The integration of agentic AI coding tools into corporate engineering workflows is rapidly transforming the software development landscape. These autonomous systems are not merely assisting developers but are increasingly taking on tasks independently, leading to significant shifts in productivity and workflow dynamics.
Between December 2024 and May 2025, a study involving over 400 companies revealed a substantial increase in the adoption of agentic AI tools. Initially, just over half of these organizations utilized such tools; by May, this figure had surged to 82%. This trend indicates a growing confidence in AI's ability to handle complex engineering tasks autonomously.
Unlike traditional AI assistants that offer suggestions or generate small code snippets, agentic AI systems perform actions such as writing code, initiating code reviews, submitting commits, and providing feedback without human intervention. This evolution marks a significant departure from interactive systems requiring constant oversight to more autonomous operations.
Popular tools facilitating this shift include GitHub Copilot Reviewer, Cursor BugBot, and CodeRabbit. Emerging platforms like Graphite, Greptile, and Bito.ai are also gaining traction, reflecting a diverse and expanding market for AI-driven code review solutions.
Tools like Claude Code, Devin, and Codex are at the forefront of this movement, enabling teams to delegate entire programming tasks to AI systems. This rapid adoption underscores a readiness among firms to embrace deeper automation in their development processes.
As agentic AI continues to evolve, engineering organizations must adapt their processes to integrate these tools effectively, balancing the benefits of automation with the need for human oversight and creativity.
Note: The information presented is based on data from Jellyfish’s engineering management platform and reflects trends observed between December 2024 and May 2025.
Source: Digital Information World Agentic AI Coding Tools Gain Momentum in Corporate Engineering Workflows
The Rise of Agentic AI in Software Development
Between December 2024 and May 2025, a study involving over 400 companies revealed a substantial increase in the adoption of agentic AI tools. Initially, just over half of these organizations utilized such tools; by May, this figure had surged to 82%. This trend indicates a growing confidence in AI's ability to handle complex engineering tasks autonomously.Unlike traditional AI assistants that offer suggestions or generate small code snippets, agentic AI systems perform actions such as writing code, initiating code reviews, submitting commits, and providing feedback without human intervention. This evolution marks a significant departure from interactive systems requiring constant oversight to more autonomous operations.
Automated Code Reviews: A Gateway to AI Integration
Automated code reviews have emerged as a primary entry point for AI adoption in software development. The proportion of companies employing AI-powered code reviews increased from 39% in January to 76% by May 2025. Early adopters report that these tools now manage up to 80% of all code reviews, leading to modest yet measurable efficiency gains, including faster review cycle times.Popular tools facilitating this shift include GitHub Copilot Reviewer, Cursor BugBot, and CodeRabbit. Emerging platforms like Graphite, Greptile, and Bito.ai are also gaining traction, reflecting a diverse and expanding market for AI-driven code review solutions.
Advancing Toward Fully Autonomous Coding Workflows
Beyond code reviews, a growing number of companies are exploring fully agentic coding workflows, where AI agents not only review but also write and submit code into production pipelines. Although still in the early stages, the adoption rate for these workflows increased from less than 2% in January to nearly 8% by May 2025.Tools like Claude Code, Devin, and Codex are at the forefront of this movement, enabling teams to delegate entire programming tasks to AI systems. This rapid adoption underscores a readiness among firms to embrace deeper automation in their development processes.
Implications for Engineering Teams and Productivity
The shift toward agentic AI tools signifies a fundamental change in engineering workflows. By automating routine and complex tasks, these tools allow developers to focus on higher-level problem-solving and innovation. However, this transition also necessitates new strategies for managing AI-human collaboration, ensuring code quality, and addressing potential ethical considerations.As agentic AI continues to evolve, engineering organizations must adapt their processes to integrate these tools effectively, balancing the benefits of automation with the need for human oversight and creativity.
Note: The information presented is based on data from Jellyfish’s engineering management platform and reflects trends observed between December 2024 and May 2025.
Source: Digital Information World Agentic AI Coding Tools Gain Momentum in Corporate Engineering Workflows
