XMPro Named as a Sample Vendor in Two Categories of the Gartner® Hype Cycle™ for AI in ITSM, 2026
In our view, inclusion in Agent Orchestration and Agentic AI reflects how XMPro's Agentic Operations Platform was designed from the start: APEX as the orchestration control plane and MAGS as the agentic AI framework, working together for industrial enterprises.
DALLAS, TEXAS — June 17, 2026 — XMPro, the agentic operations platform for asset-intensive and mission-critical industries, today announced it has been named as a Sample Vendor in two categories of the 2026 Gartner Hype Cycle for AI in ITSM, published 2 June 2026: Agent Orchestration and Agentic AI.
"In our opinion, recognition in both Agent Orchestration and Agentic AI in the same Hype Cycle reflects how industrial operations teams now think about AI agents: the agent and the orchestration layer that governs it are inseparable. XMPro built APEX as the orchestration control plane and MAGS as the multi-agent framework on the same platform, with the Operational Identity Model grounding every reasoning step in real industrial context."
Pieter van Schalkwyk — CEO, XMPro
According to Gartner, Agent Orchestration carries a “High” benefit rating with less than 1% of target audience market penetration and “Emerging” maturity. Agentic AI carries a “Transformational” benefit rating with 5% to 20% market penetration and “Emerging” maturity. (1)
On Agent Orchestration, Gartner states: “Agentic orchestration represents the rise of a new control plane from record keeping to delivering business outcomes. It enables transparent economics of AI agents — tracking automation mix, SLA attainment, and cost per decision — and aligning monetization to proven outcomes. Furthermore, it can bridge gaps between disparate systems, such as ERP, CRM, HCM and more, allowing agents to access, analyze, and act on data across the enterprise securely and work on complex tasks at scale.” (1)
Gartner also states: “Without orchestration, AI agents will sprawl across the enterprise and become chaotic and unmanageable, limiting business impact.” (1)
On Agentic AI, Gartner states: “Agentic AI is an approach to building AI solutions that uses one or multiple software entities classified wholly or partly as AI agents. AI agents are autonomous or semiautonomous software entities that apply AI techniques to perceive, decide, act and pursue goals across digital or physical environments.” (1)
On the value agentic AI creates, Gartner states: “Agentic AI creates this value through goal-driven systems that offer more flexibility, adaptability and higher levels of automation and, more importantly, augmentation — further bridging the gap between humans and machines.” (1)
“We believe industrial enterprises cannot adopt agentic AI by deploying agents in isolation,” said Pieter van Schalkwyk, CEO of XMPro. “An agent without an orchestration control plane is an unmanaged risk. An orchestration layer without composable, governed agents has nothing to orchestrate. XMPro built both layers together. APEX handles agent lifecycle, governance, audit, and the supervisory Control Tower. MAGS provides the multi-agent collaboration framework. StreamDesigner integrates with SCADA, PLCs, historians, and ERP systems. The Operational Identity Model anchors every agent in real industrial context. That integrated architecture is what lets industrial operations scale from pilots to autonomous operations.”
How we think XMPro's Agentic Operations Platform Aligns to Both Categories
The XMPro Agentic Operations (AO) Platform combines industrial intelligence infrastructure with the Multi-Agent Generative Systems (MAGS) framework on top of a composite AI core, with APEX as the orchestration control plane.
Agent Orchestration: APEX Control Tower. APEX provides centralized lifecycle management, governance controls, and supervisory monitoring across agent teams. Every agent has an identity, a policy boundary, an audit trail, and an objective function before it runs. The Control Tower exposes the economics of agent operations: automation mix, SLA attainment, escalation rates, and cost per decision.
Agentic AI: Multi-Agent Generative Systems (MAGS). Specialized AI agents coordinate under bounded autonomy, sharing insights, reaching consensus on recommendations, and escalating to human operators when confidence thresholds are not met. MAGS provides the multi-agent collaboration pattern for industrial workflows.
Composite AI architecture. XMPro combines generative AI for reasoning with symbolic AI, first-principles models, and causal AI for task execution. Agent decisions are grounded in physics, process logic, and causal models, not in language-model heuristics alone.
Industrial integration (StreamDesigner). XMPro connects directly to SCADA, PLCs, historians, and ERP systems via StreamDesigner, building governed intelligence pipelines that process live sensor streams and operational data.
Domain specialization through the Operational Identity Model (OIM). XMPro MAGS agents are configured against the OIM, which encodes institutional process knowledge, equipment relationships, and operational constraints. Agents reason against this domain context rather than against generic enterprise data.
Bounded autonomy and policy enforcement. Deontic policy rules define what agents can and cannot do, with role-based permissions, consensus mechanisms for critical decisions, and comprehensive audit trails for compliance in regulated industrial environments.
XMPro's APEX platform and Multi-Agent Generative Systems (MAGS) framework are available immediately for industrial enterprises seeking to deploy orchestrated, multi-agent systems with bounded autonomy in mission-critical environments. For more information, visit www.xmpro.com.
(1) Source: Gartner, Hype Cycle for AI in ITSM, 2026, Chris Matchett, Chris Laske, Siddharth Shetty, 2 June 2026.
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About XMPro
XMPro is the agentic operations platform that takes industrial enterprises from monitoring to autonomous operations, on one platform, at their own pace, without changing tooling. The XMPro AO Platform combines industrial intelligence infrastructure with Multi-Agent Generative Systems (MAGS) to give AI agents the operational context, institutional knowledge, and governed execution surface they need to run industrial operations autonomously. XMPro serves Fortune 500 companies across manufacturing, mining, energy, utilities, and other asset-intensive sectors. Headquartered in Dallas, Texas, XMPro has been solving complex challenges for global industrial companies since 2009.
Media Contact:
Wouter Beneke — Marketing Lead XMPro Email: wouter.beneke@xmpro.com Web: www.xmpro.com