Global Generative AI in Industrial Design Market By Deployment Mode(On-Premise and Cloud-Based), By Application (Product Design, Customization, and Others), By Industry (Automotive, Aerospace, Furniture, and Others), By Region and Companies - Industry Segment Outlook, Market Assessment, Competition Scenario, Trends, and Forecast 2024-2033

Report Overview

Generative AI in Industrial Design Market size is expected to be worth around USD 1,749.2 Mn by 2033 from USD 198.6 Mn in 2023, growing at a CAGR of 25.0% during the forecast period from 2023 to 2033.

The surge in demand for new advanced technologies and integration of IoT in production techniques for outputs are some of the main key driving factors for the generative AI in industrial design market. Generative artificial intelligence is used to brief a wide range of modern technologies that makes machine to accomplish tasks that would require human intelligence. It comprises of using computer algorithms to put on intelligent behaviour and decision-making based upon huge sets of information.

The main element of GenAI comprises of ML, machine language processing and computer vision. ML includes the usage of algorithms that permits machine to understand from information and makes decisions based on that data. NLP which is also known as natural language processing includes the potentiality of machines to learn, process and produce human language. Computer vision comprises teaching machines to understand and know visual data such as pictures, audio and videos.

GenAI transforms the industrial design in a vital way. With the potentiality to discover various design solutions in a portion of the time it would take to develop them by hands or manually. The capability to instantly create and examine designs which means that helps the designers to work more effectively than ever before. This will also undoubtedly help the creative designers to focus more on the new ideas innovations and different aspects of work. It is a powerful tool for the designers that facilitates bonding or partnership between human and machines.

According to Infosys in May 2023, states that Infosys has launched Infosys Topaz, an AI-first providing to fasten business value for worldwide enterprises by using generative artificial intelligence. This will help to augment the capability of human enterprises and groups by providing numerous opportunities in the future. There are more than 12,000 AI used cases that has helped to accelerate and seed innovative ideas. Similarly, there are about more than 150 pre-trained AI models with more than 10+ AI platforms driven by AI-first experts and data strategists.

There are several advantages of using GenAI in industrial designs such as it helps to accelerates prototyping, maintains efficacy of design methodology and improves the product quality. GenAI also supports the designers to discover many designing alternatives that leads to more new ideas and innovative solutions. The demand for the generative AI in industrial design will increase due to its requirement in various industrial sectors and firms that will help in market expansion in the coming years.

Key Takeaways

• Market Value: Generative AI in Industrial Design Market size is expected to be worth around USD 1,749.2 Mn by 2033 from USD 198.6 Mn in 2023, growing at a CAGR of 25% during the forecast period from 2023 to 2033.
• Based on Deployment Mode: On-premise generative AI secures data in industrial design operations.
• Based on Application: Generative AI transforms product design, enhancing creativity and precision.
• Based on Industry: Generative AI revolutionizes automotive design, boosting efficiency and creativity.
• Regional Analysis: Generative AI dominates 46.5% of North American Industrial Design market.
• Growth Opportunity: Generative AI's strategic integration with industry-specific solutions and collaborative AI technologies drives transformative growth and innovation in industrial design.

Driving factors

Adaptability in Style and Aesthetics Enhances Customization and Client Satisfaction

Generative AI's adaptability in style and aesthetics represents a critical driver in the industrial design market. By integrating AI that can tailor artificial models to specific design needs, design agencies can vastly improve the relevance and appeal of their outputs. This technology allows for iterative feedback and real-time adjustments, which are invaluable in achieving client-specific outcomes.

The capability to quickly adapt designs according to client feedback without extensive manual reworking underpins not only enhanced customer satisfaction but also boosts the potential for creative innovation. As agencies adopt this technology, they can differentiate themselves in a competitive market by offering highly customized solutions efficiently.

Labor Productivity: Streamlining Design Processes and Economic Optimization

Generative AI significantly impacts labor productivity by automating and enhancing various work activities within industrial design. The ability of AI to learn and apply complex design rules and aesthetics reduces the reliance on human input for routine and intricate tasks alike.

This automation not only speeds up the design process but also frees up human designers to focus on more strategic and creative aspects of projects. The economic benefits are manifold—reduced labor costs, minimized errors, and accelerated project timelines—all contributing to a more productive and economically viable operational model.

Time and Cost Efficiency: Revolutionizing Model Generation

The use of Generative AI in automating model generation is a game-changer for time and cost efficiency in industrial design. By employing AI algorithms capable of transferring characteristics from one model to various others, design firms can bypass the time-intensive process of building each model from scratch.

This capability not only reduces the direct costs associated with manual model creation but also dramatically decreases the turnaround time for project completion. Consequently, firms can handle more projects simultaneously, significantly boosting throughput and profitability.

Restraining Factors

Computing Constraints: Limiting the Efficiency and Effectiveness of Generative AI

One of the primary restraining factors in the deployment of Generative AI within industrial design is the issue of insufficient computing power and model optimization. Many embedded AI systems are operated on devices with limited processing resources, which can significantly impede the performance of AI algorithms. This limitation often results in prolonged inference times, reduced accuracy, and ultimately, a diminished user experience.

Such technical constraints not only slow the adoption rate of Generative AI solutions but also affect the scalability and reliability of these technologies in complex industrial design applications. Without substantial investments in more powerful computing infrastructures or the development of more efficient AI models, the full potential of Generative AI in revolutionizing design processes may remain untapped.

Integration Challenges: Bridging the Gap with Legacy Systems

Another critical barrier is the difficulty of integrating Generative AI technologies with existing legacy systems within organizations. The design and implementation of AI solutions must be meticulously tailored to ensure compatibility with older infrastructures, which often do not support the latest advancements in AI technology.

This integration challenge can lead to significant delays in project timelines, increased costs, and potential disruptions in daily operations. Companies face the dual task of modernizing their IT systems and ensuring that new AI solutions can seamlessly interact with established protocols, a process that requires both time and technical expertise.

Deployment Mode Analysis

On-premise generative AI offers secure, customizable solutions for industrial design's complex needs.

In 2023, the On-Premise segment held a dominant market position in the deployment mode category of the Generative AI in Industrial Design Market, capturing more than a 60% share. This significant market share is indicative of a continued preference for on-premise solutions among enterprises that prioritize control, security, and data privacy. On-premise deployment allows firms to maintain physical control over their AI infrastructures and data storage, mitigating concerns about data breaches and third-party access which are paramount in sensitive industries.

The robust position of on-premise deployments is also reinforced by its integration capabilities with legacy systems, which many established industrial companies still operate. These organizations tend to favor on-premise solutions due to their alignment with existing IT and product design workflows, which can be extensively customized to suit specific operational needs without the constant requirement of internet connectivity.

Despite the dominance of on-premise solutions, the market is witnessing a gradual shift towards cloud-based models, driven by the scalability, cost-effectiveness, and enhanced collaborative features that cloud platforms offer. As industrial design processes increasingly integrate more complex and data-intensive generative AI applications, the flexibility of cloud solutions becomes more appealing.

Application Analysis

Generative AI in product design accelerates innovation, enhances functionality, and optimizes user experience.

In 2023, Product Design emerged as the frontrunner in the Generative AI in Industrial Design Market, particularly in the realm of Customization. This dominance can be attributed to the increasing demand for personalized products across various industries, ranging from automotive to consumer electronics. Leveraging Generative AI in Product Design has enabled companies to efficiently tailor their offerings to meet individual customer preferences, leading to enhanced customer satisfaction and brand loyalty.

Product Design utilizing Generative AI has significantly streamlined the design process, allowing for rapid iteration and optimization. By harnessing the power of algorithms to generate design variations based on specified parameters, companies can explore a myriad of design possibilities in a fraction of the time it would traditionally take. This not only accelerates time-to-market but also fosters innovation by encouraging experimentation with unconventional design concepts.

In addition to Customization, Generative AI has also made substantial inroads in Material Design within the Industrial Design sector. By simulating material properties and behaviors, designers can evaluate the performance of various materials in different environments, facilitating informed decision-making and ultimately leading to the development of more robust and sustainable products.

Industry Analysis

Generative AI revolutionizes automotive design, optimizing aerodynamics and material use for enhanced efficiency.

In 2023, Automotive solidified its stronghold as the leading segment in the Generative AI in Industrial Design Market, particularly within the automotive industry. This dominance can be attributed to the industry's relentless pursuit of innovation and efficiency, driving the adoption of cutting-edge technologies like Generative AI to revolutionize design processes and product development.

Within the automotive sector, Generative AI has proven instrumental in redefining traditional design methodologies. By leveraging algorithms to generate and optimize design alternatives based on specified constraints and objectives, automotive manufacturers can swiftly iterate through design iterations, enabling the rapid development of next-generation vehicles that prioritize performance, safety, and sustainability.

Moreover, the automotive industry's emphasis on customization and personalization has further fueled the adoption of Generative AI in design. By harnessing the power of data-driven design algorithms, automakers can tailor vehicle components and features to meet the diverse preferences and needs of consumers, enhancing overall customer satisfaction and brand loyalty.

Key Market Segments

Based on Deployment Mode

• On-Premise
• Cloud-Based

Based on Application

• Product Design
• Customization
• Material Design
• Prototyping and Simulation
• Other Applications

Based on Industry

• Automotive
• Aerospace
• Furniture
• Construction & Architecture
• Other Industries

Growth Opportunity

Industry-Specific Solutions

The Generative AI market is poised for transformative growth in 2024, especially within the industrial design sector. As companies increasingly tailor Generative AI solutions to specific industries, they unlock significant potential in areas such as healthcare, marketing, sales, education, and customer service.

This strategic segmentation allows firms to deeply integrate AI into core business processes, thereby not only enhancing operational efficiencies but also fostering a more intuitive design process. By leveraging AI-driven insights, companies can anticipate user needs more accurately and create more personalized, effective designs.

Collaborative Technological Integration

A key trend in 2024 is the convergence of Generative AI with other cutting-edge AI technologies like advanced analytics and machine learning. This integration extends the capabilities of industrial designers by providing them with tools that inspire innovation and streamline design processes.

For instance, in product development, combining Generative AI with machine learning algorithms can result in highly innovative outputs, optimized for both function and aesthetics. This synergy not only enhances the creative capabilities of designers but also shortens product development cycles and boosts market responsiveness.

Latest Trends

Real-World Application: Driving Productivity and Efficiency

Generative AI technology has reached a stage where its practical applications are tangible across various industrial domains. From enhancing field productivity to facilitating maintenance planning and enabling robotic automation, the key lies in accessible platforms. These platforms must empower both subject matter experts and data scientists with simplified access to intricate industrial data, fostering seamless integration into existing workflows.

Design Optimization: Unlocking Innovative Solutions

One of the most compelling trends shaping the global Generative AI in Industrial Design Market is its role in design optimization. By harnessing AI and advanced algorithms, generative design processes can autonomously generate solutions tailored to specific user-defined criteria. These criteria may span material selection, manufacturing processes, cost considerations, and more. By exploring a vast array of potential solutions, generative design not only expedites the design process but also fosters innovation by uncovering novel approaches to age-old challenges.

Regional Analysis

In the realm of industrial design, Generative AI has emerged as a transformative force, reshaping traditional approaches to design ideation and prototyping across global markets. North America stands as the foremost epicenter of this technological revolution, commanding a dominant share of 46.5% in the global market. With a robust ecosystem of technological innovation and significant investments in AI research and development, North America's prominence is underscored by its advanced infrastructure and a burgeoning landscape of startups and established players alike.

Meanwhile, Europe remains a key bastion of innovation, leveraging its rich industrial heritage and collaborative research networks to harness the potential of Generative AI. The European market is propelled by initiatives promoting digital transformation and sustainable design practices. Similarly, Asia Pacific emerges as a dynamic hub of growth, fueled by rapid industrialization and a burgeoning demand for smart manufacturing solutions. Asia Pacific showcases immense potential, driven by technological advancements and strategic partnerships aimed at enhancing design efficiency and product innovation.

In contrast, the Middle East & Africa and Latin America regions exhibit a slower pace of adoption, constrained by factors such as limited technological infrastructure and economic challenges. However, initiatives promoting digitalization and Industry 4.0 frameworks are gradually gaining traction, offering opportunities for market expansion in these regions. As Generative AI continues to evolve, collaborations between key industry players and government initiatives aimed at fostering innovation are expected to drive growth across all regions, catalyzing a paradigm shift in industrial design practices on a global scale.

Key Regions and Countries

North America

• US
• Canada
• Mexico

Western Europe

• Germany
• France
• The UK
• Spain
• Italy
• Portugal
• Ireland
• Austria
• Switzerland
• Benelux
• Nordic
• Rest of Western Europe

Eastern Europe

• Russia
• Poland
• The Czech Republic
• Greece
• Rest of Eastern Europe

APAC

• China
• Japan
• South Korea
• India
• Australia & New Zealand
• Indonesia
• Malaysia
• Philippines
• Singapore
• Thailand
• Vietnam
• Rest of APAC

Latin America

• Brazil
• Colombia
• Chile
• Argentina
• Costa Rica
• Rest of Latin America

Middle East & Africa

• Algeria
• Egypt
• Israel
• Kuwait
• Nigeria
• Saudi Arabia
• South Africa
• Turkey
• United Arab Emirates
• Rest of MEA

Key Players Analysis

In 2024, Autodesk, Inc. stands as a pivotal player in the global Generative AI in Industrial Design Market, commanding attention with its innovative solutions and industry-leading expertise. With its extensive portfolio of software tools tailored for industrial design, engineering, and manufacturing, Autodesk has been instrumental in driving the adoption of generative AI technologies across various sectors. The company's commitment to continuous research and development has enabled it to stay at the forefront of technological advancements, ensuring its offerings remain cutting-edge and relevant to evolving market needs.

Siemens emerges as another significant contender in the Generative AI landscape, leveraging its deep-rooted presence in industrial automation and digitalization. With its robust suite of software solutions, Siemens integrates generative AI capabilities seamlessly into the design and production processes, empowering businesses to optimize product performance, reduce time-to-market, and enhance overall efficiency.

Adobe Inc., known for its creative software solutions, has also made significant strides in the Generative AI domain, catering to the design-centric needs of industries ranging from automotive to consumer electronics. Through its innovative platforms and tools, Adobe facilitates the exploration of design possibilities, enabling users to unleash their creativity while leveraging the power of AI-driven insights.

Ansys, Inc. brings its expertise in simulation and engineering software to the Generative AI arena, offering comprehensive solutions that enable engineers to simulate, optimize, and validate designs with unparalleled accuracy and efficiency. Dassault Systèmes SE, PTC Inc., and Hexagon AB also contribute significantly to the market with their respective strengths in CAD, PLM, and manufacturing technologies.

While these key players dominate the landscape, other emerging contenders continue to make their mark, driving competition and fostering innovation in the rapidly evolving Generative AI in Industrial Design Market. As businesses increasingly recognize the transformative potential of generative AI, collaboration and strategic partnerships among these key players are expected to further accelerate market growth and adoption.

Top Key Players in Generative AI in Industrial Design Market

• Autodesk, Inc.
• Siemens
• Adobe Inc.
• Ansys, Inc.
• Dassault Systèmes SE
• PTC Inc.
• Hexagon AB
• Other Key Players

Recent Development

• In March 2024, Generative AI is revolutionizing industrial design by enabling McKinsey's teams to rapidly innovate and refine product concepts, significantly enhancing productivity and creativity throughout the product development lifecycle.
• In April 2024, In the McKinsey & Company report on the impact of Generative AI in product design, it is highlighted that Gen AI significantly accelerates and enhances the design process by enabling designers to quickly generate and iterate on innovative product solutions, ultimately transforming the way products are conceptualized and brought to market.
• In March 2024, As generative AI applications surge, McKinsey advises semiconductor leaders to strategically invest in expanding fabrication plants and innovating chip technologies to meet the escalating computational demands and ensure industry sustainability.
• In January 2024, According to Avi Dahiya, Founder & CEO, Twyn, Generative AI is revolutionizing the manufacturing industry by significantly enhancing digital twin development and introducing groundbreaking brain-tech interfacing for 3D model creation, signaling a major technological leap for companies committed to embracing cutting-edge innovations for increased efficiency and creativity.

Report Scope