XMPro Named as a Sample Vendor in Gartner® Report: Customer Trust Is a Critical Barrier to Agentic AI Adoption

Leading Industrial AI Platform Recognized for Reliability Tools that Build Trust in Agentic AI Systems

DALLAS, TX, UNITED STATES, June 8, 2025 /EINPresswire.com/ -- XMPro, a leading provider of industrial AI and intelligent business operations solutions for asset-intensive industries, today announced it has been recognized as a Sample Vendor in the Gartner^® report, "Emerging Tech: Customer Trust Is a Critical Barrier to Agentic AI Adoption" published on June 2, 2025.*

XMPro was recognized as a Sample Vendor. According to the report, "Gartner research reveals that a top inhibitor to agentic AI adoption is a lack of customer trust. Vendors that offer observability tools, reliability controls and explainability features will emerge as near-term winners in the agentic AI market."

According to the report: "Many interviewed providers did not use GenAI for task execution; rather, they used classical AI technologies, such as ML models and rule-based logic. For example, using LM for reasoning but ML for task execution. This hybrid approach to agentic AI embeds transparency and reliability into task automation."

"We believe, our inclusion in this Gartner report validates our focus on building trusted industrial AI solutions that deliver real operational value," said Pieter van Schalkwyk, CEO of XMPro. "Our hybrid approach to agentic AI, combining advanced language models with proven industrial AI techniques, directly addresses the trust challenges that organizations face when deploying autonomous systems in critical industrial environments."

Industry Context: The Trust Challenge in Agentic AI

The Gartner report reveals critical insights about agentic AI adoption:
• “The study interviewed 20 agentic AI providers, of which a majority (more than 50%) cited customer trust as a top challenge to driving customer adoption.”
• “By 2028, less than 10% of agentic AI deployments will operate unsupervised, up from less than 1% in 2025”
• “the market is currently favoring semisupervised, simple task automation over more autonomous, complex agentic task automation.”

XMPro's Approach to Trusted Industrial Agentic AI Through Composite AI:

XMPro's intelligent business operations solution (iBOS) addresses the trust challenges identified in the Gartner report through its unique Composite AI framework that combines six complementary AI methodologies:

•Truth-Grounded Architecture: Every AI recommendation passes through multiple validation layers including first-principles validation, symbolic rule enforcement, evidentiary reasoning, and multi-agent cross-checks, ensuring decisions are safe, explainable, and trusted

•Hybrid AI Integration: Combines Generative AI for insight synthesis with Symbolic AI for rules-based intelligence, First Principles Models for physics-based validation, and Causal AI for root-cause discovery, addressing the report's emphasis on combining language models with classical AI

•Agentic AI with Bounded Autonomy: Orchestrates coordinated teams of specialized AI agents that observe, reason, plan, and act, with configurable human oversight and flexible autonomy controls based on operational risk tolerance

•Real-Time Industrial Observability: Built-in monitoring, tracing, and alerting mechanisms designed specifically for mission-critical industrial environments where equipment failure or safety incidents have major consequences

•Domain-Specific Industrial Intelligence: Pre-configured for aerospace & defense, manufacturing, mining, oil & gas, utilities, and other asset-intensive industries, translating domain expertise into formal logic structures with clear, auditable reasoning chains

•Multi-Agent Collaboration with Guardrails: Supports collaborative multi-agent teams that work together on complex industrial problems while enforcing safety protocols and operational constraints

Organizations can learn more about XMPro's industrial agentic AI solutions at www.xmpro.com.

*Source: Gartner, "Emerging Tech: Customer Trust Is a Critical Barrier to Agentic AI Adoption," Danielle Casey, Alfredo Ramirez IV, Anushree Verma, Akhil Singh, Aakanksha Bansal, 2 June 2025

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About XMPro
XMPro is a leading industrial AI company that helps enterprises achieve measurable business outcomes through intelligent operations. The company's Multi-Agent Generative Systems (MAGS) platform combines industrial digital twins with trusted agentic AI to optimize operations, improve asset performance, and enhance decision-making in complex industrial environments. XMPro serves Global 2000 companies in manufacturing, mining, energy, utilities, and other asset-intensive industries, helping them navigate their industrial AI transformation journey with confidence.

Wouter Beneke
XMPro
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