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TRUVACE RECORD VERSION
record: TRV-2026-0444
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-07-20T10:55:09.767340Z
status: published
lens: g_space
sector: business
headline: Artificial intelligence implementation in manufacturing SMEs: A resource orchestration approach
dek: Artificial intelligence (AI) is playing a leading role in the digital transformation of enterprises, particularly in the manufacturing industry where it has been responsible for a profound transformation in key business and production operations. Despite the accelerated growth of AI technologies, knowledge of the implementation of AI by small and medium-sized enterprises (SMEs) remains underexplored. Thus, this study seeks to examine how manufacturing SMEs orchestrate resources for AI implementation. Building on…
gain_title: Manufacturing SMEs in Sweden structure, bundle, and leverage AI resources to transform key business and production operations and create competitive advantage.
problem_title: (none)
trace_subject: (none)
gain_reading: Manufacturing SMEs in Sweden structure, bundle, and leverage AI resources to transform key business and production operations and create competitive advantage.
gain_evidence: Artificial intelligence (AI) is playing a leading role in the digital transformation of enterprises, particularly in the manufacturing industry where it has been responsible for a profound transformation in key business and production operations. | SMEs effectively leverage AI resources and capabilities by mobilising technologies, coordinating manufacturing processes, and empowering skilled people. | drive an organisation's digital transformation whilst creating a competitive advantage.
problem_reading: (none)
problem_evidence: (none)
quick_read: Published April 3 2024, this peer-reviewed study investigated AI implementation in manufacturing SMEs in Sweden across packaging, plastic, and metal sectors. It found SMEs build an AI resource portfolio through acquiring and accumulating resources, bundle them into learning and governance capabilities, and leverage them in production.

The work matters because it shows a practical pathway for smaller manufacturers to achieve digital transformation and competitive advantage, not just large firms. What remains uncertain is how transferable this orchestration pattern is beyond the studied Swedish cases and sectors, given limited prior knowledge on SME AI adoption.
limitation: Findings are bounded to a small set of case studies in specific sectors and geography, and broader SME implementation knowledge remains limited.
tag: Evidence-backed gain
key_points: Study examines AI implementation in manufacturing SMEs using resource orchestration theory. | Findings based on multiple case studies of SMEs in Sweden in packaging, plastic, and metal sectors. | SMEs structure a portfolio based on acquiring and accumulating AI resources. | Resources are bundled into learning and governance capabilities and leveraged by mobilising technologies, coordinating processes, and empowering skilled people.
rundown: The study applies resource orchestration theory to examine how manufacturing SMEs acquire and accumulate AI resources, then bundle them into learning and governance capabilities.

Leveraging occurs through a dynamic process described as mobilising technologies, coordinating manufacturing processes, and empowering skilled people to drive digital transformation.
sources:
- peer_reviewed | International Journal of Information Management | https://doi.org/10.1016/j.ijinfomgt.2024.102781 | 2024-04-03
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