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Agentic automation will transform how businesses operate, taking a large portion of routine work out of human hands. However, the path to operationalizing it at enterprise-grade quality can be a challenging one for many companies.
Teams working to deploy AI agents quickly encounter familiar obstacles: automations that behave inconsistently, pass controlled tests but fail under real operational conditions, or produce different results depending on who built them and where. Even with highly skilled teams, achieving stable, predictable output that aligns with business objectives is notoriously difficult.
This is precisely why so many organizations struggle to reach ROI from their AI pilots. Agentic automation remains loosely bolted onto existing systems, with minimal integration into core processes, and no clear way to scale beyond isolated experiments.
Beneath almost every example of stalled agentic automation deployment lies the same root cause: fragmentation.
How Fragmentation Bottlenecks Automation ROI
Fragmentation between teams doesn’t just slow the development of end-to-end automations; it actively degrades output quality. When teams build automations independently, each introduces its own assumptions, security practices, and process definitions. Over time, this results in a patchwork of disconnected workflows and AI agents that can’t be reliably stitched together into complete, enterprise-grade processes.
Under these conditions, it’s no wonder that 95% of AI pilots fail to deliver measurable business impact.
The underlying causes are remarkably consistent across organizations struggling to operationalize agentic automation:
1. Misaligned Workflows Across Teams
One team automates their portion of a business process. When that process crosses into another department, the next team builds their own automation using entirely different logic. The outcome isn’t true end-to-end automation; it’s a chain of partial workflows that require manual intervention at every handoff.
2. Inconsistent Development Standards
Without shared script libraries or governance standards, automations vary widely in structure, quality, and reliability. Teams repeatedly reinvent the wheel, duplicating work and producing brittle workflows that fail under real-world conditions. With no shared knowledge base, learnings aren’t transferred and quality never compounds.
3. Privilege Creep and Lack of Guardrails
To speed up experimentation, developers often give agents full admin rights or unrestricted access. Over time, these temporary privileges harden into production workflows with dangerously broad permissions. This exposes sensitive systems to breaches and allows automations to pull incorrect data, producing faulty outputs.
4. Regulatory Compliance Roadblocks
Even when fragmented automations technically function, the absence of unified logging, access control, and security policies means they would never pass audits under emerging AI regulations. As a result, scaling becomes impossible without introducing unacceptable regulatory and security risk.
Fragmentation, therefore, doesn’t just slow development of AI-driven automations; it dooms them from the start. When unified governance standards aren’t in place, even successful automations struggle to graduate from prototypes to established parts of core business processes. IT teams end up firefighting issues, correcting poor-quality outputs, and mitigating compliance issues instead of focusing on innovation, optimization, and strategic value creation.
How Good Governance Restores Quality, With Real-World Examples
Surveys of high-performing organizations that have successfully operationalized agentic automation reveal a clear pattern: they take a unified, company-wide approach.
When teams are given room to customize and deploy automation within a centralized framework, anchored by shared standards, governance, and policy, innovation accelerates without compromising quality, security, or reliability.
The examples below show an important truth: the difference between inconsistent, low-value automation and enterprise-grade agentic automation isn’t the sophistication of the technology itself; it’s the governance supporting it.
1. Eliminating Fragmentation Before It Undermines the Business
In many large enterprises, automation begins as a collection of isolated scripts: quick fixes written by whoever has the access and time. Over months and years this creates duplication, inconsistent quality, and hidden automation that exposes the organization to operational and security risks.
Bechtle, one of Europe’s largest IT service providers, solved this challenge by centralizing its Microsoft automation strategy with ScriptRunner. By introducing shared script libraries accessible to service-desk teams across the company, Bechtle ensured that every team could rely on high-quality, policy-validated workflows without requiring elevated rights or custom-built scripts. Within six months, Bechtle deployed a unified automation framework across the business, reducing repetitive workload in 2nd- and 3rd-level support by 30%.
2. Enabling Real End-to-End Automation
The productivity gains promised by agentic automation don’t come from automating single tasks, but from connecting them into seamless, cross-functional workflows that mirror real business processes.
Brose Group, a global automotive supplier operating across 24 countries, achieved this by using ScriptRunner as its centralized automation platform. IT created a shared PowerShell library of dynamic, pre-approved templates that regional teams could use for recurring administrative tasks like provisioning, patch management, and data validation, all without needing admin rights.
This shift from ad-hoc scripting to centralized automation saved the organization 4,000+ working hours per year, while ensuring global consistency in security, compliance, and execution quality. Most importantly, it enabled Brose to unify automations across engineering, IT, and operations into cohesive end-to-end workflows.
3. Strengthening Oversight, Security, and Continuous Improvement
Effective governance isn’t about locking systems down; it’s about creating the visibility, accountability, and performance insights required for ongoing improvement.
Rhenus Logistics, a global logistics provider with over 39,000 employees, used ScriptRunner to bring structure and oversight to hundreds of scripts and workflows across its Microsoft ecosystem. ScriptRunner became both the execution engine and the control layer, ensuring that every action, whether executed by an admin or a delegated end user, was logged, monitored, and fully traceable across their global infrastructure.
This level of observability not only supported strict compliance requirements like SOX and NIST, but also dramatically reduced onboarding time for new locations and empowered the organization to refine automations based on explicit performance and quality metrics.
These examples make one point clear: automation only performs as well as its governance allows. When companies centralize control, standardize execution, and enforce comprehensive oversight, automation runs not just faster, but smarter. It evolves from scattered scripts into a coordinated, auditable, continuously improving system that consistently delivers high-quality output.
This is the same foundation that agentic automation relies on to run end-to-end workflows that deliver a high level of business impact: predictable, coordinated, optimizable, and policy-aligned from start to finish. With the right centralized approach, teams can build and deploy agentic automations quickly, consistently, and collaboratively, protected by the guardrails needed to prevent misconfigurations, security risks, and compliance failures.
How ScriptRunner Enables Enterprise-Grade Automation Quality
ScriptRunner provides the governance, structure, and execution layer required to unify automation across the Microsoft ecosystem under a high-performance framework.
With ScriptRunner, organizations gain:
- Centralized automation execution, with one platform for all scripts, workflows, and AI-driven actions.
- Standardized script libraries, where pre-approved and version-controlled automations are ready for self-service use across the business.
- Robust governance controls, with built-in enforcement of access controls and human-in-the-loop approvals.
- Complete visibility and logging, so that every workflow is traceable, auditable, and validated for contribution to business objectives.
If you want to remove your automation ROI bottlenecks and turn agentic automation into an enterprise-grade productivity engine for the Microsoft ecosystem, book a meeting.