The manufacturing sector is undergoing a profound transformation driven by the exponential growth of data and Industry 5.0 technologies like AI and GenAI. As they concretize their business plans for growth and sustainability, CIOs endeavor to increase their investment in AI and ML technologies.
According to McKinsey, GenAI could contribute up to $430 billion in value to the industry.

Effectively harnessing the potential of GenAI to deliver tangible value and achieve a quick return on investment can be challenging for many companies. For manufacturing CIOs, the pressing question is: how can this transformative technology be deployed effectively to achieve measurable outcomes across the value chain?

This article explores actionable strategies and real-world applications.

As part of its GenAI Acceleration program, Eviden has collaborated with numerous manufacturers to leverage GenAI efficiently. From our interactions with clients, we have identified eight top use cases that create high value and ROI across the manufacturing value chain.

This article explores actionable strategies and real-world applications. Discover how manufacturers are moving beyond pilots to full-scale execution, leveraging GenAI to solve complex challenges, optimize operations, and unlock new value streams.

In this article, we will explore real-world examples of how AI and GenAI are applied in the manufacturing industry — from research and development to production, sales, and service — creating measurable value at every stage.

 

Unlocking opportunities with GenAI in R&D

AI and GenAI’s impact on research and development is expected to grow rapidly, driving innovation, accelerating time-to-market, and reducing costs. By automating routine tasks, generating creative ideas, and analyzing complex data, GenAI can significantly streamline two key R&D processes.

  • Product design: The combination of high-performance computing resources and Computer Aided Engineering and Testing (CAE/CAT) technologies enables manufacturers to dramatically speed up their R&D processes. Our experience shows that industry leaders like Bosch and BMW have successfully implemented this approach with Eviden’s science + computing arm, achieving much faster innovation cycles and reduced time-to-market. As our experience with BullSequana AI and major manufacturing projects demonstrates, the combination of AI and HPC is a key pathway for accelerating innovation in manufacturing.
  • Developer assistant: AI has the potential to boost developers’ efficiency and productivity by automating repetitive tasks. AI-powered development and testing tools can increase application development or modernization efficiency by up to 30%, as demonstrated recently for a large car manufacturer using our innovative MO4D GenAI-assisted development framework. Additionally, AI can identify patterns in data sets and suggest new research avenues through comprehensive data analysis. This allows developers to focus on higher-level, innovative tasks.

 

Putting it to practical use in production

AI and GenAI are making significant inroads into the production stage of manufacturing. By leveraging advanced algorithms and machine learning models, manufacturers can significantly optimize production lines, enhance product quality, and reduce waste.

Here are three major use cases:

  • Quality control: Powered by AI, automated quality inspection and defect detection can achieve up to 99% detection accuracy, dramatically improving product quality. For instance, companies like Airbus and an automobile manufacturer have successfully implemented these techniques with our support to enhance quality control processes and maintain consistently high standards.
  • Predictive maintenance: By analyzing sensor data, AI can improve equipment reliability and predict failures with up to 20% greater accuracy; reducing downtime and minimizing costs, too. Notable manufacturers such as Daimler Truck and Acond have partnered with us to adopt these technologies effectively.
  • Integrated supply chain and demand planning: Advanced data analytics and AI enable manufacturers to optimize supply chain operations and demand forecasting. Real-time data integration from IoT devices combined with historical sales data enhances supply chain visibility, improving operational efficiency by up to 20%. For example, we collaborated with a leading modular housing manufacturer and a top logistics company to implement AI-driven demand forecasting, achieving up to 30% greater accuracy, reducing stockouts and waste, and optimizing inventory levels.

Leveraging GenAI for seamless sales and service

The integration of AI and GenAI into sales and service supports manufacturers in predicting customer behaviors, creating personalized content, and automating complex tasks. This enables proactive customer support and informed decision-making.

Key use cases include:

  • Personalized marketing: Advanced AI analytics empower manufacturers to design highly targeted marketing campaigns across channels such as email, social media, and web advertising. This drives customer engagement and increases conversion rates. For instance, we supported global CPG leaders like Estée Lauder in leveraging these capabilities to streamline their marketing efforts and strengthen customer relationships.
  • Sales tools: AI-powered sales tools leverage data analytics, natural language processing, and machine learning to provide actionable customer insights. This gives the sales teams the advantage of understanding customer behavior better and crafting highly personalized strategies for B2B accounts or B2C customers, thereby proactively identifying new opportunities and boosting sales. In this domain, we have supported automotive players like AAA Auto and Esure, achieving exceptional sales results and reducing churn by 20%.
  • Knowledge search: GenAI-powered knowledge bases enhance information access for all workers, especially in a factory and in after-sales services. Such tools enable employees to quickly retrieve product information, service protocols, and company policies. Using GenAI-powered frameworks like Eviden Knowledge Pilot, workers can efficiently generate reports, resolve complex issues, and make informed, data-driven decisions; resulting in a 30% boost in productivity.

                                                               

The strategic edge

From accelerating R&D and enhancing quality control to optimizing supply chains and revolutionizing customer engagement, experience demonstrates that the latest advancements in AI and GenAI empower manufacturers to achieve unprecedented levels of efficiency, innovation, and personalization.

The emergence of Intelligent Agents — where Eviden plays a leading role — will further accelerate this potential!

 

If you would like to discuss these use cases in greater detail, you can drop us a message or connect with us on LinkedIn.

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