AI for Manufacturers: How To Start Using AI in Manufacturing — WSI Webinar Series Part 2

Lisa Kilrea is the Founder of WSI eResults, a leading digital marketing agency that specializes in helping manufacturers, distributors, and B2B companies grow through AI-powered, data-driven strategies. With over 20 years of entrepreneurial experience and a proven track record, Lisa has led WSI Results to deliver standout lead generation and revenue growth in the industrial sector. Her background includes work with major brands like Quaker Oats and BP Petroleum, and she's known for pioneering innovative marketing tactics that blend traditional expertise with cutting-edge digital solutions. In this episode… In today's fast-paced, technology-driven world, AI is no longer a far-off concept — it's transforming industries right before our eyes. For manufacturers, the challenge isn't just about keeping up with innovation; it's about strategically incorporating AI to drive tangible results. So, how can manufacturers begin their AI journey, and where do they start? According to Lisa Kilrea, a digital marketing and AI expert, manufacturers should first focus on leveraging AI that is already embedded within the tools they're using. She emphasizes that AI doesn't always require adopting groundbreaking new technologies; in many cases, it is already integrated into existing platforms such as CRMs, ERPs, and customer service systems. These systems can help automate repetitive tasks and boost productivity, creating immediate value without overhauling existing processes. The key takeaway here is simple: AI isn't about replacing humans, but enhancing their capabilities, leading to better customer service and more efficient operations. In this episode of In Good Company: Where Relationships Drive Results, part two of WSI's webinar series, Lisa Kilrea discusses how manufacturers can start using AI to improve their processes. She explains the five stages of AI adoption, from existing tools to advanced AI copilots. Lisa also discusses practical examples, like AI's role in demand forecasting and automating quoting processes, which streamline operations and enhance business outcomes.