How to Enhance Human Expertise in Manufacturing with Agentic AI?

[Erkan Teskancan]

## How to Empower Human Expertise on the Production Floor with Agentic AI

Agentic artificial intelligence (AI) is creating a powerful collaboration on the factory floor by combining human expertise with machine proactivity in the manufacturing sector. This technology enhances production processes with autonomous digital assistants that can perceive and analyze their environment and take action with minimal human intervention.

The success of Agentic AI is built on using the expertise of workers through a Human-in-the-Loop model to build trust and to balance human judgment with machine initiative in the factory environment. Over the past two years, AI, especially generative AI applications powered by large language models, has begun to enter the production line.

### What is Agentic AI?

• AI agents functioning as autonomous software systems,
• Performing environmental perception, motion planning, and tool use with minimal human intervention,
• Capable of learning and adapting over time.

### The Power of Agentic AI in Manufacturing

• Strengthens real-time decision-making and human-machine collaboration,
• Offers an opportunity to overcome the productivity stagnation experienced in markets like Germany and America,
• Allows workers to focus on more value-added tasks by freeing up their time from repetitive duties.

### Importance of the Human-in-the-Loop Model

• Requires user approval to prevent AI agents from machines running out of control,
• Enables workers to interact with AI to improve agent performance,
• This approach enhances trust and performance.

### Future Stages

• Stage 1: Assistants and automation – Content support and background tasks,
• Stage 2: Goal-oriented autonomy – Tool and sub-agent coordination in troubleshooting,
• Stage 3: Proactive and predictive systems – Detecting breakdowns and inefficiencies in advance and offering recommendations.

### Use Cases of Agentic AI in Manufacturing
1. Troubleshooting: The orchestrator agent interprets the operator's request, provides correct solutions, and creates a record with user approval.
2. Early warnings: The agent proactively detects recurring issues in forklift safety checks and notifies the supervisor.
3. Shift performance prediction: Analyzes performance risk with current data and recommends necessary measures.

### Building Trust Between AI and Humans

• Trust in AI in manufacturing is high and supported by 78-84% in strategic decisions and operational innovation,
• However, issues such as the balance between human oversight and efficiency, and cultural and trust barriers, are still awaiting answers.

The true power of Agentic AI lies in establishing an effective partnership on the factory floor by combining human expertise with machine proactivity. In the future, manufacturing efficiency will be shaped not by replacing people, but by empowering them with intelligent and proactive partners.