The risk for AI creating “efficient inefficiency”

Author Moonshot.news

Published on: 14/04/2025

If AI is used to carry out “bullshit tasks”, it will lead at most to “efficient inefficiency”. There’s much hype about the efficiency of artificial intelligence. But technology adoption is not simply a technical process. Organisations must look beyond existing tasks and consider how they should change, two researchers at University of Leeds argue in a report published in Journal of Business Research and presented in LSE Business Review.

“The central question is rarely whether a technology can perform a task, but whether the task is worth performing at all. Those who ignore this question risk overlooking the problem of efficient inefficiency. They also miss the opportunity to rethink the problem of organisation and to find novel solutions to it”, write Stuart Mills, Assistant Professor at University of Leeds and Visiting Fellow at London School of Economics and David A Spencer, Professor at University of Leeds.  

Products like OpenAI’s ChatGPT have great potential to increase productivity and contribute to economic growth. Whether this potential is realised, however, will depend on how AI is used, they argue.

If AI performs inefficient tasks, it will simply lead to more efficient inefficiency – that is, it will compound inefficiency rather than tackle it. This outcome reflects the fact that the adoption of AI is an organisational process rather than just a technical one and that its capacity to raise efficiency is limited by human and social factors within organisations, they write.

If bullshit jobs are carried out by AI, this may simply perpetuate inefficiency. AI may just speed up the delivery of what are inefficient tasks to begin with, they write.

“Economists argue that inefficiency will be removed by competition. Our view, however, is that inefficiency can persist due to the interests that managers have in maintaining inefficiency.” 

“The capacity of managers to tackle efficient inefficiency may also be limited by their bounded rationality. No manager can spot every inefficient task. In practice, most managers may be focused on adopting AI to substitute for existing human tasks, regardless of their efficiency.”

“As technology companies have sought to develop AI products, the problem of efficient inefficiency is emerging. One study explored how programmers used an AI co-pilot when writing code. The study found that AI increased the amount of code written. However, it also increased the amount of code churn—broken code that programmers had to edit and fix. In this instance, AI might appear to make programmers more productive, since they are writing more code. But factoring in churn, it becomes less clear whether AI is improving efficiency or just doing something inefficient more efficiently (writing more bad code).”

“The point we would stress is that the efficiency gains from AI are not predestined but instead depend on its uses within organisations. Because of the power that managers wield and the inherent bounds to management rationality, AI will often be used to more efficiently perform inefficient tasks.”

“Dealing with inefficient efficiency ultimately calls for organisational reform, not just to tackle task inefficiency, but also to challenge management power. Democratic processes and institutions, including within organisations, are vital if AI is to work in ways that enhance incomes and well-being for all in society.”