Software Engineers See 70% Productivity Leap with Generative AI

By Greg Tavarez, TMCnet Editor  |  February 27, 2024

Generative AI initiatives, which involve the use of AI to create new content or complete tasks, have demonstrably led to increased productivity across various industries. We know what these tools can do. They automate repetitive tasks, generate code and identify potential errors.

For example, chatbots powered by GenAI can handle routine customer inquiries. Because of this, human representatives can focus on more complex issues. Similarly, GenAI can generate targeted marketing content, personalize emails and optimize ad campaigns.

Ness Digital Engineering, a full-lifecycle digital services transformation company and a subsidiary of KKR, and Zinnov, a global management and strategy consulting firm, wanted to dig a bit deeper. So, they conducted a new joint study that measures the actual productivity gains resulting from deploying GenAI at an engineering level.

The study, uniquely framed to help CTOs, CIOs and CPOs understand the technology and psychological drivers of engineering productivity and the long-term ramifications on business and organizational design, had some interesting results.

The study suggests that the implementation of GenAI in businesses can lead to better productivity gains, enable deeper contextual awareness, and pave the way for seamless globalization of work. These factors, the study argues, have the potential not only to improve business outcomes but also to fundamentally reshape organizational design.

Engineers reported the most significant impact when utilizing GenAI for existing codebase functions, experiencing a 70% reduction in task completion time for existing code updates and a subsequent decrease in development cycle time. This, in turn, freed up senior engineers' time, who saw a 48% reduction in their task completion time, allowing them to dedicate more effort to strategic planning and mentoring junior colleagues.

Additionally, GenAI demonstrated its capability in simplifying complex coding scenarios. The result is a roughly 10% reduction in the time it takes to complete high-complexity tasks. But perhaps most notably, the study found a 70% improvement in employee engagement. By streamlining tasks and fostering a more collaborative and dynamic work environment, GenAI is found to play a crucial role in creating a positive and fulfilling work experience for employees.

“GenAI stands poised to transform the software development landscape,” said Ranjit Tinaikar, CEO, Ness Digital Engineering. “To fully harness the power of GenAI, we collaborated with Zinnov to understand the impact of GenAI on software development and its nuances. The study serves as a guide on the impact of GenAI on product development process, organization structures, employee engagement, learning, and development.”

These findings challenge traditional organizational structures, advocating for a shift toward a model that prioritizes expertise and efficiency, alongside human control and decision-making, facilitated by technology. This implies a future workforce where domain expertise and problem-solving skills hold greater value than purely technical proficiency.

Senior personnel are likely to transition from individual contributors to mentors and problem-solving strategists, while junior professionals will benefit from increased guidance and faster development.

“Generative AI is now integrated into software engineering workflows across many organizations, aiding in tasks like generating test cases, refactoring code and identifying innovation opportunities,” said Pari Natarajan, CEO, Zinnov. “This study validates the belief that generative AI complements rather than dictates workflows, facilitating frictionless knowledge sharing and unlocking the true value of globalization.”

While the study highlights the potential benefits of GenAI, it is important to acknowledge that ethical considerations and responsible implementation are paramount (which my team and I have discussed countless times). As with any transformative technology, ensuring transparency, addressing potential biases and fostering human-machine collaboration is key to reap the full benefits of GenAI while mitigating potential risks.

Edited by Alex Passett
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