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Agentic automation is widely promoted as the next major productivity breakthrough for enterprise IT. By combining automation with AI-driven decision-making, organizations expect faster, more flexible operations, reduced manual effort, and the ability to scale IT services without growing headcount.
It’s no secret that, due to a lack of long-term planning in their automation strategy, teams often struggle to scale agentic automation projects into sustainable ROI. However, in the early stages of experimentation, the promise of agentic automation is clearly apparent. Automation pilots deliver quick wins, teams experience how they can move faster with intuitive and hyper-fast agents at their fingertips, and initial productivity gains are easy to demonstrate.
The problems arise when teams attempt to scale pilots into production systems. As agentic automation expands its mandate and takes on real stakes, it starts to amplify pre-existing weaknesses across an organization’s automation environment. Productivity plateaus or even declines, and teams spend more time is spent troubleshooting than celebrating wins.
A key reason for this change of fortunes is tool sprawl. As operations scale, the very tools that helped unlock early automation value gradually turn into a source of friction that erodes ROI over time. This tendency for entropy should be clear to any IT leader who steps back and takes a macro view of their teams’ automation practices.
How the Early Stages of Agentic Automation Deliver ROI
Most automation initiatives begin pragmatically. Teams identify repetitive or time-consuming tasks and deploy tools that solve those problems quickly. In this phase, the priority is speed and impact, not long-term architectural consistency.
Agentic automation builds naturally on this foundation. AI agents are introduced to take over existing processes, evaluate conditions autonomously, and take automated action wherever required. Early use cases often show impressive results, such as faster incident response, streamlined provisioning, or reduced ticket volumes.
At this stage, the automation environment typically looks manageable:
- Automation is managed by a limited number of teams.
- Tools are selected based on clear, specific needs.
- Workflows are relatively easy to understand and maintain.
- Productivity gains are visible and easily measurable.
Each new tool or automation workflow seems like a boon when it’s applied with a clear purpose. Teams are keen to experiment further, and the cost of managing multiple tools and workflows seems negligible compared to the benefits they deliver.
When More Tools Start Reducing, Not Increasing, ROI
As automation proves its value, demand grows. Other teams want similar efficiencies. Automation is introduced to ever more parts of the operational system. New tools and workflows are introduced to address specific needs across different platforms, services, or line-of-business apps.
Over time, this leads to a fragmented automation landscape:
- Multiple tools are now performing overlapping functions.
- Scripts and workflows are duplicated across platforms.
- Different execution models, credential handling methods, and security controls are used across automations.
- Understanding of domain-specific automation logic is tightly coupled to individual teams or tools.
While each automation still could be said to save time in isolation, the collective overhead begins to pile up. Engineers must learn and maintain multiple tools to keep pace with their own automation processes. When updates are required, changes need to be replicated in several places, often without clear visibility into how this might affect the system at large. Troubleshooting requires jumping between systems to understand what ran, where, and why.
In many cases, the documentation is not there to make this ever-increasing complexity easy to navigate. The cost of coordination increases, while the ability to compound productivity across the organization diminishes. ROI stops growing because the effort required to operate and govern automation grows unsustainable.
Why Agentic Automation Amplifies Tool Sprawl Chaos
Agentic automation simply replicates human action, but at hyper-speed. What happens when an engineer makes a mistake? Processes break, but they are usually able to explain what they did, and the damage is limited. With an AI agent working at machine speed, that mistake is likely to get compounded 100 times over, and without unified monitoring tools, retracing the steps to find out what happened is nigh-on impossible.
AI agents rely on the same scripts, workflows, tools, and execution environments that humans use to perform real work. In a fragmented tool landscape, this creates serious challenges. Agents must navigate inconsistent interfaces, incompatible execution models, and uneven governance controls. Small discrepancies that were tolerable when humans ran automation become major problems when agents act autonomously and at machine speed.
Without the right guardrails and monitoring in place, agentic automation errors are often harder to identify and communicate than human ones. Rather than reducing workload, therefore, agentic automation increases the volume of activity that needs to be traced and corrected. Teams spend more time supervising automation, handling exceptions, and restoring trust in systems. Instead of acting as a force multiplier, agents amplify the chaos that was already present in a sprawl-heavy environment.
This is where many organizations realize that their automation problem is not a lack of technology, but a lack of consolidation, oversight, and planning.
Centralization as the Antidote to ROI Erosion
Sustainable automation ROI comes from reducing friction as automation scales.
The surefire way of achieving this is establishing a shared execution and orchestration platform that standardizes how automation is triggered, governed, and observed, regardless of where it runs.
That way, you provide a long-term foundation for:
- Workflows that behave consistently across environments.
- Automation assets that are reusable instead of duplicated.
- Security and access controls that are enforced uniformly.
- Simplified monitoring and troubleshooting that reveals both errors and optimization opportunities.
For agentic automation, this foundation is critical. When they’re given a stable, predictable automation environment, AI agents can be let loose to perform routine automation tasks with unprecedented levels of speed and flexibility.
With clear pathways for execution across tools and databases, and strict enforcement of access controls, centralization gives human engineers the clarity needed not only to monitor and optimize agentic automation activities, but also consequently to build a scalable automation infrastructure that compounds productivity gains across the organization.
For example, through a centralized execution and orchestration platform, teams can safely create and share compliant, access scoped automation workflows that can be tweaked and reused without requiring handover of credentials or excessively broad privileges. Agentic automation can be integrated into these workflows, or make use of these workflows itself to handle emerging, domain-specific requirements.
A change at the foundation level makes automation a compounding asset again, rather than a growing operational tax. Injected into this environment, agentic automation becomes a heavyweight productivity multiplier, rather than a chaos amplifier.
Achieving Agentic Automation ROI with ScriptRunner
ScriptRunner provides a centralized execution and orchestration layer for automation across Microsoft and hybrid environments, helping organizations move from fragmented tooling to a cohesive, well-governed automation strategy.
With ScriptRunner:
- Automation is created using standardized models, making workflows easier to maintain and reuse, with or without agentic automation involved.
- Execution is governed consistently, regardless of who or what triggers it.
- Self-service portals allow approved users or AI agents to initiate automation workflows safely without direct system access.
- Unified monitoring and logging provide a single, authoritative view of automation activity across environments.
By consolidating execution while preserving team autonomy, ScriptRunner directly reduces duplication, lowers maintenance effort, and restores control over all automation activity. Agentic automation can then focus on amplifying value rather than tripping over complexity.
Book a meeting with ScriptRunner to see how centralized automation can create sustainable ROI for agentic automation projects at production scale.