6 High-Impact Ways Manufacturers Are Using AI Today

AI (Artificial Intelligence) isn’t just a buzzword anymore—it’s quickly becoming a must-have for manufacturers trying to keep up with digital transformation and stay ahead of the curve.

Recent industry data shows that about 35% of manufacturing firms are already using AI in core production and data processes, and 95% plan to invest in AI-driven automation in the coming years.  

The good news: you don’t need a PhD in machine learning or a massive budget to start seeing real impact. In this blog, we’ll break down practical ways manufacturers can use AI right now and explain why having a centralized hub for your product content is essential for AI to truly work its magic.

• 6 Ways to Use AI Today  
  
  • Automating Repetitive Taks  
  • Smarter Content Creation  
  • Predictive Maintenance  
  • Better Quality Control  
  • Supply Chain Optimization  
  • Improving Product Management  
• Getting Started With AI: Real, Practical Next Steps
• How Prodify Sets You Up for AI Success

6 Ways to Use AI Today

1. Automating Repetitive Tasks

One of the easiest (and most impactful) ways to start using AI is through automation. Over 70% of employees say automation tools help accelerate their workflow, and even small automations can create major efficiency gains. AI-powered automation helps take tedious, time-consuming tasks off your team’s plate, reducing manual busy work, minimizing errors, and freeing up time to focus on higher-value activities.

Here are a few common ways manufacturers are using AI automation today:

• Smart Assistants & Support Tools: Chatbots that instantly answer product questions, pull up relevant documents, and guide partners or AEC prospects through your product information. ‍
• Internal Knowledge & Training Tools: Self-serve AI tools that help onboard new employees faster and reduce repetitive internal questions. ‍
• Invoice Processing & Workflow Orchestration: Automating routine workflows like approvals, exception escalations, and syncing updates across connected systems. ‍
• Data Entry & Validation: Reducing manual input by automatically capturing, checking, and organizing product data for accuracy and consistency.

2. Predictive Maintenance

Unexpected downtime is expensive, frustrating, and often completely avoidable. That’s why predictive maintenance is one of the most widely adopted AI use cases in manufacturing.

Instead of waiting for equipment to fail (or relying solely on scheduled maintenance), AI can analyze real-time machine data, like vibration, temperature, pressure, and performance patterns, to identify early warning signs before a breakdown happens.

Here’s how to start using predictive maintenance to your advantage:

• Identify your most critical equipment (the machines that cause the biggest disruption when they go down)
• Start collecting baseline performance data like vibration, temperature, cycle time, and output consistency
• Use sensors and monitoring tools to track equipment health in real time
• Look for repeat patterns that signal wear, failure, or inefficiency before breakdowns happen
• Build a proactive maintenance schedule based on data trends—not guesswork
• Use insights to plan downtime strategically so maintenance doesn’t interrupt production schedules

For building product manufacturers, predictive maintenance can be especially valuable for keeping production consistent and avoiding delays that impact distributor commitments and AEC project timelines.

3. Better Quality Control

Quality control is another area where AI is making a major impact, especially for manufacturers managing high production volume and strict performance requirements.

AI-powered inspection systems can analyze product output using sensors, imaging, and pattern recognition. This makes it easier to spot defects, inconsistencies, or deviations from specifications in real time—often faster and more accurately than manual inspection alone. This helps ensure the product delivered matches the product specified, protecting your brand reputation and nurturing long-term trust.

4. Supply Chain Optimization

If the past few years have taught us anything, it’s this: supply chains can go sideways fast. Between global disruptions, rising costs, and overnight demand changes, supply chain management has become one of the biggest stress points in manufacturing.

AI helps make supply chain planning less of a gamble and a lot more data driven. By analyzing huge amounts of information, like purchasing patterns, lead times, and inventory levels, AI can forecast demand, flag potential risks, and help your teams make smarter decisions faster.

The result? Fewer surprise shortages, less excess inventory collecting dust, and a much smoother path from production to delivery. And when AEC projects are on tight timelines, getting products delivered on time isn’t just helpful—it’s a competitive edge.

5. Smarter Content Creation

For building product manufacturers, technical design files are your most valuable content. CAD drawing, BIM models, 3D renderings, and specs are what ultimately help products get into real projects, but technical files alone aren’t enough. To stand out in a competitive market, manufacturers also need strong supporting content that builds credibility and drives engagement, like case studies, project spotlights, brochures, and other educational marketing materials.

While AI should never replace true product expertise, it can make content creation faster and more efficient by handling the heavy lifting, especially in the early stages of writing and editing.

Here are a few ways manufacturers are using AI to streamline content creation:

• Creating first drafts or improving existing copy
• Generating ALT text, email subject lines and preview text, meta descriptions for web pages, and more
• Checking that content is on brand  
• Adjusting content for different regions or audiences
• Repurposing content into different formats (for example, turning an eBook into a webinar)

When paired with expert review, AI can remove a lot of the “blank page” struggle and grunt work from content development—helping you produce more without sacrificing accuracy or quality.

6. Improving Product Management

Manufacturers often struggle with scattered specs, multiple file versions, and inconsistent naming conventions. Thankfully, AI can help make sense of it all by:

• Auto-tagging and categorizing assets  
• Generating metadata and product descriptions
• Detecting duplicate files, inconsistencies, and outdated versions
• Reducing time spent searching for files
• Extracting key data from files
• Automating file naming conventions  
• Identifying missing content
• Suggesting related products and variants
• Tracking engagement insights

But here’s the catch: AI is only as good as your product management platform. If your product files live in different, disconnected systems, AI can’t give you reliable insights.

AI performs best with clean, consistent data—without it, outputs quickly become messy and unreliable, often doing more harm than good. That’s where a central repository like Prodify, a unified PIM (Product Information Management) + DAM (Digital Asset Management) system, becomes non-negotiable.

Getting Started With AI: Real, Practical Next Steps

AI doesn’t have to be intimidating, and you don’t need to overhaul your entire organization overnight. The best approach is to start small, focus on high-impact wins, and build momentum from there.

Here are a few practical steps you can take right now:

1. Centralize your product content: Bring your critical product files and assets into a unified platform like Prodify so AI isn’t trying to learn from fragmented systems. Think of it as giving AI a clean workspace to operate in.

2. Start with one workflow: Choose one area where your team is already feeling pain, like file organization, content creation, or repetitive admin work, then do some research to find the best AI tool for the job.  

• For File Organization & Search: Tools like Google Cloud Search, Algolia AI, or AI-enhanced DAM systems with semantic search can understand natural language queries and help your team find what they need without hunting through folders. ‍
• For Content Creation & Drafting: Platforms such as ChatGPT, Jasper, or Writer can help save hours of writing time. ‍
• For Document Automation: Microsoft Power Automate AI Builder or Zapier with AI extensions can extract, classify, and organize data from files automatically. ‍
• For Workflow Automation: Tools like UiPath, Make (formerly Integromat), or Zapier can automate common processes like approvals, file tagging, version control triggers, and email routing. ‍
• For Quality & Defect Detection: AI-powered inspection systems like Landing AI or Cognex Vision Systems can analyze images and sensor data to catch defects faster than manual QA.

3. Track what’s working: Whether you’re using AI for forecasting, content, or product management, measure the results. Track time saved, fewer errors, faster turnaround, or improved engagement so you can justify continued investment.

4. Use AI as an assistant, not a replacement: AI works best when it supports your experts, not when it tries to replace them. Let AI handle repetitive tasks and first drafts, but keep your team in control of accuracy, compliance, and final approvals.

5. Stay curious: The AI world moves fast. New tools, agents, and upgrades pop up all the time, so keep an eye out for fresh opportunities to automate more and stay ahead.

How Prodify Sets You Up for AI Success

AI can’t fix messy data, but Prodify can.

By bringing your digital assets (CAD/BIM files, marketing materials, etc.) and product data (SKUs, pricing, etc.) into a single source of truth, Prodify ensures your AI tools have clean, structured, consistent information to work with. Instead of pulling from duplicate files, outdated versions, or mismatched naming conventions, AI can operate on accurate, up-to-date content—exactly what it needs to generate insights you can trust.

Learn more about Prodify here, or book a demo to get started.

Final Thoughts

AI isn’t a magic wand, but it is a powerful set of tools that, when used strategically, can reduce friction, eliminate busy work, and help you work smarter across the board. But it’s important to remember: AI isn’t a standalone solution. It’s part of a much bigger shift toward digital transformation, one that’s changing how manufacturers manage products, support the AEC community, and stay competitive in a spec-driven market.

Download our eBook for a complete guide to digital transformation for building product manufacturers.