Software development is at an inflection point. As agentic AI reshapes how teams build, deploy, and manage applications, the boundaries between developers, tools, and systems are dissolving.
The 2026 IDC FutureScape: Worldwide Developer and DevOps Predictions explores this evolution across four major shifts: from developers guiding AI-augmented tools, to intelligent agents reshaping DevOps, to organizations mastering multi-agent orchestration, and finally to the rise of structured agent development itself.
These predictions trace a dual shift: developers are simultaneously learning to work with intelligent agents and learning to build them. Both paths demand new skills, new development paradigms, and new models for scaling and governing AI across the enterprise.
The path of transformation: Developers as orchestrators
By 2030, 70% of developers will partner with autonomous AI agents, shifting human developers toward planning, design, and orchestration and transforming the developer tools ecosystem.
Autonomous AI agents will redefine what it means to build software. These systems will act as intelligent extensions of the development process, generating code, identifying bugs, refactoring systems, and proposing architectural improvements. This shift allows developers to move from repetitive work to higher-value problem-solving.
The human role becomes one of oversight: assigning tasks, validating outputs, and refining results. Architecture and code reviews remain essential, with human teams ensuring that AI-generated contributions meet performance, design, and security standards. At the same time, AI enhances productivity by flagging vulnerabilities, enforcing consistency, and surfacing optimizations that might otherwise go unnoticed.
As AI integration deepens, developers will take on greater responsibility for designing, guiding, and governing agent behavior. Their focus will shift toward planning, orchestration, and oversight to ensure that automation supports organizational goals while remaining ethical, explainable, and secure.
From linear pipelines to adaptive systems
By 2030, 70% of organizations will embed AI agents in DevOps and DevSecOps pipelines to execute development and security workflows, as platform engineering enables standardization at scale.
Software delivery is evolving from automated pipelines to intelligent ecosystems. AI agents will be embedded across development and security workflows, automatically handling code testing, deployment, and compliance checks. These agents will work around the clock, accelerating delivery while reducing the chance of human error.
Platform engineering will provide the foundation for this model. Consistent standards, APIs, and observability across teams will ensure that agents can operate securely and reliably at scale. This transformation allows organizations to balance innovation with governance as automation reaches new levels of efficiency.
The shift to agentic delivery represents a significant inflection point for DevOps. It’s not just about doing things faster but about creating a pipeline that can continuously learn, adapt, and improve. Organizations that prepare for this change will see shorter release cycles, stronger security, and a level of agility that defines the next generation of software delivery.
The governance imperative
By 2029, the risks and complexity of multi-agent orchestration will drive organizations to intensify strategy, boost COE resources, and increase spending on AI governance and monitoring tools by 35%.
As organizations move from using a handful of independent agents to managing vast networks of interconnected ones, the challenge becomes one of control and accountability. This scale and complexity introduce new risks: agents operating outside policy boundaries, misaligned decision-making, and cascading failures that can ripple across entire platforms.
Organizations that succeed will treat governance as a continuous discipline embedded in every layer of operations. Investing in robust oversight, centers of excellence, and monitoring systems will not only mitigate risk but also unlock faster innovation. With the proper governance structure, multi-agent systems become an engine for resilience.
For technology leaders, the message is clear: as AI-driven automation scales, so must your governance. The companies that get this balance right will be the ones that innovate confidently, able to harness the full potential of agentic systems, while others are still managing unexpected complexity.
Building agents, not just using them
By 2028, facing a 10x increase in agents deployed, 60% of the G2000 will adopt an agent development life cycle for effective scale-up of agentic AI across the enterprise.
As AI agents multiply across the enterprise, organizations will need a structured way to manage their creation, training, and governance. Traditional development methods aren’t built for the complexity of agentic systems that learn, reason, and evolve. The Agent Development Life Cycle (ADLC) will become the backbone of how companies scale AI safely and effectively.
ADLC introduces a new paradigm for development. It integrates large language models with reasoning engines, memory systems, and continuous feedback loops to ensure agents can adapt intelligently over time. This advancement means development must evolve from static product releases to dynamic, ongoing systems of improvement. The ADLC provides the structure and guardrails to keep pace with AI’s rapid learning cycles while maintaining transparency and trust.
For business leaders, this is more than an IT initiative. It’s a strategic capability that redefines how value is created and maintained. Companies that achieve ADLC maturity early will be able to deploy agentic AI faster, respond to market shifts in real time, and continuously improve business outcomes. Those who delay will find themselves limited by outdated processes, unable to manage AI complexity at scale.
The new developer paradigm takes shape
As developers build with AI agents, they’re also building AI agents. These aren’t separate tracks but interconnected practices that inform and reinforce each other. The new paradigm is characterized by developers who are simultaneously users, creators, and governors of intelligent systems. Organizations that recognize this evolution will move faster and more confidently, developing the skills and structures needed to operate at both levels. Mastery of this dual capability will define what it means to develop software in the agentic era.
These predictions come from IDC’s FutureScape: Worldwide Developer and DevOps 2026 Predictions. For the complete research on how agentic AI is reshaping software development, delivery, and governance, explore the full report.
To understand how these developer shifts connect to the broader agentic enterprise transformation, visit IDC’s FutureScape 2026 Predictions and join our webinar series for actionable insights on navigating the agentic era across your organization.
