The results of the latest FEBIS-FENCA survey on AI in Trade Credit Management reveal an industry at a critical crossroads. While expectations for AI are nearly universal, the reality of implementation shows a sector still navigating the "early adoption" phase, where productivity gains are being prioritised over full-scale automation.
Despite the significant buzz surrounding artificial intelligence, AI maturity remains relatively low across the trade credit ecosystem. 79% of organisations currently use AI in less than 25% of their credit decisions, and 36% report no AI-driven decisioning at all. The "Human-in-the-loop" model remains dominant, with 86% of respondents foreseeing AI as a tool to automate routine tasks while humans retain final judgment and accountability.
Today, the primary motivation for AI adoption is operational efficiency (75%) and cost reduction (63%), rather than transformative business outcomes. This is reflected in the most common use cases:
- Generative AI for reporting and documentation (42%) is the leading application, followed by credit scoring (34%) and data aggregation (30%).
- The industry is starting with "safe," measurable use cases that reduce manual reviews and speed up decision-making (cited by 48% of respondents).
One of the most striking findings is the gap between adoption and oversight. While organisations are eager to deploy AI, only 21% have a fully implemented AI governance framework. This lack of readiness is the primary bottleneck for scaling technology across the enterprise.
Trust and caution are particularly visible in sensitive areas: 73% of organisations do not use AI in communications with vulnerable borrowers, citing ethical and reputational risks. The most significant challenges cited by leaders include regulatory compliance (65%) and data privacy (62%).
Despite the current implementation gaps, the outlook for the next three years is overwhelmingly bullish. 93% of respondents expect AI to have a significant or transformative impact on the industry by 2029. To meet this future, investment is ramping up: 57% of organisations plan to allocate at least 5% of their total budget to AI, with 30% planning to spend more than 10%.
The delivery of data is also evolving. While batch uploads and web interfaces are still common, the industry is shifting toward real-time APIs (63%) and emerging AI agents to facilitate machine-to-machine consumption of credit data.
Conclusion
The FEBIS-FENCA data makes it clear that the growth window for AI in trade credit is open now. For firms to move beyond simple productivity tools and achieve true transformation, they must bridge the governance gap. Success will likely belong to those who adopt hybrid models (39% of the market), combining external expertise with in-house control to ensure that AI is not just delivered, but effectively operationalised.
Survey results ⬇️:
Source: FEBIS - FENCA Survey
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