{
  "id": 5002018,
  "title": "AI makes work faster but not necessarily companies more productive",
  "url": "https://urgent.news/2026/09/02/ai-makes-work-faster-but-not-necessarily-companies-more-productive-5002018",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-02T03:00:00.000Z",
  "source": {
    "name": "The National Business",
    "slug": "the-national-business",
    "url": "https://www.thenationalnews.com/future/technology/2026/09/02/ai-makes-work-faster-but-not-necessarily-companies-more-productive/"
  },
  "original_language": "en",
  "account": "Artificial intelligence (AI) offers remarkable speed in completing tasks, from drafting documents to generating code and responding to customers. However, companies investing heavily in AI are still grappling with a fundamental question: where is the economic value?\n\nThe issue lies in the distinction between making individual tasks more productive and creating overall organizational value. Reducing the time taken to complete a single task is beneficial, but it does not automatically translate into enhanced organizational effectiveness.\n\nPwC's January 2026 survey of 4,454 chief executives revealed that 56% reported no financial benefit from AI implementation. This phenomenon is not new; similar patterns were observed in the 1980s when computers were introduced. Initially, the benefits of information technology were not immediately reflected in productivity statistics. The key takeaway is that new technologies need time to generate returns, and technological change must be accompanied by organizational change.\n\nThere are three levels at which this mismatch occurs. First, organizations must reconsider what they aim to achieve through AI. Efficiency gains, such as completing tasks faster, are obvious business cases. However, efficiency and value creation are not synonymous. As AI capabilities become more widely available, standardized activities may become less differentiated. The real question is what an organization can accomplish with AI that was previously too costly, slow, or demanding of scarce expertise. In the UAE, where the economy is pursuing growth and diversification, AI's value lies not just in reducing labor costs but also in leveraging scarce expertise to evaluate more opportunities, serve more customers, and provide services that were previously uneconomic.\n\nSecond, organizations need to redesign how work fits together. When AI performs certain tasks, it creates a potential fragility in the overall workflow. Each component may become faster, but the entire workflow can become more vulnerable. Human activities that catch unusual cases, question assumptions, connect information across stages, and take responsibility when issues arise are essential. Therefore, the crucial question is not just \"Can AI do this task?\" but \"If AI does this task, who can verify its output, and who remains accountable?\"\n\nThird, organizations must rethink the role of human workers. Traditionally, the approach has been to allocate tasks to AI that it performs better and retain human roles for the remaining tasks. However, this approach risks defining human work as a shrinking residual. Instead, a better model is to view humans as responsible for larger units of output, supported by AI agents that execute parts of the work. Two critical human capabilities in this framework are problem formulation – determining what problems need solving – and solution validation – assessing whether an AI-generated answer is sufficient for action.\n\nThis shift also alters how organizations perceive human capital. Equipping employees with new technical skills is crucial, but it is equally important to rethink how roles, capabilities, and learning evolve as AI becomes embedded in everyday work. Another emerging concern is the potential weakening of tomorrow's workforce due to AI automating the learning experiences of junior employees. A recent study found a 9% decline in junior employment at AI-adopting firms. The AI productivity paradox, therefore, is fundamentally an organization-design problem. To fully capitalize on AI's potential, organizations must redesign at three interconnected levels: their objectives, how their workflows integrate human and AI contributions, and what people ultimately remain responsible for. As AI becomes more capable, organization design becomes increasingly crucial, not less. The ease of decomposing work and assigning specific tasks to machines underscores the importance of deciding how these pieces should be reassembled into an accountable whole. Organizations that best manage this restructuring are likely to capture the most value from AI.",
  "summary": "Artificial intelligence presents organisations with a curious paradox. The technology can draft documents, analyse information, generate code and respond to customers in a fraction of the time these activities once required. Yet executives investing heavily in these capabilities are still asking a basic question: where is the corresponding economic value? There is less of a contradiction here…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 2,
    "also_reported_by": [
      {
        "outlet": "The National UAE",
        "title": "AI makes work faster but not necessarily companies more productive",
        "url": "https://urgent.news/2026/09/02/ai-makes-work-faster-but-not-necessarily-companies-more-productive",
        "published": "2026-09-02T03:00:00.000Z"
      }
    ]
  },
  "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."
}