Beyond Chatbots: GenAI Now Negotiates Deals and Runs Mines

BOSTON, MA – November 24, 2025 – While public fascination with Generative AI remains fixed on eloquent chatbots and surreal image generators, a far more consequential transformation is quietly taking place within the bedrock of the global economy. A new publication from a key technology standards consortium reveals that the next wave of AI is moving out of the data center and into the factory, the mine shaft, and the corporate boardroom, poised to automate not just text, but critical industrial operations and high-stakes business decisions.

The Object Management Group (OMG), a historically influential body in software architecture, today released the 28th edition of its Journal of Innovation, focusing squarely on the deployment of Generative AI in industrial settings. The collection of papers, authored by member companies at the forefront of this shift, paints a picture of an AI that is less a creative partner and more a tireless, autonomous operational manager.

“As industries worldwide embrace AI-driven transformation, we invited research and case studies highlighting the real-world impact of GenAI on operational strategies, workforce adaptation, and industry-specific challenges,” said Edy Liongosari, Chief Research Scientist at Accenture and Co-chair of OMG’s Thought Leadership Group, in the announcement. The journal, he noted, offers "actionable insights and thought leadership" on this evolution.

The Architects of a New Industrial Order

To understand the weight of this publication, one must first understand its source. The Object Management Group is no mere industry think tank. Founded in 1989, it is the consortium behind foundational software standards like the Unified Modeling Language (UML) and the Common Object Request Broker Architecture (CORBA)—technologies that have defined how complex software systems are designed and interact for decades. Its standards are deeply embedded in sectors from finance to defense.

This history makes OMG’s focus on industrial AI a significant market signal. The group is not just observing a trend; it is positioning itself to write the rules that will govern it. This strategic intent was underscored by a recent major development: on October 1, 2025, the EDM Association, a global body focused on data management best practices, completed its acquisition of OMG. The merger created what the organizations call the "world's largest data and standards community," explicitly aiming to forge a trusted path from data strategy to production-grade systems. By publishing this journal, the newly empowered OMG is laying the intellectual groundwork for future standards that will ensure safety, reliability, and interoperability as AI takes control of critical infrastructure.

From Boardrooms to Mine Shafts: AI Gets to Work

The journal’s articles move the conversation about Generative AI far beyond content creation, detailing its application in complex, high-value industrial tasks.

One standout paper from Japanese tech giant NEC Corporation explores the use of GenAI for automated negotiation. While automated systems for bidding and procurement are not new, they have traditionally been rigid. NEC’s research details how large language models (LLMs) can create far more dynamic and context-aware negotiation agents, capable of understanding complex preferences and adapting to changing market conditions in real-time. This isn't about generating a polite email; it's about deploying an AI to autonomously secure better terms in a supply chain contract, a direct and measurable impact on the bottom line.

Taking the concept of autonomy even further, software firm XMPro Inc. details its work on "Cognitive Agent Frameworks" for industrial decision-making. Drawing on anonymized case studies from manufacturing, energy, and mining, the company showcases how teams of specialized AI agents can manage and optimize physical operations. XMPro’s approach, which it calls a "Composite AI" system, combines the flexibility of generative models with the reliability of older AI methods like rules-based systems and physics-based models. This hybrid design is crucial for mission-critical environments where a "hallucination" is not a quirky error but a potential industrial accident. Their paper describes a "Control Loop Optimization Team" of AI agents in a manufacturing setting that delivered significant business value while maintaining stringent safety and efficiency standards.

The scope of this industrial AI extends to planetary scale. An article co-authored by LunateAI, a specialized advisory firm with roots in NASA and the Open Geospatial Consortium, explores how GenAI is reshaping the analysis of geospatial data. The technology is being used to transform massive streams of data from Earth Observation satellites and IoT sensors into actionable intelligence for everything from climate resilience and disaster response to national security. In this context, GenAI acts as a powerful analytical engine, identifying patterns and making predictions at a speed and scale no human team could match.

The Quiet Race to Standardize Intelligence

These applications, while impressive, also highlight an urgent need for governance. When AI is negotiating multi-million-dollar deals or managing the controls of a power plant, ad-hoc development is not an option. Interoperability, security, and predictability become paramount. This is the strategic core of OMG's initiative.

The journal is a public-facing component of a deeper strategy. In late 2024, OMG formed an Artificial Intelligence Joint Working Group to specifically advance AI integration with digital twins and other industrial technologies. The goal is standardization. By fostering a consensus on best practices and architectural patterns, OMG aims to provide the industry with a stable, reliable foundation—the "plumbing," as some engineers call it—upon which companies can build their own specific AI solutions without having to reinvent the wheel. This effort is a race to bring order to the chaotic, rapid-fire innovation of the AI world before it becomes irrevocably fragmented and potentially unsafe in critical industrial contexts.

A Counterpoint: The Wisdom Stored in Feelings

Yet, even as the march toward automation accelerates, a fascinating counter-narrative is emerging from within the engineering community itself. One of the journal's most thought-provoking papers, from a consortium including STEM-TEC LTD and Resurface Behavioural Health, argues for a more human-centric approach. Titled "Beyond AI Agents: Creating the Conditions for Breakthrough Intelligence," the article posits that the greatest leaps forward will come not from replacing human faculties, but from designing AI that respects and collaborates with them.

The authors explore designing processes that tap into "the wisdom stored in feelings, not just files." This is a radical departure from the data-centric view that dominates AI development. It suggests that human intuition, experience, and even emotional response are valuable forms of data that current AI models are ill-equipped to handle. The future of intelligence, this paper argues, may not be a purely artificial one, but a composite intelligence where human insight guides and validates the powerful but brittle logic of machines.

This perspective serves as a crucial reminder that efficiency and resilience—the journal’s stated themes—are not solely technical problems. As AI agents become embedded in our industries, the ultimate challenge will be integrating their computational power with the irreplaceable wisdom of human experience. The work detailed by OMG's members shows this integration is no longer a future concept; it is the present reality being engineered today.