{
  "id": 11176732,
  "title": "McKinsey senior partner: Why AI’s easiest wins are misleading CEOs",
  "url": "https://urgent.news/2026/10/01/mckinsey-senior-partner-why-ais-easiest-wins-are-misleading-ceos",
  "topic": "ai",
  "section": "AI",
  "published": "2026-10-01T10:30:00.000Z",
  "source": {
    "name": "Fortune",
    "slug": "fortune",
    "url": "https://fortune.com/2026/10/01/mckinsey-senior-partner-why-ais-easiest-wins-are-misleading-ceos/"
  },
  "original_language": "en",
  "account": "McKinsey's latest research reveals that AI adoption among organizations remained steady at 89 percent this year, compared to 88 percent the previous year. Despite this growth, the percentage of high performers - those attributing at least 5 percent of earnings before interest and taxes to AI and reporting value from its use - stayed flat at 6 percent. Experts argue that while the use of AI is spreading, the corresponding increase in returns is lagging behind.\n\nThirty-seven percent of organizations report some positive effect on earnings, but the gap between widespread use and genuine benefit remains wide. To address this issue, leaders must align incentives, improve change management, and strengthen their data foundations. However, executives often mistake AI's clear successes in specific areas like customer support and software development as a universal solution, overlooking the unique challenges of redesigning work processes that lack clear outcomes and evaluation methods.\n\nFor instance, a study of customer-support agents found AI assistance increased resolved issues per hour by 15 percent, while software developers using AI coding assistants completed 26 percent more tasks on average. While these gains are significant, they do not guarantee improved company earnings as adding AI to any business process does not automatically translate to better results.\n\nContact centers and software teams had already established efficient systems before AI's arrival, making it easier for AI to enhance their performance. However, applying AI to other areas, such as document review for small-business loans in a bank, might only save a few days if the decision-making process remains fragmented and error-prone.\n\nTo truly benefit from AI, leaders must understand that it should not merely replace existing tasks but should redesign the entire process. This requires clarifying who is responsible for decision-making, how exceptions will be handled, and how to measure the effectiveness of AI implementation. Without addressing these crucial aspects, even promising AI pilots may remain inconclusive.\n\nLeaders need to communicate a clear vision for the change, acknowledging the uncertainty that comes with adopting new technology. They must explain the purpose of the transformation, even if they cannot predict every outcome. McKinsey's research indicates that organizations redesigning their workflows are 5.3 times more likely to achieve enterprise-level value compared to those that have not, highlighting the importance of strategic redesign in maximizing AI's potential.",
  "summary": "CEOs tout contact centers and software coding as AI successes. But are they? That works was already standardized, for reasons nothing to do with AI.",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}