LLMs and Generative AI in the enterprise.
Inspire, develop, and guide a winning organization.
Understand the unique values and behaviors of a successful organization.
Create visible workflows to achieve well-architected software.
Understand and use meaningful data to measure success.
Integrate and automate quality, security, and compliance into daily work.
An on-demand learning experience from the people who brought you The Phoenix Project, Team Topologies, Accelerate, and more.
Learn how to enhance collaboration and performance in large-scale organizations through Flow Engineering
Learn how making work visible, value stream management, and flow metrics can affect change in your organization.
Clarify team interactions for fast flow using simple sense-making approaches and tools.
Multiple award-winning CTO, researcher, and bestselling author Gene Kim hosts enterprise technology and business leaders.
In the first part of this two-part episode of The Idealcast, Gene Kim speaks with Dr. Ron Westrum, Emeritus Professor of Sociology at Eastern Michigan University.
In the first episode of Season 2 of The Idealcast, Gene Kim speaks with Admiral John Richardson, who served as Chief of Naval Operations for four years.
Exploring the impact of GenAI in our organizations & creating business impact through technology leadership.
DevOps best practices, case studies, organizational change, ways of working, and the latest thinking affecting business and technology leadership.
Just as physical jerk throws our bodies off balance, technological jerk throws our mental models and established workflows into disarray when software changes too abruptly or without proper preparation.
Leaders can help their organizations move from the danger zone to the winning zone by changing how they wire their organization’s social circuitry.
The values and philosophies that frame the processes, procedures, and practices of DevOps.
This post presents the four key metrics to measure software delivery performance.
September 12, 2024
Artificial intelligence (AI) continues to make significant inroads across various domains. But questions about its effectiveness remain. A new study provides compelling evidence that AI-powered coding assistants can substantially boost software developer productivity in real-world enterprise settings.
This research, conducted by economists from prestigious institutions including MIT, Princeton, and the University of Pennsylvania, analyzed data from over 4,800 developers at Microsoft, Accenture, and another Fortune 100 company who were given access to GitHub Copilot.
This research stands out for several reasons:
The headline 26% increase in completed tasks is a significant finding that could have far-reaching implications for software development teams. This productivity boost could potentially allow companies to deliver software projects faster, reduce time to market for new features, or tackle more complex challenges with existing resources.
The 13.5% increase in code commits and 38.4% rise in compilation frequency suggest that developers using AI assistants are producing more code and iterating more quickly. This could lead to faster prototyping, more frequent testing, and a more agile development process.
One of the most intriguing findings is the outsized benefit for junior developers and those with less tenure. The study found that:
This suggests that AI coding assistants could be a powerful tool for onboarding new developers, accelerating the productivity ramp-up for new hires, and potentially narrowing the productivity gap between junior and senior developers.
The study revealed interesting patterns in how developers adopted and used the AI assistant:
These patterns highlight the importance of change management and targeted implementation strategies when rolling out AI coding assistants.
As an enterprise technology leader, this research provides valuable insights to inform your AI strategy:
While the study’s findings are promising, it’s important to approach AI coding assistants with a balanced perspective:
The authors note that their findings may underestimate the potential impact of AI coding assistants, as the technology continues to improve rapidly. As these tools become more sophisticated, we may see even greater productivity gains and new capabilities emerge.
This research provides strong evidence that AI coding assistants are reaching a level of maturity where they can drive real business value in enterprise software development. As an IT leader, it’s crucial to start thinking strategically about leveraging these tools to boost developer productivity, accelerate innovation, and maintain a competitive edge in the fast-paced world of technology.
Want to learn more about AI in the Enterprise? Check out some of our recent guidance papers and articles on AI here.
Managing Editor at IT Revolution working on publishing books and guidance papers for the modern business leader. I also oversee the production of the IT Revolution blog, combining the best of responsible, human-centered content with the assistance of AI tools.
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