligence (AI) raises expectations of substantial increases in rates of technological progress, but such anticipations are often not connected to detailed ground-level studies of AI use in innovation processes. Accordingly, it remains unclear how and to what extent AI can accelerate innovation. To help to fill this gap, we explore and assess results from 32 interviews with U.S.-based academic manufacturing and materials sciences researchers experienced with AI and machine learning (ML) techniques. We found that AI was prim
This research provides a ground-level perspective on AI's impact on innovation, moving beyond theoretical discussions to empirical observation, which is critical as AI adoption accelerates across industries.
Understanding how AI specifically accelerates innovation in manufacturing and materials science offers insights into future productivity gains and the strategic deployment of AI resources.
The study shifts the narrative from generalized AI potential to concrete examples and challenges in specific R&D contexts, highlighting real-world friction points and success factors for AI integration.
- · AI/ML researchers
- · Manufacturing sector
- · Materials science
- · Nations investing in AI R&D
- · Traditional R&D methodologies
- · Industries slow to adopt AI
- · Economies lacking AI talent
AI models and tools will be increasingly tailored to specific scientific and engineering domains based on these empirical insights.
Accelerated innovation in materials could lead to paradigm shifts in energy, defence, and computing, enabling entirely new technologies.
Nations that effectively integrate AI into their industrial R&D will gain significant economic and strategic advantages, potentially widening global innovation disparities.
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Read at arXiv cs.AI