In the Global Institute of Credit Professionals’ (GICP) latest report, ‘Credit in the Age of AI’ finds that organisations with similar levels of artificial intelligence (AI) adoption can achieve markedly different results. Success has been determined less by the technology itself and more by the organisational capability needed to embed AI effectively across its people, processes and operating models.
The findings show that AI adoption remains shallow across much of the industry. 56% of organisations currently use AI in less than 25% of their credit processes, including 14% that are not using AI at all. Adoption is currently in lower-risk activities such as document drafting, financial analysis and market research, while AI is delivering its greatest reported impact in activities closest to credit decision-making, including risk assessment and credit scoring.
Despite relatively modest levels of adoption, organisations are already seeing measurable benefits. 47% of organisations using AI across just 25% to 49% of their workflows report high organisational impact, rising to 66% among those using AI across 50% to 75% of workflows. The findings show that how organisations implement AI is just as important as how much AI they use.
The report identifies governance as one of the clearest differentiators between organisations achieving high AI-enabled impact and those struggling to realise value. 67% of organisations with eight or nine AI governance measures in place reported high AI-enabled impact, compared with just 23% of organisations with zero or only one governance measure in place.
Similarly, 50% of organisations reporting high AI-enabled impact have formal governance frameworks in place, compared with only 18% of those where AI-enabled impact remains minimal or mixed.
Organisations reporting high AI-enabled impact also introduced over twice as many workforce and workflow changes, averaging 2.58 organisational changes compared with 1.22 among organisations reporting lower AI impact, reinforcing that successful AI implementation requires organisational transformation as well as technology. However, the research also reveals a disconnect between where organisations recognise challenges and where they are investing.
65% of respondents identified leadership and governance factors as the biggest barrier to successful AI adoption, yet only 38% plan to prioritise investment in this area. The report also highlights what it describes as the ‘Two Waves of AI Value’.
The first wave has focused on productivity gains from lower-risk applications such as drafting, summarisation and research. The second wave is now emerging as organisations begin applying AI to underwriting, credit assessment and risk scoring.
Overall, across organisations expecting disruptions from generative AI, autonomous decision-making or real-time monitoring, 79% are not yet deploying AI in the corresponding functions. suggesting ambition continues to outpace organisational readiness.
“The conversation around AI has largely focused on adoption, but our research shows that adoption alone is not creating competitive advantage.
“Organisations with similar levels of AI activity are achieving very different outcomes because success depends on much more than technology.
“The organisations seeing the greatest impact are investing in governance, workforce capability and operating models that enable AI to be embedded effectively into day-to-day credit decision-making.
“As AI becomes an established part of the credit lifecycle, competitive advantage will increasingly depend on how well organisations combine technology with skilled professionals, sound judgement and effective execution.”
Andreas Karaiskos, Executive Director, Global Institute of Credit Professionals
The report concludes that as AI becomes embedded across the credit lifecycle, competitive advantage will increasingly depend on an organisation’s ability to embed AI across its people, processes and decision making.
Organisations who invest in governance, leadership, workforce capability and operational change alongside technology will be best placed to translate AI adoption into meaningful long-term business value.
