The Intersection - Episode 8: What Can AI Actually Do in Manufacturing?
In this episode of The Intersection, Megan Kacvinsky and Denine Harper sit down with co-host Steve Coffey to explore what AI can actually do inside a building product manufacturing organization. The conversation moves beyond generative AI and focuses on practical applications around data, production visibility, process improvement, and technology integration, including how manufacturers can connect existing systems without replacing their entire tech stack.
Summary
In this episode of The Intersection, Megan Kacvinsky and Denine Harper sit down with co-host Steve Coffey to explore what AI can actually do inside a building product manufacturing organization. The conversation moves beyond generative AI and focuses on practical applications around data, production visibility, process improvement, and technology integration, including how manufacturers can connect existing systems without replacing their entire tech stack.
Key Insights
- AI in manufacturing goes far beyond ChatGPT. Machine learning, computer vision, and predictive technologies have been used in manufacturing for years.
- Many manufacturers are using only a fraction of the capabilities within their existing ERP, CRM, and other technology platforms.
- The bigger challenge is often not a lack of software, but siloed systems and disconnected data across sales, finance, operations, and production.
- AI can help make sense of messy data, but it cannot fix a fundamentally broken process.
- Manufacturers should start with the business outcome and workflow they want to improve, then determine what technology is needed.
- Better production visibility can uncover bottlenecks, scrap trends, capacity issues, quality patterns, and at-risk orders.
Practical Takeaways for Manufacturers
- Start with the problem, not the AI tool.
- Map the workflow and identify where information, processes, or handoffs are breaking down.
- Look for ways to better connect the technology you already own before replacing major systems.
- Use AI to help organize and interpret messy data, but address underlying process problems at the same time.
- Prioritize visibility from order entry through production and delivery.
- Evaluate AI investments based on measurable business outcomes such as capacity, efficiency, margin, quality, and customer experience.
- Don’t assume weak legacy technology puts you behind. Less infrastructure can sometimes make it easier to adopt newer, more agile solutions.
Quotable Moments
- “You have to start with the business outcome and the process, not the technology.” – Steve Coffey
- “You can’t just dump AI on top of bad process and expect it to fix everything.” – Steve Coffey
- “If you’re a building product manufacturer and you’re feeling like you’re behind from a technology perspective, from a data perspective, ironically, that could almost become your superpower right now.” – Megan Kacvinsky
- “The biggest opportunity by far is data set process simplification.” – Denine Harper
Next Steps for Manufacturers
Before adding another AI tool, identify the business outcome you want to improve and understand the process behind it. Look closely at where data is disconnected, where visibility breaks down, and where existing technology is underutilized. The opportunity with AI isn’t simply to add more software. It’s to make better use of the systems, data, and processes you already have so your organization can make faster, better decisions.
About the Hosts
Megan Kacvinsky — CEO | Point To Point
Megan Kacvinsky helps Building Product Manufacturers drive specification through targeted AEC marketing. As a partner at Point To Point, she specializes in demand generation, customer engagement, and strategic content marketing that fuels sales success.
With 15+ years of experience, Megan combines digital marketing expertise with sharp business acumen to bridge the gap between marketing strategy and real-world impact. She has transformed marketing programs for Fortune 500 companies, mid-market firms, and startups—adapting strategies to fit each organization's unique needs. Known for her tailored, results-driven approach, Megan crafts high-impact solutions that help brands thrive in the competitive building and manufacturing industries.
Denine Harper — Founder | DHx Consulting
Denine Harper is the founder of DHx Consulting and a Fractional CMO who helps building materials manufacturers turn strategy into measurable growth. She works at the intersection of brand, demand generation, and go-to-market execution—aligning sales, marketing, and operations to drive revenue without friction.
With experience leading large-scale brand and performance initiatives, Denine brings a practical, operator’s perspective to growth. She is known for building systems that improve visibility, strengthen positioning, and help companies scale with confidence.
Steve Coffey — Senior Managing Partner | Coffey & Co
Steve Coffey is the co-founder of C&C and has spent nearly a decade working closely with building materials manufacturers across the residential and commercial construction industry. His experience spans executive strategy, plant operations, and job site realities, giving him a practical understanding of how products actually make it into buildings. Today, he helps companies bridge the gap between innovation and execution by aligning teams, improving visibility, and building systems that enable scalable growth.