AI and the Industry

Unlocking a New Potential Support System

Artificial intelligence (AI) has moved beyond the realm of science fiction and is transforming industries around the world, including component manufacturing. Yet, for many in the industry, AI can seem like an abstract or intimidating concept. What exactly is AI, and how can manufacturers start using it to drive tangible benefits? In the BCMC education session, Demystify AI, Ashley Baker provided a breakdown of AI fundamentals and explored practical ways to apply it within the industry.

At its core, AI is a branch of computer science focused on creating systems that simulate human intelligence. Unlike traditional programs, AI systems learn from data without needing to be explicitly programmed, which allows them to improve their performance over time. Today’s AI can analyze data, make decisions, solve complex problems, interpret language, and even process visual and auditory inputs. However, most AI systems are what experts call “Narrow AI,” designed to excel at specific tasks such as data entry automation, image recognition, or operating customer service chatbots. 

Despite its potential, AI still faces skepticism. Common concerns about AI include issues related to privacy, ethics, and the fear that it could replace human jobs. However, rather than viewing AI as a replacement for human workers, Ashley highlighted industry’s thought leaders who suggest thinking of it as a tool that enhances human capabilities. AI has the potential to automate repetitive tasks, allowing workers to focus on higher-value activities and new skill sets, rather than reducing overall job numbers. As one expert puts it, “AI won’t replace humans, but humans using AI will have an edge.” By seeing AI as a support system rather than a threat, companies can responsibly unlock its potential while addressing ethical concerns through careful data management and review practices.

For individuals and companies just beginning their journey with AI, Ashley suggests starting small to make the process more approachable. Experimenting with AI tools personally for tasks like research, editing, or brainstorming, can build confidence and familiarity. Professionals can use tools such as ChatGPT as digital assistants for tasks like information gathering and basic content generation. Organizations might consider offering internal bootcamps on AI, where employees can learn how AI can streamline tasks relevant to their specific roles and projects.

In the component manufacturing world, some early adopters are already experiencing benefits from AI. Ashley shared an industry example of a company that is reducing dependency on tech support by allowing teams to handle common queries in-house with AI. Some companies have even shifted personnel from tech support roles to newly created AI-focused positions, highlighting how AI can foster job growth and skill development rather than simply serve as task replacement. 

In practice, AI offers a broad range of applications for component manufacturing. Through various examples, Ashley explained how it can be used to develop training materials, and even streamline onboarding for new employees. AI-driven chatbots are already making strides in customer support, providing instant responses to common inquiries and freeing up human agents for more complex questions. Product scheduling, sales forecasting, personalized marketing, inventory management, and data handling are other areas where AI can bring efficiency gains. With AI tools for these tasks, manufacturers can optimize resources, reduce waste, and better predict customer demand.

Looking to the future, Ashley focused on a conversation with a component manufacturer who shared his ideas for AI applications. Most notable was his plan to automate the quoting process which would result in substantial time and cost savings. She also covered the concept of an AI-driven drone which would play a role in quality assurance tasks such as stacking and sorting materials. AI board-scanning technology was of particular interest, as well, as it would allow manufacturers to assess lumber characteristics with precision in an effort to build better components.

As with any transformative technology, AI requires careful planning and oversight to deliver its full benefits. Ashley emphasized that AI is only as effective as the data it learns from, and poor-quality inputs will lead to unreliable results. By committing to high standards of data quality and ethical oversight, companies can ensure that AI operates as a valuable tool rather than a risky unknown. Proper implementation can also mitigate risks of bias and misinformation, creating an environment in which AI’s advantages outweigh potential drawbacks.

The key to leveraging AI in component manufacturing is to take those first steps. Ashley suggested beginning with simple experimentation and encouraging a culture of learning. As AI tools become more integrated into the industry, companies that embrace AI responsibly will stand to benefit the most, realizing gains in productivity, innovation, and overall competitive advantage.