From Automation to Autonomy: How Agentic AI is Redefining Industrial Operations

Session Name:  From Automation to Autonomy: How Agentic AI Is Redefining Industrial Operations

Speaker:  Jürgen Schön, Head of Manufacturing GTM, EMEA, ServiceNow

Session Summary:  This session explores the critical transition from basic automation to true enterprise autonomy using agentic AI. It highlights how ServiceNow's overarching AI platform orchestrates tasks across hundreds of disconnected IT systems to seamlessly resolve complex business problems. By acting as a unified "front door," this technology streamlines end-to-end workflows across the manufacturing value chain while ensuring humans remain in control of final decisions.

The era of simple automation is rapidly making way for a new paradigm in industrial operations: true autonomy. At a recent industry event, Jürgen Schön, Head of Manufacturing GTM, EMEA for ServiceNow, detailed how "agentic AI" is set to become the next massive driver of productivity. These intelligent systems do more than just follow pre-programmed rules; they orchestrate complex workflows and make autonomous decisions to streamline the enterprise.

The "Technology Soup" and the Adoption Gap

Over the past three decades, industrial productivity has been boosted by several major technological waves, starting with Lean Management and ERP software in the 1990s, followed by robotics, and most recently, Industry 4.0. However, the current enterprise landscape has evolved into what Schön describes as a disorganized "technology soup".

Despite the buzz surrounding artificial intelligence, true end-to-end adoption remains strikingly low. According to recent research on the manufacturing sector:

• 64% of organizations use agentic AI in at least one siloed business function.

  
  

• Only 15% have successfully implemented AI workflows across their end-to-end enterprise.

  
  

• A mere 8% leverage agentic AI as a fully autonomous system capable of solving complete business problems independently.

The root of this problem lies in system sprawl. On average, an enterprise relies on 367 different IT systems, and individual employees regularly navigate between 10 to 11 disparate applications. Because each system features a different user interface and isolated data sets, it takes employees close to five hours to resolve cross-system business problems, often requiring lengthy email chains and phone calls to coordinate.

ServiceNow’s Architectural Solution: Sense, Decide, Act

To bridge this operational gap, ServiceNow has introduced an AI platform that functions as an overarching architectural layer on top of a company's existing IT infrastructure. Rather than migrating massive amounts of data, the platform utilizes "zero copy alignments" and relies on over 1,000 existing integrations to access information where it already lives.

Schön outlined the platform's capabilities through three foundational pillars:

• Sense: The system accesses data scattered across hundreds of existing systems and gives it meaningful business context within a workflow.

  
  

• Decide: Acting as an open ecosystem, the platform can embed preferred external AI models—such as those from IBM or OpenAI—to analyze the data and determine the best possible course of action.

  
  

• Act: The platform seamlessly executes the required automation and workflows based on those AI-driven decisions.

The Power of the AI Orchestrator

Achieving this autonomy does not mean sacrificing human control; rather, the AI can be configured to prompt human workers for approvals and guidance. This is executed through "AI Agents"—autonomous, highly specialized assistants that some customers have even personalized with human names like "John" or "Marcus".

To manage multiple agents running simultaneously, the system uses an "AI Orchestrator". This orchestrator ensures various agents work in harmony across IT, HR, Finance, Supply Chain, and Procurement to resolve issues smoothly.

For the average employee, this manifests as a "front door for your entire workforce". Instead of logging into multiple tools, an employee can simply type a natural language request, such as: "I need a noise-canceling headphone, Zoom Pro, and the office map for my headquarters. Can you help?". Similar to querying a search engine, the AI Orchestrator instantly deploys the necessary agents to find the map, generate hardware requests, route software approvals, and initiate backend workflows.

Implementation Strategy and the Future of SaaS

For enterprises looking to adopt this technology, Schön advises a targeted, step-by-step approach based strictly on immediate business urgency, whether that is starting on the factory production floor or within the Customer Relationship Management (CRM) environment.

Looking to the future, the integration of overarching AI layers raises questions about the long-term necessity of underlying software. While the immediate goal of the AI platform is to integrate data rather than rip out core systems like SAP, Salesforce, or Workday, a shift is inevitable. Schön noted that as employees increasingly rely on the unified AI interface, companies may eventually choose to decommission their legacy SaaS applications to significantly reduce costs.