AI is a powerful tool, but without the right controls and governance, it can create as much pain as value, including in manufacturing environments. Enterprises are deploying AI agents to automate workflows, extract insights, and execute tasks in industrial settings in the name of efficiency. But without disciplined oversight, standalone initiatives can quickly introduce chaos, as unmanaged outputs and unchecked hallucinations begin to erode the value those agents are meant to deliver.

When enterprises lack the control layer to route, govern, or make AI-generated data useful at scale, interoperability and accuracy breaks down. “Confabulation” will compound without human interaction and applied supervision. The promise of Agentic AI was speed and scale, but without some kind of regulation layer, many organizations have instead introduced complexity and risk into their systems.

Taming Agent Sprawl

Uncontrolled proliferation is breeding “agent sprawl,” or a great multitude of AI agents deployed without centralized visibility, ownership, tracking, or governance. The result can be fragmented, flawed automation that duplicates computations, ignores context, or perpetuates falsehoods based on bad data. According to the Foundry Research AI Priorities Study, 97 percent of IT decision-makers report challenges when implementing new AI initiatives, including governance, maintenance, and security. Some estimates put the ROI erosion from unmanaged agent sprawl at up to 50 percent.

As multiagent deployments scale, coordination becomes non-negotiable. AI-native applications will fail without a control layer. Early in 2026, Gartner named this category Universal Orchestration (UO), deeming it a software layer that “focuses on coordinating execution runtimes across diverse systems” to address “the inability of existing execution platforms to coordinate AI agents, bots, APIs, and human tasks consistently at scale.” (Gartner ID G00841113, February 4, 2026, by Saikat Ray.)
The category formalizes what forward-looking enterprises were already building toward: A software-based control plane that resides above individual agents and enforces consistent behavior across all of them. Universal Orchestration platforms, like software solutions from market leader Axon Ivy, are purpose-built to address this issue.

Unpacking Universal Orchestration

IBM defines Agentic AI as “an artificial intelligence system that can accomplish a specific goal with limited supervision,” driven by ML models that simulate human decision-making. Universal Orchestration becomes necessary when the data volume of AI agents exceeds what any single team or platform can manage. Universal Orchestration operates multiple AI agents within a defined framework of governance, security, and escalation, while providing visibility into performance and outcomes.

Universal Orchestration applies policy, manages exceptions, routes data to the right downstream system, and keeps humans in the loop where decisions require it. The objective is not to produce greater output volume; AI itself takes care of that. UO enforces the production of verified, actionable output, where data is purposefully directed and meaningfully interpreted.

AI Makes Orchestration More Crucial, Not Less

Manufacturing, healthcare, finance, insurance, and telecommunications companies have been early adopters of Universal Orchestration. These industries run multiagent, multiplatform AI and IoT deployments at scale, where inconsistent policy enforcement can lead to not just performance issues, but outright compliance failures. Governance has therefore become requisite in these verticals.

Unregulated AI agents amplify the orchestration gap, deepening that disconnect between AI’s brilliant data generation and enterprise’s ability to successfully execute on that product. Models can classify damage, extract fields from documents, flag anomalies, and prioritize exceptions faster than any human team, creating genuine value—but AI can’t close the gap on its own. Enterprises should not confuse intelligent extraction with intelligent control, which can make or break the management and after-effects of these endeavors.

Universal Orchestration creates tangible benefits in the field. Audit teams need an evidence trail. Finance teams need to be confident that their ERP updates reflect informed decisions, not opaque automation. Thresholds need to be defined, routes approved, rules imposed, and rationales preserved. Human reviewers need their evidence provided in a meaningful context, not as an automation model score. This demands human-driven guidance, executed through software-based governance.

Asset Relationship Management: A Universal Orchestration Use Case

Many manufacturing enterprises still track their physical assets in a fixed asset register, audited annually. Assets move, get damaged, or are retired in between these audits, and a manual register is typically not updated to match. This creates what we call “ghost assets,” or physical resources that no longer exist—yet the company continues to depreciate, insure, and erroneously pay property taxes on these “ghost” articles. Kroll Advisory, which runs 8,000 fixed asset engagements a year, reports that 10 to 30 percent of the average fixed asset register is comprised of ghost assets.

Asset Relationship Management (ARM) software automates this process. It pulls real-time, continuous data from RFID, GPS, intelligent document management, and manual inspections to verify the existence, location, and condition of physical assets like machinery, equipment, and fleet assets.

Input sources like RFID and GPS generate independent signals that are transmitted to the ARM solution, continuously and in real time. When an overwhelming volume of signals arrives simultaneously, the orchestration layer routes, reconciles, and validates. The outcome is an up-to-the-minute, verified record of what assets exist, where each one is, and their respective conditions. The asset data can then be entered into a company’s enterprise resource planning (ERP) system, where it will help shape educated business decisions.

Universal Orchestration does not replace ERP systems or business process automation (BPA). Well-designed systems, like Axon Ivy’s Universal Orchestration platform, sit above these solutions, presiding over what AI agents do before their output is submitted to an ERP or BPA platform. Unaligned agents are a primary reason why AI-native deployments fail to deliver. Orchestration makes Agentic AI output useful, repeatable, and audit-ready.

Tim Harris is CEO and co-founder of SoloTruth, an evidence-based asset management platform that helps enterprises reconcile asset truth across systems. Harris is an inspection and asset management expert helping regulated and industrial enterprises replace asset guesswork with asset proof.