Developing a Strategic Approach to Production-Enhancing AI

artificial intelligence (AI) to substantially transform their businesses. The initial applications of generative AI (genAI) in industry are focused on increasing bottom line efficiency and productivity, cutting costs and improving product quality.

While these results sound promising, organizations must understand that building effective genAI frameworks and models requires a foundation of reliable data on which to base actionable suggestions, and there are no silver bullet solutions. Achieving success with genAI mandates a strategic approach to organizational readiness.

GenAI represents the next evolution in operational machine learning, enabling self-learning based on patterns in existing data. This technology brings the concept of the augmented engineer to life by suggesting solutions, answering questions and explaining problem-solving methods. Additionally, it accelerates the integration of human expertise with advanced data analytics.

With 2.1 million jobs in U.S. manufacturing projected to go unfilled by 2030 (based on a Deloitte prediction), companies will need to increasingly rely on AI to fill the void. AI enhances human capacity to address emerging challenges with insights derived from operational data.

Assessing organizational readiness

To assess readiness and augment process data analysis with genAI, organizations must first examine their data quality. High-quality data is essential for genAI effectiveness. A key aspect of this quality is connected to its relevance to the specific problems a team is working on. To fulfill these requirements, users need the knowledge and ability to prepare their data effectively (as shown in Figure 1). After all, technology’s output is only as good as the quality of the data. As the saying goes: garbage in equals garbage out.

One of the greatest barriers to this kind of ongoing technical training is a lack of time, especially in sustained blocks, to engage in formal training courses. Fortunately, AI can help with this. The most forward-thinking manufacturers are using AI to provide industry-relevant, just-in-time learning on demand, enabling teams to—as one Seeq AI Assistant user said—“complete tasks eight times faster and without interrupting other teams for help."