Global Generative Design Market is Estimated to Witness High Growth Owing to Growing Adoption in Manufacturing Industries and Rapid Advancements in AI And ML Technologies
The Global Generative Design Market is estimated to be valued at US$ 4.02 Bn in 2024 and exhibit a CAGR of 16.3% over the forecast period 2024-2031. Generative design approach allows designers to automate intelligent design exploration, enabling rapid evaluation of thousands of design alternatives. Furthermore, increasing adoption of generative design software by automotive and aerospace industries for product design and development is further fueling market growth.
Market Dynamics:
Growing adoption of generative design across various manufacturing industries along with rapid advancements in artificial intelligence (AI) and machine learning (ML) technologies are the major factors driving the growth of the global generative design market. Generative design leverages AI and ML algorithms to automatically generate thousands of optimised design alternatives based on performance requirements defined by designers. This helps manufacturers to reduce product development cycle time and costs significantly. Additionally, integration of generative design tools with computer-aided design (CAD) systems is also facilitating wider application in designing complex parts and final products.
Advancements in the field of AI and machine learning is driving growth of the generative design market
The continuous advancements and improvements being made in the fields of artificial intelligence (AI) and machine learning are helping to propel the growth of the global generative design market. Generative design leverages AI and computational methods to automate parts of the design process. This has allowed engineers and designers to focus on more creative aspects of their work while delegating routine tasks to AI systems. As new algorithms and techniques continue to emerge in AI, it is helping generative design tools to become more sophisticated, autonomous, and able to tackle more complex design challenges. This is leading to higher adoption rates among companies looking for new ways to drive innovation and accelerate product development cycles.
Growing demand for lightweight and sustainable product design is a key driver
There is growing pressure on organizations across industries to develop more sustainable and eco-friendly products. This is driving increased focus on lightweight and sustainable design principles. Generative design tools are well-suited for such sustainable design goals as they help engineers optimize designs for weight reduction without compromising strength or functionality. With generative design approaches, thousands of design concepts can be evaluated in a short time to determine optimal designs that reduce material usage and therefore lower environmental impact. The ability of these tools to automate sustainable design is fueling their increased importance and aiding the growth of the generative design industry.
Lack of skilled workforce poses a challenge for adoption
While generative design tools hold much promise to revolutionize engineering processes, their adoption rates face a key hurdle in the lack of a sufficiently skilled workforce that can make the most of these advanced design solutions. Generative design requires skills spanning computer sciences, AI/ML proficiency as well as traditional engineering design knowledge. Finding talent that bridges across these diverse domains remains difficult. Without a trained workforce that understands both technology and design applications, the full potential of generative design cannot be realized. This skills gap acts as a restraint on the market's ability to grow to its full capabilities.
High upfront costs limit adoption among smaller organizations
Generative design software packages come with high upfront license and implementation costs that act as a barrier, especially for smaller engineering firms and design startups. While these tools promise to recoup expenses through reduced design cycle times or optimized products, justifying the initial investments can be challenging for cost-sensitive organizations. Additionally, integrating new generative design workflows may require process overhauls with associated consultancy and training expenditures. The steep costs deter adoption among cash-strapped smaller players, slowing down the overall market growth trajectory.
Emergence of generative design as a service offers new opportunities
To expand access to generative design capabilities, newer startup vendors have emerged offering these solutions through an on-demand software as a service (SaaS) model. This reduces upfront costs by switching to affordable usage-based pricing. It removes the need for big infrastructure investments and puts automated design power within reach of solopreneurs and small businesses. The pay-per-use model helps justify expenses through proven return on investments. Cloud-based models also eliminate maintenance overhead. The advent of generative design as cloud services is enabling a much wider set of organizations to leverage these capabilities, opening up new growth prospects for the market.
Growing demand from non-traditional industry verticals presents an opportunity
While traditionally adoption of generative design has been strongest among manufacturing industries, newer applications are emerging in non-traditional sectors like healthcare, architecture, media and entertainment. For instance, generative design is being used to develop customized medical devices and prosthetics, and in architectural spatial planning. GPU-accelerated generative models are letting creative professionals harness AI for visual content creation and design exploration tasks. The expansion of use cases to more diverse verticals beyond core engineering domains opens up a substantial greenfield opportunity. As awareness grows, these untapped markets will contribute significantly to future revenue streams in the generative design market.
Link: https://www.coherentmarketinsights.com/market-insight/generative-design-market-5141
Key Developments:
- In June 2022, Altair, a worldwide leader in computational science and artificial intelligence (AI), acquired Gen3D, a startup from the University of Bath in the UK. Gen3D is renowned for its groundbreaking application of the implicit geometry method to model intricate geometries, such as lattice structures, in additive manufacturing.
- In October 2022, Siemens, a leading global force in digitalization, and Desktop Metal, Inc., a major provider of additive manufacturing solutions, unveiled a comprehensive partnership designed to expedite the adoption of additive manufacturing (AM) for production purposes, with a particular focus on the world's largest manufacturers. This collaboration will integrate Siemens' technology with Desktop Metal's AM 2.0 systems, emphasizing binder jet 3D printing to boost efficiency and sustainability in manufacturing processes.
- In August 2022, Carbon, a top company in 3D printing technology, acquired ParaMatters, a provider of generative design software for additive manufacturing. This acquisition bolsters Carbon's software capabilities with topology optimization, enabling the creation of more complex and high-performance part designs in additive manufacturing. By incorporating ParaMatters' technology, Carbon seeks to enhance its generative design features and refine the product development process for its clients.
- In January 2022, Saffelberg Investments, an independent investment firm with a capital base of 380 million EUR, completed a funding round with Diabatix NV, a Belgian SaaS scale-up based in Leuven specializing in AI-driven generative thermal design. With a 2 million EUR investment, Saffelberg will aid Diabatix in accelerating the development of its ColdStream platform, which allows engineers to quickly generate optimized thermal designs for heat sinks and cold plates through the integration of AI and generative design.
Key Players:
Adobe Inc., Altair Engineering Inc., ANSYS Inc., Autodesk Inc., Bentley Systems Inc., Dassault Systèmes, Desktop Metal Inc., ESI Group, Google LLC, IBM Corporation, Microsoft Corporation, MSC Software, NVIDIA Corporation, Paramatters, and Siemens AG
