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The New Developer: AI Skill Threat, Identity Change & Developer Thriving in the Transition to AI-Assisted Software Development

Published onApr 20, 2024
The New Developer: AI Skill Threat, Identity Change & Developer Thriving in the Transition to AI-Assisted Software Development

In this research study, we share original empirical research with 3000+ software engineers and developers across 12+ industries engaged in the transition to Generative AI-assisted software work. We bring a human-centered approach to pressing questions that engineering organizations are facing on the rapidly-changing possibilities of AI-assisted coding. How are developers impacted by changing demands on their roles? Where might there be emerging equity & opportunity gaps in who has access to these new development capabilities? What are the risks to the quality of technical work, and the developer productivity, thriving, and motivation which drive that technical work?

From this work we present a new evidence-based framework to help developers, engineering managers, and leaders as they grapple with failure to thrive in the transition to AI-assisted work: AI Skill Threat. AI Skill Threat describes developers’ fear, anxiety, and worry that their current skills will quickly become obsolete as they adapt to AI-assisted coding. Our framework also predicts when and why AI Skill Threat emerges: engineers who maintain a strong belief in competition and the demonstration of “innate brilliance” are more likely to report AI Skill Threat. However, engineers who report the presence of learning cultures and belonging are less likely to report AI Skill Threat.

Finally, we document new and emerging equity and opportunity gaps for software teams adopting new tooling practices. AI Skill Threat is higher for Racially Minoritized developers, who also rate the overall quality of AI-assisted coding outputs significantly lower. Both female developers and LGBTQ+ developers were significantly less likely to report plans to upskilling for new AI-assisted workflows. These and other emerging differences point toward a critical need to understand how organizations ensure that AI-assisted coding adoption is equitable and accessible, and that key insights from developers with important perspectives on the risks of AI-assisted coding are heard.

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