UK Executives Outsourcing Critical Decisions to AI, Survey Finds

A survey of 200 UK business leaders has revealed a dramatic shift in corporate decisionmaking, with the majority now relying on artificial intelligence to guide their most critical choices. The findings, published by data streaming vendor Confluent, paint a picture of executives increasingly abdicating their judgment to machine learning models in an attempt to keep pace with accelerating business demands.

The research, conducted by market research agency 3Gem in late 2025 and titled "Quick Thinking 2.0," surveyed owners, founders, CEOs, managing directors, and C-level leaders across the UK's private sector. When asked about their decisionmaking processes, 62 percent of respondents admitted that AI now makes the "majority" of their decisions. This represents a fundamental shift in how corporate leadership operates, with human executives increasingly serving as intermediaries between AI recommendations and organizational action.

Perhaps most concerning is that 70 percent of executives reported second-guessing their own judgments when those decisions conflict with AI recommendations. This suggests a growing psychological dependence on algorithmic guidance, where human intuition and experience are being systematically devalued. The survey also found that 65 percent of leaders felt decisionmaking had become less collaborative since adopting AI tools, a finding that raises questions about the erosion of team-based leadership approaches.

Richard Jones, VP of Northern Europe for Confluent, acknowledged the trend while attempting to frame it positively. "It's easy to see why so many UK leaders are leaning on AI when making high-pressure decisions," Jones said. "When the stakes are high, AI can feel like a neutral voice that processes information quickly and offers clear recommendations."

However, the data suggests this "neutral voice" may be drowning out other perspectives. Nearly half of surveyed executives (46 percent) now rely on AI more than they do on advice from colleagues and team members. This represents a significant departure from traditional leadership models that emphasize diverse input and collaborative problem-solving.

Interestingly, executives showed more restraint when it comes to AI involvement in personnel decisions. Only 27 percent trusted machines to help with hiring and firing decisions, likely due to legal and ethical concerns. In the United States, using AI for employment decisions carries legal implications. The US Equal Employment Opportunity Commission under the Biden administration warned that employers could be held liable for discrimination caused by third-party AI tools. While federal guidance has since been withdrawn, several US states including Illinois, Colorado, and New York have enacted regulations governing automated employment decisions.

The survey also revealed mounting pressure on executives to make faster decisions. A striking 92 percent of respondents said the speed required for business decisions has increased over the past three years, up from 83 percent in Confluent's previous survey. This acceleration appears to be driving the adoption of AI tools as executives seek to keep pace with what they perceive as an increasingly volatile business environment.

Yet this rush to embrace AI-driven decisionmaking comes with significant risks. A 2025 research study found "a significant negative correlation between frequent AI tool usage and critical thinking abilities, mediated by increased cognitive offloading." In other words, the more executives rely on AI for decisions, the less capable they become of independent critical analysis.

Writer Lila Shroff has coined the term "LLeMmings" to describe people who outsource their thinking to AI systems. The term captures the concerning dynamic where human decisionmakers become passive followers of algorithmic recommendations rather than active, critical thinkers.

Confluent argues that AI usage represents a natural evolution for real-time data streaming, claiming that machine learning can process information at scales impossible for humans. "The future of leadership is about arming both humans and machines with the right data to make the right calls," the report states. "Right now, CEOs feel squeezed. Instinct is being overridden, AI is stepping in but without real-time data, and neither can reach their full potential."

This latest trend bears striking similarities to previous waves of "executive decision support" technologies from the 1980s and 1990s. Then, as now, vendors promised that sophisticated software would enhance executive decisionmaking by providing rapid access to critical information. The difference today is that AI systems don't just present information—they actively make recommendations and, in many cases, execute decisions autonomously.

The implications extend beyond individual companies. As more organizations adopt similar AI-driven approaches, entire industries may begin to converge toward algorithmic consensus rather than diverse strategic thinking. This could reduce competitive differentiation and create systemic vulnerabilities if widely adopted AI models share common blind spots or biases.

For now, the trend appears to be accelerating rather than slowing. As business leaders continue to face mounting pressure to make faster decisions in increasingly complex environments, the temptation to outsource critical thinking to AI systems will likely grow stronger. The question that remains unanswered is whether organizations can maintain the innovative edge and strategic agility that traditionally came from human judgment and diverse perspectives in an era of algorithmic decisionmaking.