Artificial intelligence (AI) is already influencing healthcare, scientific research, and business decisions that shape people’s lives. Yet organizations are racing to deploy it without necessarily establishing who is accountable when it fails. That is a leadership failure.
Patients, consumers, employees, and investors all have a stake in whether companies can prove their AI is being used responsibly. They should demand that proof. The debate about AI is too often trapped between catastrophic predictions and promises of extraordinary productivity.
Both distract from the immediate problem: can an organization identify where AI is being used, establish who owns each application, and produce evidence that its outputs are checked? If it cannot, its assurances about responsible AI are public relations, not governance. The evidence reinforces the urgency.
In its 2026 AI Index Report, Stanford University’s Human-Centered AI Institute found that documented AI incidents recorded by the AI Incident Database rose from 233 in 2024 to 362 in 2025. The report also found that responsible AI benchmarking and reporting are struggling to keep pace with advances in AI capabilities. AI is advancing rapidly, but the systems needed to assess and manage its risks are not keeping up.
This matters far beyond the boardroom. In healthcare and life sciences, unchecked AI could miss an adverse event, distort a clinical finding, or generate an unsupported claim about a medicine. In other industries, it could expose private data, mislead customers, or influence decisions about money and access to essential services.
Ordinary people cannot be expected to determine whether a harmful decision originated with a human or a machine. They need institutions that can explain what happened and accept responsibility. I call one of the central dangers moral outsourcing: allowing AI to substitute for accountable human judgment.
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