In recent times, one of the most common explanations for layoffs has been the rise of AI and productivity gains. However, the data behind this narrative suggests the need for a more balanced perspective.
According to the Gartner 2026 Future of Work trends, only 1% of layoffs attributed to AI driven productivity improvements in the first half of 2025 were directly linked to measurable increases in productivity. This finding suggests that workforce reductions are often shaped less by technological necessity and more by strategic and managerial choices.
AI Has Accelerated, But Has Decision Quality Improved at the Same Pace?
AI can accelerate processes, reduce costs, and enable organizations to access and analyze larger volumes of information. However, faster processes do not automatically translate into better decisions.
Organizations can now generate more analyses in a shorter time. Yet this does not necessarily mean that strategic accuracy, risk assessment, or long term impact analysis improves at the same pace.
Another important factor is the accuracy and reliability of AI systems themselves. A study conducted by the European Broadcasting Union and the BBC found that leading AI assistants produced significant factual inaccuracies in roughly 45% of responses to news related queries, and at least one issue appeared in 81% of responses. These findings highlight that while AI can support productivity gains, it also carries notable risks related to errors and misinformation.
The key distinction here lies between productivity and decision quality. Productivity can be enhanced through technological tools. Decision quality, however, is shaped by leadership approaches, organizational culture, and governance structures.
If AI systems are implemented without clear principles and boundaries, a speed driven operating model may create short term advantages while gradually weakening institutional trust over time.
Continuous change and the pressure for speed can also increase the cognitive load on employees. Adapting to new systems, responding to rising performance expectations, and navigating uncertain environments require significant resilience. In this context, the responsibility of leaders goes beyond investing in technology. They must also establish a decision making framework that is fair, transparent, and accountable.
AI is a tool. Workforce strategies, however, remain a matter of management choice. Sustainable organizations approach technology not just as a cost reduction mechanism, but as a way to create value and strengthen the quality of decisions. For organizations today, the priority should not be speed alone, but a deliberate and responsible direction forward.
