Software developer at crossroads, AI code vs traditional coding

AI's Productivity Paradox: How ChatGPT Bans Impacted Coders & What It Means for Your Workflow

Reese Marlowe in Tech & Innovation December 2025 • 4 min read.

"Discover the surprising ways a ChatGPT ban affected software developers in Italy, revealing crucial lessons about AI's role in productivity and skill development."

The rise of generative AI tools like ChatGPT has sparked intense debate. Are these technologies a boon to productivity, or do they introduce new challenges? While many celebrate AI's potential to automate tasks and boost output, recent research suggests the reality is far more complex. A groundbreaking study analyzed the impact of Italy's ChatGPT ban on software developers, revealing surprising insights about AI's heterogeneous effects on productivity.

Italy's ban on ChatGPT in early 2023 offered a unique opportunity to study the real-world effects of restricted AI access. Researchers tracked the coding output and quality of over 36,000 GitHub users in Italy and other European countries, using a difference-in-differences framework to isolate the ban's impact. The findings challenge the simplistic notion that AI universally boosts productivity, highlighting the importance of user experience and task complexity.

This article delves into the study's findings, exploring how the ChatGPT ban affected developers with varying levels of experience. We'll examine the short-term consequences of restricted AI access, uncover the unexpected ways developers adapted, and discuss the implications for businesses and individuals navigating the evolving landscape of AI-powered work.

The Unexpected Twist: AI's Impact on Productivity

Software developer at crossroads, AI code vs traditional coding

The study's most striking finding was that the ChatGPT ban's impact varied significantly based on developer experience. Less experienced developers actually saw a short-term increase in both output quantity and quality. Without ChatGPT, they became more productive, while seasoned developers experienced the opposite. The decreased quality could indicate that the AI assists less skilled workers to complete tasks.

Conversely, experienced developers faced a decrease in productivity, particularly on more routine tasks like resolving issues and debugging. This suggests that experienced developers may have become reliant on ChatGPT for these tasks, and its absence disrupted their workflow. This reliance, or over-reliance, on AI is not unheard of.

Increased output for beginners: Those new to coding found themselves doing more without the AI, showing reliance and potential over-dependence on such systems.
Slowdowns for experts: Experienced coders found that simple tasks took far longer and were more cumbersome without the tool.

These findings challenge the assumption that generative AI universally boosts productivity. Instead, the impact depends on the user's skill level and the nature of the task. While less experienced developers may benefit from AI assistance, experienced developers may become over-reliant, hindering their ability to perform routine tasks independently.

Lessons Learned: Adapting to an AI-Driven World

The study's findings offer valuable lessons for individuals and organizations navigating the age of AI: Generative AI's effects are not uniform, but depend greatly on the users' experience levels and the complexity of the task. To realize the best results, organizations need to tailor AI tools to match the demands and skills of their workers.

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Everything You Need To Know

How did Italy's ban on ChatGPT in early 2023 provide insights into AI's effects on software development?

The ChatGPT ban in Italy created a natural experiment, allowing researchers to compare the coding output and quality of over 36,000 GitHub users in Italy and other European countries. By using a difference-in-differences framework, they were able to isolate the ban's impact and reveal how restricted AI access affected developers with varying levels of experience. This approach offered a real-world view of AI's influence, challenging assumptions about its universal benefits. However, the study does not cover other potential factors influencing developer productivity during that period, such as changes in project demands or team dynamics.

What were the surprising findings regarding the impact of the ChatGPT ban on software developers with different experience levels?

The study revealed that the ChatGPT ban led to increased productivity in less experienced developers, as they showed more output and quality, potentially due to reduced over-reliance on AI. Conversely, experienced developers experienced decreased productivity, particularly on routine tasks like issue resolution and debugging, suggesting they had become dependent on ChatGPT. These results indicate that the impact of generative AI is not uniform and can depend on user expertise and task complexity. The study does not delve into the specific types of tasks where ChatGPT was most beneficial or detrimental.

What does the study suggest about the assumption that generative AI universally boosts productivity?

The study challenges the idea that generative AI inherently boosts productivity for everyone. It demonstrates that the impact of tools like ChatGPT varies significantly depending on the user's skill level and the nature of the task. While less experienced developers may benefit from the assistance of AI, experienced developers may become over-reliant, which could hinder their ability to perform routine tasks independently. This finding highlights the importance of tailoring AI integration strategies to the specific needs and skills of workers. However, the study does not explore potential long-term effects on skill development or adaptation strategies beyond the immediate response to the ban.

What can organizations learn from the effects of the ChatGPT ban in Italy regarding AI adoption?

Organizations should recognize that the effects of generative AI tools are not uniform. They need to tailor AI tools to match the demands and skills of their workers to realize the best results. The study implies that a one-size-fits-all approach to AI integration can be ineffective or even detrimental. The findings suggest that organizations should provide targeted training and support to help developers of all experience levels effectively use AI tools without becoming over-reliant on them. This study doesn't include the cost or impact of training programs.

What are the implications of over-reliance on AI tools like ChatGPT for experienced software developers?

Over-reliance on tools like ChatGPT can hinder the ability of experienced software developers to perform routine tasks independently. The study indicates that these developers may become less productive when AI assistance is unavailable, particularly for tasks such as resolving issues and debugging. This dependence can limit their problem-solving skills and adaptability in situations where AI tools are restricted or unavailable. This also has implications for software development teams. This study however does not delve into potential ways to mitigate this risk, such as regular skill assessments and retraining programs.