Artificial intelligence (AI) has become an indispensable business tool. From summarising information and identifying patterns to accelerating research, AI has transformed the way organisations gather intelligence on prospective clients.
For businesses seeking to manage risk, improve decision-making or protect their interests, AI can provide a valuable starting point during the client vetting process. However, while AI offers considerable advantages, it should never replace trusted sources of information or experienced human judgement. The key question for any business is not whether AI should be used, but rather – where should the line be drawn.
One of AI’s greatest strengths is its ability to process large volumes of publicly available information within seconds. Instead of spending hours searching multiple websites, reviewing company profiles or analysing news articles, businesses can quickly obtain a broad overview of a prospective client. Large Language Models (LLM’s) – a type of AI – are models trained on massive amounts of text and are particularly useful for identifying publicly reported litigation, adverse media, company histories, industry trends and other readily available information. This significantly improves efficiency and enables teams to focus their attention on areas that require deeper intuition.
Despite these advantages, AI has important limitations that every organisation should recognise. AI systems do not possess first-hand knowledge or real-world experience of a business relationship. Their outputs are largely based on publicly available data, which may be incomplete, outdated or inaccurate. Information found online can remain available long after circumstances have changed, while equally important information may never have been published at all. Furthermore, AI can occasionally generate incorrect conclusions by combining unrelated facts or presenting assumptions as though they are established facts. These inaccuracies, sometimes referred to as ‘hallucinations’, reinforce the need to verify any information before relying upon it for commercial decisions.
Another significant consideration is context. Creditworthiness, payment behaviour and commercial reliability often extend well beyond what is publicly visible. A company may have an excellent online reputation while consistently paying suppliers late. Conversely, a business facing temporary financial pressure may continue to honour its obligations through strong supplier relationships and sound management. AI is generally unable to distinguish between these nuances because much of this information exists only through direct commercial experience rather than publicly accessible data.
For this reason, organisations should avoid making client acceptance or credit decisions based solely on AI-generated information. Instead, AI should serve as an initial screening tool that identifies areas requiring further investigation. Final decisions should be supported by verified information obtained from reputable and independent sources.
Trusted business information providers remain essential in the vetting process because they combine multiple verified datasets with practical market intelligence. Credit bureaux, trade references, financial statements, legal records, payment histories and verified company information provide a far more comprehensive assessment of commercial risk than AI alone can deliver. Equally valuable are organisations that maintain direct relationships with businesses, suppliers and industry participants, enabling them to provide practical insight into how a company behaves in real trading environments. This type of intelligence reflects actual commercial experience rather than simply what appears online.
Experienced credit professionals also continue to play a critical role. Their ability to interpret financial information, recognise emerging risks, identify inconsistencies and understand broader market conditions cannot be replicated entirely through automated systems. Human judgement allows businesses to balance objective data with commercial experience, resulting in more informed and defensible decisions.
As AI technology continues to evolve, its role within business due diligence will undoubtedly expand. Nevertheless, responsible organisations should view AI as a decision-support tool rather than a decision-maker. Its purpose is to improve efficiency, highlight potential concerns and assist with information gathering – not to replace professional expertise or trusted commercial intelligence.
Ultimately, effective client vetting requires a balanced approach. AI offers speed, convenience and valuable research capabilities, but businesses should always verify its findings through credible, independent sources and experienced professionals with genuine exposure to the marketplace. By combining technological innovation with trusted business intelligence and informed human judgement, organisations can reduce risk, strengthen decision-making and build more reliable commercial relationships.
