Companies have spent billions on artificial intelligence, yet most of the decisions that affect their customers are still made without it, and few leaders can explain the ones AI does make.
That is the central finding of FICO’s 2026 State of Responsible AI report, produced with Corinium Global Intelligence and now in its fifth year. Of the 1,004 senior technology, risk and data leaders surveyed, just 5.2% say they are very confident explaining their AI-driven decisions to regulators and customers. More than a third, 37.3%, are neutral or not confident at all. Meanwhile, 71.5% of customer-impacting decisions are still made without AI.
“Most organisations can tell you where and what their AI decided. Far fewer can tell you why,” said Scott Zoldi, chief analytics officer at FICO. He argued that the gap points to missing responsible AI standards and techniques, which in turn limits how willing organisations are to use AI in decisions that affect customers. “As regulators and customers scrutinize how AI is used in decision-making, auditability and explainability are nonnegotiable,” he said.
Strong returns, but legacy processes still dominate
The study found no shortage of financial payoff. Some 85.1% of respondents say AI has met or exceeded their ROI expectations. Yet most enterprise decisions still depend on older methods. Humans make 33.3% of them, rules-based systems 21.4%, and standard analytics 16.8%.
FICO’s argument is that closing this divide requires standards that earn trust for AI, so that the technology can take a seat in decisions that still run on instinct and legacy rules.
What leaders say would help most
Asked which responsible AI practice would make the biggest difference, respondents most often named model development standards, at 71.9%. Interpretable model architectures followed at 67.9%. Companies are also acting on this: 58.8% use bias detection tools, and 53.5% regularly audit their AI models.
The timing matters. AI regulation is intensifying worldwide, and policymakers are proposing frameworks that would mandate responsible AI practices. Leaders who cannot explain their systems risk losing the trust of both regulators and customers.
A missing platform, and a people problem
Part of the challenge is technical. Only 8.2% of organisations have a single shared AI deployment platform fully in place, while 71.2% have one partially in place. Almost all respondents, 96.4%, believe closer collaboration between AI and technology leadership on a shared platform would unlock additional returns.
The other part is organisational. Resistance to change (61.4%) and a lack of shared understanding of AI (58.4%) are the two leading barriers to internal alignment. Looking five years out, 63.2% name workforce skills falling behind the pace of AI adoption as their top risk, while loss of control over AI systems ranks last at 10.4%. Leaders appear more worried about their people keeping pace than about the technology getting away from them.
“A year ago, there were serious questions about whether AI would deliver returns. Today, the top question facing executives is how to scale the technology enterprise-wide,” said Lariza Carrera, Production Director at Corinium Global Intelligence. “Increasingly, the answer has less to do with the technology itself and more to do with the people running it.”
Agentic AI remains stuck in pilots
Despite the hype, agentic AI is far from mainstream. Only 2.4% of leaders have deployed it broadly across customer-facing use cases, and 71.5% are still in early exploration or pilot phases. Security concerns (40.1%) and data integration or quality challenges (38.3%) are the most-cited barriers to getting returns from it.
Leaders also do not expect agents to pay off first. Over the next 18 months, they see more ROI from domain-specific language models (49.5%), generative AI (48.7%) and interpretable model architectures (46.6%) than from agents (27.5%).
“Agentic AI is still in early experimentation mode, and that’s exactly when the groundwork matters most,” said Rachael Hadaway, VP of AI Product at FICO. “The leaders investing in security and data integration today are building the foundation for autonomy at scale.”