[AI for All, Diverging AX]④"Putting an End to Going It Alone"... Overseas, It's 'Collaborative AX'

Evolving Beyond Technical and Financial Support
Toward Building Industrial Ecosystems

Editor's NoteArtificial Intelligence (AI) is transforming corporate productivity and the way people work, but there is a growing gap in adoption speed between large corporations and small and medium-sized enterprises (SMEs). While companies equipped with dedicated AI teams and infrastructure are accelerating company-wide AI transformation (AX), those without such resources—both companies and public institutions—are left in AX blind spots, excluded from "AI for All." The Asia Business Daily examines the AX gap emerging beneath the surface of innovation and explores the necessary conditions and solutions to drive up productivity through truly inclusive AI, leaving no one behind.

Policies by various countries to accelerate the spread of Artificial Intelligence (AI) in the corporate sector are evolving beyond technological and financial support to building robust industrial ecosystems. To reduce the burden of AX investment on individual companies, countries are building shared infrastructure that lowers AX costs.

Across Europe, systems to collectively support AX on a regional and sectoral basis are spreading. In northern Italy's Emilia-Romagna region, universities, research institutes, and industrial clusters are linked to provide SMEs with AI diagnostics and pilot projects. This year, they initiated a project to assess the level of AI adoption and provide hands-on support to 50 local cooperatives. In Trentino, a business initiative is underway in which companies present real-world challenges in production, logistics, or quality management; students from the University of Trento and experts from research institutions then develop AI models and algorithms over approximately 11 weeks.

Germany is lowering barriers to AX adoption by deploying regional AI experts. Through its Mittelstand digital policy, digital hubs across the country support SMEs in various regions and industries, and 100 AI trainers are active nationwide. These trainers visit companies directly, offering workshops and consulting to find tailored AI solutions that fit the specific characteristics of local industries such as manufacturing and logistics.

The United States is working to ensure that AI can make optimal use of industrial data by establishing technology standards and interoperability. The National Institute of Standards and Technology (NIST) has conducted research to convert manufacturing data into computer-readable "machine-readable" standards. This approach enables AI utilization by aligning the formats and meanings of data generated from disparate companies and equipment.

Singapore is building an "AX package marketplace" to enable SMEs to easily select needed AI solutions. Companies can input their business demands and receive recommendations for pre-approved generative AI products through the government's "GenAI Navigator" service. In May of this year, Singapore supported technology adoption for over 2,000 SME retailers. This approach provides AI solutions for problems encountered in day-to-day store management or business operations.

Japan is pursuing company AX and workforce development simultaneously through case-based education using enterprise data. Workers in training identify and solve management challenges at local SMEs by leveraging AI technology. This system allows companies to verify AI solutions suited to their needs without incurring the expense of high-priced consultants or hiring experts, while trainees can build practical experience and often progress to full-time employment, creating a virtuous cycle.

This content was produced with the assistance of AI translation services.