The task trap: Why AI's biggest promise has nothing to do with speed

A recent analysis from TechRadar highlights the 'micro-productivity trap' currently hindering enterprise AI adoption. While many organizations celebrate AI for its ability to accelerate individual tasks—such as coding, drafting content, or summarizing documents—the author argues that these gains are often isolated and fail to drive meaningful business value. Data from PwC and Gartner suggests that a significant portion of AI projects risk failure because companies prioritize speed over strategic outcomes. The article posits that the true potential of AI lies in upstream decision-making and business-domain intelligence rather than mere task automation. To overcome this, the author advocates for the use of 'fusion teams' that combine operational expertise with technical judgment. By focusing on contextualized data and high-quality decision-making rather than just velocity, organizations can move beyond superficial productivity gains to achieve genuine, compounding business impact in the agentic AI era.