IT departments face immense pressure. The answer to their challenges involves a fundamental reevaluation of who develops solutions, who handles automation, and the very mechanics of task execution.
A clear strain exists within contemporary IT. Teams are overwhelmed by a rising tide of projects, simultaneously tasked by leadership to spearhead the organization’s evolution into an AI-powered entity.
Statistics reveal a challenging scenario: IT departments are swamped. Digital transformation efforts have intensified rather than abated. Remarkably, IT project requests in 2025 surged by 18% over the previous year, and almost a third of all IT projects (29%) failed to meet their deadlines, leading to friction with business stakeholders.
However, a seldom-voiced truth among IT leaders is this: the solution isn’t simply more overtime. Instead, it involves empowering existing teams with the tools already available to them. When workloads exceed conventional capabilities, the focus must shift to boosting staff productivity and addressing overdue tasks.
Therefore, as the disparity between demands and achievable outcomes grows, the imperative becomes clear: redefine roles in creation and automation, and fundamentally redesign workflows.
Addressing the skills shortage means leveraging your current workforce’s potential—a transformation currently underway through the concept of ‘vibe coding’.
The Emergence of Vibe Coding
The premise is straightforward: a subject matter expert articulates their requirements using everyday language, and an AI agent (or multiple agents) then handles the entire process—from planning and reasoning to complete execution. This marks a pivotal moment where experts, whether in IT or other fields, can finally construct the systems they’ve long envisioned.
Henceforth, domain specialists are freed from needing to master intricate coding languages to translate their concepts into functional workflows, processes, or service stages. They gain the ability to create systems perfectly aligned with their expertise. IT service organizations quick to adopt this approach will gain an unparalleled competitive edge in user experience.
Imagine needing an onboarding process complete with provisioning, equipment allocation, training, and approvals. Just articulate it. The AI agent will then chart the flow, discern interdependencies, integrate necessary actions, and construct the full workflow. For quicker incident assessment, simply provide the AI agent with the parameters. It will analyze employee communications, glean context, identify trends, link relevant incidents, and automatically initiate subsequent actions.
Anticipating the thought, ‘Here comes another tech leader suggesting AI will eliminate jobs,’ I want to clarify: developers remain essential. Their role evolves from constant, repetitive maintenance to concentrating on critical areas such as architectural planning, system design, and addressing complex challenges—tasks that inherently demand human ingenuity and drive innovation.
IT Service: A Pre- and Post-Agentic AI Perspective
Those familiar with conventional IT service environments will recognize the inherent challenges: inflexible forms, constrained workflows, reliance on specialized personnel, tedious manual transfers, and constant context shifting. These issues are commonplace.
Agentic AI revolutionizes the service lifecycle from the very first interaction. When an employee initiates contact, perhaps via Slack or a web portal, the AI agent instantly interprets their intent, gathers essential information, cross-references for related problems, and pre-populates fields typically managed by humans. This eliminates the need for portals, tedious forms, or repetitive exchanges just to grasp the situation.
As a case progresses, the agent assesses whether it qualifies as an incident. It scrutinizes the relevant configuration items, identifies analogous open issues, and can even suggest potential root causes. All this data is sourced from a dynamic configuration management database (CMDB) that provides real-time mapping of systems and assets, equipping IT analysts with context they would otherwise struggle to compile.
Even escalations transform. The AI agent furnishes the human specialist with a comprehensive, actionable summary of the situation. Technical support engineers can then concentrate on resolution instead of information retrieval. Furthermore, teams can collaborate on incidents within platforms like Slack, with direct links to all pertinent records.
Collectively, these advancements yield immediate, tangible benefits: quicker responses and reduced mean time to repair (MTTR). The most compelling aspect? These gains are achieved by maximizing the potential of your current workforce.
Redefining the Builders
The most revolutionary aspect of vibe coding is its democratizing effect on access. Individuals with deep operational knowledge—ranging from IT service professionals to HR associates and operations managers—can now actively participate in solution development. Essentially, anyone capable of describing a required outcome can delegate its execution to AI agents.
This approach enables organizations to regain lost capacity. Indeed, 67% of organizations acknowledge AI’s transformative impact on technical roles, necessitating upskilling for their current staff. Developers gain bandwidth to concentrate on foundational infrastructure and innovation. Business units acquire the agility to create and refine solutions in real time. For leaders, this translates into a more flexible and robust operating model, one that withstands shifts in the talent market.
The Imperfections of Innovation
It’s important to acknowledge that vibe coding, while potent, isn’t a cure-all. It represents a significant initial step, yet it shouldn’t be mistaken for a complete solution.
As industry experts such as Vernon Keenan have observed, a large language model (LLM) functions much like a power generator, supplying raw computational energy. However, for effective enterprise deployment, it demands a strong orchestration framework and a deep understanding of the organizational context. Lacking precise control mechanisms, comprehensive monitoring, and business-specific insights, natural language inputs can still result in ‘hallucinations,’ potentially increasing manual corrective work for teams.
The crucial strategy involves a ‘vibe-and-verify’ approach, where AI manages the complex creative tasks, while human oversight ensures necessary governance. It’s imperative that your orchestration platform incorporates a trust layer and provides auditable execution logs, guaranteeing that all agentic workflows adhere strictly to authentic business logic.
The Pressing Question for Today’s Leaders
Shall we merely await its widespread adoption, or leverage the current talent crunch as an opportunity to proactively re-envision work processes?
Enterprises that embrace this shift promptly will significantly alleviate operational inefficiencies, elevate employee satisfaction, safeguard their teams against burnout, and cultivate an environment where subject matter experts function as innovators rather than mere requestors.
This transformation is already in motion. Organizations that actively engage with it will be the first to realize its profound impact.
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