AI, initially hailed as a tool for supreme productivity and making workers "superhumans," has instead increased employee workloads. Data indicates that workers using AI are spending up to 346% more time on daily tasks, with email time doubling and focused work sessions decreasing by 9%. This directly contradicts promises from tech CEOs and demonstrates that AI does not inherently reduce workloads but rather strains them.
In response to this, some companies are aggressively pushing AI adoption. Accenture, for example, is making "regular adoption of AI tooling" a requirement for promotions to top roles and is tracking employee usage of its AI platforms. Similarly, KPMG has developed a dashboard to monitor whether US employees meet a 75% usage target for its AI tools, framing this as a move to help employees advance up the "AI maturity curve" and linking it to potential promotions. This push highlights the "carrot and stick" approach firms are taking, especially with older, more senior employees who are often less comfortable with new technology.
However, this aggressive adoption strategy is backfiring. A significant number of white-collar workers, up to 80%, are quietly rebelling against AI adoption mandates. Many firms lack a clear strategy for AI, with less than a third of civil servants consulted on its rollout, leading to "inconsistent" implementation and a limited return on investment. Malcolm, an AI engineer, recounted an instance where executives insisted on using generative AI for customer categorization, despite a traditional machine learning model being more accurate and cost-effective, illustrating a fundamental misunderstanding of AI's appropriate application. This confusion at the top means AI investments often fail to deliver expected benefits.
Furthermore, the introduction of AI "employees" is creating new workplace problems. Human employees are more likely to blame these AI counterparts for mistakes, and there's a risk of human workers becoming sloppier and lazier. Experts warn that if AI technology is layered on top of a fragmented or fear-based company culture, it is unlikely to succeed, resulting in slow rollouts or wasted efforts. A senior consultant noted that organizations are not achieving the expected return on investment because employees are not properly engaging with the tools, often due to a lack of clear strategy and understanding from leadership. Many businesses, despite expecting AI to transform their workforces, have no clear owner for their AI strategy, with one-third of HR professionals stating this is the case.
