Editorial
Agentic AI is redefining what’s possible in IT automation — accelerating enterprise productivity and reshaping the traditional role of developers. Gartner predicts that by 2028, 33% of enterprise software applications will include agentic AI, up from less than 1% in 2024, and will enable 15% of day-to-day work decisions to be made autonomously.
This rise of agentic AI — systems capable of independent decision-making and action — marks more than a shift in tools. It’s a redefinition of talent that will demand a new breed of IT professionals. Developers will transition from architects of code to conductors of complex symphonies composed of advanced AI systems. This isn’t a change in job description — it’s a reimagining of the role.
This shift demands not just technical acumen but also a deep understanding of business objectives, customer or user challenges, data privacy and security implications and risk management. Developers must work towards building a certain customer or user challenge foresight to orchestrate these systems not just for efficiency, but for responsible and impactful innovation.
The New Frontier for Coders
This new breed of developers will use their skills to integrate, manage and direct AI systems that are capable of making autonomous decisions, learning from data and performing complex tasks across various business functions.
Unlike traditional systems that often follow deterministic paths, agentic AI can generate multiple potential solutions, requiring human expertise to discern the optimal path. Herein lies the crucial role of the developer — to evaluate these suggestions through the lens of experience and contextual understanding. It’s the developer’s role to assess each suggestion and identify, for example, which one would optimize an existing workflow, and which one might not align with business constraints.
Moreover, developers must ensure that the agentic AI operations are rooted in data relevant to the company's goals, incorporating necessary safeguards tailored to specific applications.
And as AI agents take on more roles — from enhancing customer interactions to optimizing supply chains — the onus on developers to ensure these systems operate independently is unprecedented.
In the near future, we'll see AI agents "on demand," ready to augment human capabilities and create human-AI partnerships that combine the best of both human and machine intelligence. This isn't about AI replacing humans, but rather empowering humans to operate at a higher strategic and user experience level, focusing on creativity, critical judgment and complex problem-solving that machines cannot replicate.
Challenges in the Age of Agentic AI
While the potential for efficiency gains and innovative breakthroughs is immense, the true challenge lies in integrating these powerful, yet often isolated, AI functionalities into cohesive, business-wide solutions. With the right tools and platforms, AI systems can transform into powerful, integrated solutions. For example, an AI agent designed for financial forecasting, when integrated with enterprise systems managing procurement and inventory, can offer a more holistic view of the business — from financial health to supply chain dynamics.
Additionally, such an approach not only enhances operational efficiency but can break down silos within an organization. This allows AI to become a strategic driver in an organization’s growth, fostering an environment where tech and business objectives coincide.
With these things in mind, it’s essential for developers to be heavily involved in the orchestration process from the start, ensuring agentic AI systems complement each other and operate in concert, not just in parallel.
Related Article: AI Agents at Work: Inside Enterprise Deployments
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Bridging Gaps and Creating Synergies With AI Integration
As enterprises look to adopt agentic AI to boost the efficiency of their applications, they must also help developers connect disparate agents and agent frameworks.
Developers, now leaning on AI agent orchestrators, must design systems that communicate effectively, share insights and collaborate on decisions. These orchestrators act as the central nervous system, and will require sophisticated data architectures and APIs that allow for seamless data flow and interoperability among new and legacy systems.
Additionally, developers should focus on creating feedback loops where AI systems learn not only from their operations but also from each other, adapting and evolving to meet dynamic business needs.
The evolving role of developers highlights their increasing importance in strategic planning and execution and positions them as key players in helping businesses reap the full benefits of agentic AI. The stage is set for a transformative era in IT, and it's time for developers to embrace their new roles. Leaning into continuous learning opportunities, they can lead their organizations into a future shaped by the next phase of agentic AI.
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