A recent survey by the ARC Advisory Group highlights that industrial leaders believe artificial intelligence (AI) will be the most impactful technology for operations over the next five years. At the ARC Forum in February, discussions emphasized the need for well-organized data to maximize AI’s effectiveness in industries. Keynote speaker Nico Duursema shared insights on building a “born-digital” facility that focuses on data-centric AI solutions. Generative AI also emerged as a vital tool for training new workers and preserving knowledge as experienced employees retire. Companies like Celanese and Schneider Electric are pioneering AI applications in process safety and user interfaces, demonstrating AI’s potential in enhancing operational efficiency and safety in industrial settings.
March 1, 2025 | By Scott Jenkins, senior editor
In a recent survey by the ARC Advisory Group, industrial leaders have identified artificial intelligence (AI) as the most impactful digital technology for the next five years. This was a key topic at the ARC Forum held in February in Orlando, Florida, where experts discussed how AI tools can improve industrial operations.
The consensus among industry leaders is clear: effective AI applications rely on structured and contextualized data. Nico Duursema, CEO of Cerilon, highlighted this during his keynote speech. His company is developing a state-of-the-art gas-to-liquids facility in North Dakota, designed to be “born-digital.” This plant will utilize machine-learning AI and emphasize “data centrality,” demonstrating how data can empower AI solutions.
Another important point raised at the forum was the need for specific AI tools tailored to different industrial skills and use cases. For example, Causal AI focuses on understanding cause-and-effect relationships and can enhance predictive capabilities. Meanwhile, Agentic AI involves multiple specialized AI agents collaborating toward a common goal by using different data types and techniques.
Generative AI also made headlines at the event. Celanese Corp. showcased how it is using AI-powered natural language models (NLMs) as user interfaces for plant staff. Ibrahim Al-Syed, a digital manager at Celanese, emphasized the importance of human-centered design in AI developments within their manufacturing facilities.
One of the key motivations for adopting AI is addressing workforce challenges in the chemical process industries. As experienced workers retire and take valuable knowledge with them, generative AI systems can help capture and organize this information for newer employees. Chris Stogner from Schneider Electric noted that AI could introduce objectivity into process safety analyses, reducing human biases in evaluating hazards. Schneider is actively seeking industry partners to innovate in this area, working on AI agents that can identify and mitigate potential dangers.
The ARC Forum highlighted the promising future of AI in industrial operations, creating opportunities to enhance safety and efficiency across the sector. For more insights from the forum, visit the ChemEng Online article.
Tags: Artificial Intelligence, Industrial Operations, AI Tools, Workforce Challenges, Generative AI, Process Safety, ARC Forum 2025
What is the role of AI in process operations within chemical engineering?
AI helps to improve efficiency, safety, and decision-making in chemical processes. It analyzes data to optimize operations, predict equipment failures, and enhance product quality.
How does AI improve safety in chemical plants?
AI enhances safety by monitoring processes in real-time. It can detect anomalies and alert operators to potential hazards, helping to prevent accidents and ensure a safer work environment.
Can AI reduce costs in chemical manufacturing?
Yes, AI can lower costs by optimizing resource use and reducing waste. By predicting equipment maintenance needs, AI minimizes downtime and lowers operational expenses.
Is AI easy to integrate into existing chemical processes?
AI can be integrated into current systems, but it may require some adjustments. Companies often collaborate with tech experts to customize AI solutions that fit their specific needs.
What are the future trends of AI in chemical engineering?
Future trends include greater automation, improved data analytics, and more advanced AI models. These advancements will likely lead to smarter and more sustainable chemical manufacturing processes.