As the International Summit on Artificial Intelligence concludes in France, the rapid adoption of generative AI by businesses continues to spark intense debates—and fuel both excitement and speculation. Progress in this field is no longer confined to tech giants and service providers; it is now reshaping companies across industries and influencing global trade. From optimizing processes to transforming products, what opportunities and risks does AI adoption bring to the manufacturing sector and credit management?
Growth, productivity, competitiveness: key challenges at every level
Whether viewed from a corporate or national perspective, the implications of AI adoption can vary significantly. However, three critical themes remain central at both macroeconomic and microeconomic levels: growth, productivity, and competitiveness.
Following an initial phase of fascination and experimentation, generative AI is now entering a new stage—where large-scale, productive applications are being integrated into sustainable business models. This technological shift is driving a race for competitiveness, inevitably creating disparities between nations and companies. Those who fail to adapt risk falling behind, as not all players will recover at the same pace from strategic missteps in this domain.
The ones who will master AI will benefit from productivity gains and a strategic advantage. However, the challenge is to balance the ratio between power and responsibility: AI is a lever for growth and a source of productivity, but also a vector for ethical, social, environmental and geopolitical risks.
The acculturation of decision-makers is also decisive for companies. Especially since AI is still a moving matter, as we saw recently with DeepSeek, which turned many beliefs perceived as immutable truths upside down.
Aurélien Duthoit, ICT Sector Economist, Coface.
Is AI adoption an even playing field?
AI is a disruptive force impacting businesses of all sizes and industries, but its adoption is deeply influenced by geopolitical and economic factors, such as national sovereignty, investment policies, and market dynamics. The global AI landscape remains dominated by U.S. and Chinese companies.
Tech giants like Google, Microsoft, Amazon, Meta, Oracle, and Apple are leading the charge, collectively investing over $160 billion in 2024—primarily to expand data center infrastructure for training AI models. The stakes are set to rise further, with Donald Trump announcing a nearly $500 billion investment in AI through the Stargate project.
Meanwhile, major Chinese players such as Baidu, Tencent, and Alibaba have committed around $15 billion to AI development, positioning themselves as strong contenders in the field.
In contrast, Europe struggles to keep pace, with no single company investing on a comparable scale.
The pace of AI adoption is very unequal between sectors but also within the same sector. It depends on regulatory factors, the degree of data maturity and available resources.
Technology-oriented sectors benefit from a favourable regulatory environment, large volumes of structured data and significant IT resources. But it also benefits certain sectors such as trade or industry, which are already very committed to the digitisation of their businesses. In this respect, AI is by no means an issue limited to tech companies!
Carine Pichon, CEO of Coface France, Western Europe & Africa.
AI in client solutions and commercial risk management
AI has been a subject of discussion for years, but the emergence of generative AI has brought it back to the forefront, thanks to more accessible and user-friendly applications. Within organizations, AI adoption has followed a horizontal trajectory: initially tested in specialized functions like IT and risk management, it has since expanded to areas such as HR and finance, driving exponential growth in its use.
As AI continues to integrate into core business operations, decision-makers are increasingly focused on practical applications:
- How can AI be effectively integrated and tailored to my company’s operations?
- What tangible benefits can it bring to clients?
- How can AI enhance commercial risk assessment?
Two global leaders provide insights into their AI strategies:
- Schneider Electric, a global leader in industrial technology, leverages AI to optimize client solutions—as well as its credit risk management.
- Sonepar, the world’s top distributor of electrical equipment for professionals, harnesses AI to deliver an omnichannel experience and a highly customized value proposition.
Explore the key challenges, risks, and opportunities of AI—an industrial revolution in the making?—alongside our experts by watching the replay of the Coface Country Risk Conference 2025.
