Steel Industry & Artificial Intelligence: How to Use AI to Be More Efficient & Generate More Profits

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Steel Industry & Artificial Intelligence: How to Use AI to Be More Efficient & Generate More Profits

Over the past two years, it has often been claimed that artificial intelligence (AI) is overvalued in the short term and undervalued in the medium to long term. However, the situation is changing rapidly: the industry is now at a turning point where AI can truly transform processes, and concrete examples of its use are multiplying.

Where to start introducing AI into a steel company?

In this article, we’ll look at the three common stages of AI implementation in the steel industry, detail five essential steps to increasing productivity with AI, and present twelve concrete examples of its use in a steel company.

The 3 stages of AI implementation in the steel industry

#1 Sales & Marketing

AI is revolutionizing marketing and sales practices in the steel industry. For example, by automating note-taking during meetings with tools such as Microsoft Teams, Zoom or third-party software such as Berrycast and Otter.AI, it’s possible to record every customer exchange, create meeting summaries and automatically generate follow-up tasks. These tools guarantee an up-to-date CRM while reducing manual input, all in just a few clicks.

Sales and marketing teams are often the first in companies to integrate artificial intelligence, as many of their tasks involve writing, translating, proofreading and also thinking. All these tasks can now be greatly accelerated by artificial intelligence models to improve the end result.

Concrete examples:

  • Marketing plan: Use ChatGPT to refine your strategies, brainstorm customer personas and create a tailored marketing plan.
  • Website optimization: Ask ChatGPT to suggest improvements or rewrite your LinkedIn bio and sales prospecting messages for maximum impact.
  • Tender analysis: Centralize information in a tool like NotebookLM to analyze and synthesize tender responses, generating FAQs or full summaries. You could also create a short podcast automatically in one click, summarizing the documents received, all aligned with the questions you wish to answer.
  • Writing blog posts: AI, such as ChatGPT or Claude AI, can greatly facilitate the writing of industry-specific blog posts, reducing the creation time from ideation to finalization by almost tenfold.

#2 Back-office & administrative functions

The second level of AI adoption in steel companies is the back-office, or administrative functions. AI can dramatically reduce the time spent on routine tasks such as entering supplier invoices and extracting key information from compliance documents.

AI has the potential to transform repetitive processes to free up valuable time, enabling teams to focus on higher value-added tasks.

Concrete examples:

  • Supplier invoice management: Automating supplier invoice entry can cut data entry and re-invoicing time by up to 95%, while reducing the error rate.
  • Compliance document processing: Use AI to automatically extract data from Mill Test Reports and transmit them to customers, saving several hours of processing time each week.
  • Drafting e-mails: Write your customer and internal follow-up emails to save time and, above all, respond faster with greater impact.

#3 Production & delivery

It’s in the production and delivery phase that AI has the greatest potential to bring big gains for your business.

The challenge for the majority of organizations is that the key people with a good grasp of AI and technology are not often to be found within production and delivery teams, and are therefore unfamiliar with the real issues and problems faced by these teams. This greatly reduces the possibility of integrating AI quickly and effectively.

What’s more, the tools available are not yet sufficiently mature or easy to integrate. This explains why it is often the last stage of implementation in steel companies.

Order optimization and material purchasing forecasts, production planning and monitoring, quality inspection, vehicle loading planning for delivery: AI has the potential to be a powerful ally for your company’s operational performance.

Concrete examples:

  • Purchasing forecasting: Use AI to better predict material purchasing cycles and take advantage of the best prices based on market trends.
  • Production planning: Implement AI algorithms to optimize planning, maximize equipment utilization and reduce production lead times.
  • Quality inspection: Intelligent cameras and AI models can identify defects in real time, improving quality and reducing waste.
  • Load planning: A poorly loaded truck can affect the day-to-day profitability of your operations. Often, knowledge of this process rests with one or two people, creating dependency. Automating part of this process reduces this dependency and helps minimize errors.
  • Optimizing delivery routes: If routes are not optimal, customer satisfaction and profitability can suffer. AI can optimize delivery routes, minimize errors, increase customer satisfaction and improve profit margins.

Optimizing Beyond Excel: Industries GRC’s Success Story

Find out how one metal products manufacturer optimized production planning and boosted operational efficiency with tailor-made technology.

Steps to implementing a successful AI strategy

The 3-stage concept helps to understand how AI adoption happens incrementally in steel organizations and to identify where leverage has the most potential.

Developing a plan and methodical approach to successfully integrating AI into your business is the next step. Here’s an example of a 5-step plan you could use.

Step 1: Assess the current situation

Start by analyzing your existing processes in each stage:

  • Marketing and sales: What tools do you already use? Where are the biggest potential gains?
  • Back-office: Which tasks are repetitive and time-consuming?
  • Production: Where are the main problems to be solved by AI? Do your tools already integrate AI functionalities that you’re not using?

This assessment enables you to see where AI can make a difference.

Step 2: define an innovation leader and surround yourself with experts

It’s essential to appoint an AI and innovation leader within your company. This leader will ensure that AI initiatives are aligned with the company’s strategic objectives.

We also recommend collaborating with a specialized AI firm that knows your industry well, such as Code&Steel or Openmind Tech. This will enable you to benefit from industry best practices and rapidly implement AI projects.

Step 3: define an AI policy

Since AI is now ubiquitous, a clear usage policy is essential to frame the use of tools and protect your data:

  • Use of AI tools: Identify the AI tools in use and their relevance to your privacy standards.
  • Data security: Are you subject to specific data privacy laws?
  • Technology access rules: Make sure you limit usage to AI tools that are secure and validated by the company.

Step 4: Identify quick wins and spread the word

Look for quick wins where AI can deliver immediate results. These early successes are crucial to demonstrating the value of AI and encouraging its adoption across the enterprise.

Step 5: Identify potential gains on critical processes

For maximum impact, identify the critical problems in your processes where AI could make the difference. Rather than integrating AI at all costs, start with concrete needs and problems.

Conclusion: AI as an engine for transformation in the steel industry

Artificial intelligence is no longer a technology of tomorrow; it’s already a reality of today. Every day, at Openmind Tech and Code&Steel, we see new concrete cases of AI infusion and are surprised ourselves at the speed at which it’s all evolving.

We’re dealing with a technology that’s evolving exponentially. It’s best to prepare and move ahead as early as possible, before the competition does. The first to use the full potential of AI will most likely be tomorrow’s leaders in the steel industry.

By following a structured approach – assessing your current situation, appointing an innovation leader, defining a clear policy and identifying quick wins and gains in your critical processes – you’ll give yourself every chance of maximizing the impact of AI for your business.

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