February 2026 Volume 8

EQUIPMENT & TECHNOLOGY

(ChatGPT), Google (Gemini), Anthropic (Claude), and Microsoft (Copilot) can be purchased and installed inside a company firewall to secure and protect any proprietary knowledge and information that’s shared. When properly implemented, this type of AI assistance can reduce risk by consistently surfacing approved procedures, specifications, and vetted institutional knowledge. The Strategic Cost of Losing Control of Organizational Knowledge Forging is a knowledge-intensive industry. Decisions related to die wear, press behavior, and process sequencing reflect years of experience. When the appropriate subject matter experts are not accessible – or if they retire – the company stands to lose the context, judgment, and continuity of their decision-making rationale. AI assistants and AI-powered learning tools cannot replace expert judgment, but they can make that judgment accessible and reusable. The greatest cost of doing nothing is not measured in training hours, but in the gradual loss of control over how knowledge is shared and applied. For forging leaders, the question is no longer whether or not AI-powered learning tools have an important role to play in employee training and development. The choice is whether to proactively embrace AI tools to shape employee learning and knowledge sharing – or allow that decision to be made informally, one workaround at a time. Final Takeaways AI-powered learning does not replace experience – it harnesses the knowledge that’s already there. By providing a way to capture and share the valuable knowledge the company has built up over time, AI learning tools democratize access to expertise. When considering whether AI-powered learning tools are right for your organization, here are the key factors to remember: • Workforce learning has changed faster than traditional training systems. • AI-powered learning tools help operators build cause-and effect understanding without scrap or downtime. • When properly used, AI tools can reduce risk by keeping learning aligned with approved processes. • The greatest risk is not adopting AI but losing valuable knowledge that benefits the wider organization. In forging, knowledge has always been a competitive advantage. Using AI-powered learning tools helps companies leverage their knowledge as an asset, while ensuring that it remains controlled, accessible, and scalable, so that organizations can thrive and employees can excel. About THORS eLearning Solutions: THORS eLearning Solutions is a leading global provider of online technical courses and AI-powered productivity tools specifically designed for the manufacturing industry. Founded in 2010, THORS eLearning Solutions has been transforming manufacturing education through THORS Academy, a visually engaging and ever-expanding eLearning library of over 230 expert-developed courses. Covering topics from manufacturing fundamentals and materials to quality standards and emerging technologies, THORS Academy empowers professionals to increase their knowledge base to keep up with today’s fast-paced manufacturing

2. Visual Demonstration of the Forging Sequence Certain aspects of forging, such as internal metal flow and die cavity filling, are difficult to observe during production. AI-driven visual demonstrations address this gap by showing animated simulations of the forging sequence. Operators can replay steps, isolate stages, and explore “what if” scenarios. For example, seeing how insufficient billet temperature leads to underfill reinforces concepts that are difficult to convey through text alone. It’s like having instant, interactive video replays – directly in the flow of work. 3. AI-Based Defect Recognition Training Defect recognition is a skill typically built through experience. AI-based learning tools accelerate this process by presenting real images of forged parts and prompting learners to identify defects, probable causes, and corrective actions. This reinforces the connection between process variables and outcomes, strengthening diagnostic judgment on the shop floor. 4. Voice-Based AI Assistants Voice-based AI assistants allow operators to ask questions in plain language and receive concise explanations supported by images or short clips. This type of “hands-free” interaction is especially valuable in fast-paced environments – or for operators with limited English reading proficiency. By reducing reliance on manuals or informal guidance, these tools help standardize understanding without slowing production. 5. Skill-Level Adaptive Learning AI-powered learning tools can adjust content based on the learner’s experience level. New operators can focus on fundamentals, while more experienced personnel can explore more advanced skills such as process control, defect prevention, and die wear considerations. This allows a single system to support multiple roles, reducing the need for separate training tracks. The examples outlined above show how AI-powered learning tools can support learning at the individual skill level, making employees more efficient, confident and empowered. Moreover, giving employees easy access to accurate, approved knowledge not only improves overall efficiency, but also has direct consequences for consistency, safety, and risk across the operation. When Access to Knowledge Falls Behind, Risk Increases When access to accurate, approved information is inconsistent, variability follows. Operators rely on memory, coworkers, supervisors, outdated files, or whichever source is most readily available. When SOPs change, different teams or shifts may unknowingly work from obsolete/outdated versions of procedures or specifications. Over time, the impact of information gaps can compound – increasing rework, complicating audits, and introducing risk that is difficult to trace back to a single cause. As all-purpose AI tools like ChatGPT, Claude, Gemini and others become common outside the workplace, another risk emerges. Employees may turn to these tools for explanations – without knowing whether the information they provide aligns with company-specific standards or safety requirements. The issue is not the AI tools themselves, but the lack of control over how knowledge is accessed and applied to company-specific challenges. Commercially available AI tools from companies like OpenAI

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