AI technology is revolutionizing how Cosentino innovates and develops new surfaces. (Illustrative AI-generated image).
- Cosentino is using Microsoft’s AI Discovery platform to significantly speed up the development of new surface materials.
- The platform combines agentic AI, high-performance computing, and advanced knowledge management to automate early-stage research.
- AI can analyze scientific literature, run simulations, and suggest new material formulations, reducing development time from months to days or hours.
- This allows Cosentino to respond faster to market trends, discover novel materials, and optimize resource usage.
- The initiative aims to enhance product innovation, improve sustainability by exploring eco-friendly materials, and reduce waste from failed experiments.
- Human experts will still guide the process, focusing on the AI-generated insights for final product development and manufacturing.
From Marble to AI: Cosentino’s 79-Year Innovation Journey
In 1945, a small family business in southeastern Spain began cutting and polishing marble. That company, Cosentino, grew steadily over the decades, expanding into new materials and colors. Today, Cosentino operates in over 120 countries, with its main factory complex in Almeria spanning more than 27 million square feet. Advanced machinery, cranes, and robots work together to prepare surface materials for kitchens, bathrooms, building facades, and interiors worldwide.
Cosentino is widely recognized for its engineered stone brands, such as Silestone and Dekton. These durable, stain-resistant surfaces are available in a vast array of colors and patterns. Historically, developing these materials involved a lengthy, manual process. Scientists and engineers would mix raw materials like quartz, glass, and pigments in a lab, bake test samples, and then subject them to rigorous testing for scratch and stain resistance. This iterative cycle could take months or even years for a single new product.
While this traditional approach sufficed in simpler market conditions, customer demand for new colors, textures, and performance features has accelerated. Cosentino also faces increasing competition. To innovate faster, the company turned to artificial intelligence.
In early 2025, Cosentino announced its adoption of Microsoft’s Discovery platform, becoming the first industrial company in Spain to do so. This advanced tool integrates AI, high-performance computing, and smart data management to accelerate scientific research. For Cosentino, a company whose success hinges on discovering and testing new surface materials, this represents a significant advancement.
The transition from traditional methods to AI-driven Cosentino AI materials discovery reflects the company’s long-standing commitment to material innovation. From natural stone to engineered composites, Cosentino now leverages software to predict future material needs before physical development begins.
Understanding the Microsoft Discovery Platform for Materials Science
The Microsoft Discovery platform combines three key components: agentic AI, high-performance computing, and advanced knowledge management. This powerful combination aims to revolutionize scientific research.
Agentic AI: The Autonomous Research Assistant
Agentic AI represents a form of artificial intelligence capable of independent action. It can set goals, plan tasks, and execute them systematically. In Cosentino’s context, this AI acts as a highly efficient research assistant. It can rapidly process vast amounts of scientific literature, patents, and internal reports, identifying patterns that human researchers might overlook and suggesting novel ingredient combinations.
High-Performance Computing: Accelerating Simulations
High-performance computing involves utilizing extremely powerful computers. These systems enable complex simulations and rapid data analysis. For materials science, this means accurately predicting how a new material will behave under various conditions-such as heat, pressure, or chemical exposure-without the need to create physical samples initially.
Advanced Knowledge Management: Unifying Data Sources
Advanced knowledge management allows the platform to consolidate data from diverse sources. This includes public databases, Cosentino’s proprietary research files, supplier information, customer feedback, and performance test results. The AI can seamlessly search across this unified data repository to gather necessary insights.
Together, these components automate much of the early-stage research. The system can scan scientific literature for new findings on binders, pigments, or reinforcing fibers, generate hypotheses about material combinations, run simulations to predict properties like strength and color stability, and analyze results to identify the most promising candidates for physical testing. This significantly reduces the time human experts spend on literature review and experimental design, allowing them to focus on the most viable concepts.
The platform also incorporates a learning mechanism. Each experiment, test result, and customer interaction feeds back into the system, continuously refining the AI’s understanding of what works and what doesn’t, thereby building an ever-expanding knowledge base.
Microsoft specifically designed the Discovery platform for scientific research fields like chemistry, biology, and materials science, making it a specialized tool for accelerating discovery. Cosentino is among the first industrial companies to apply it to commercial product development.
How Cosentino Leverages AI for Faster New Materials Development
Cosentino aims to use the Discovery platform to identify optimal formulations for new surface materials more efficiently. Previously, fulfilling a request for a specific countertop appearance, like mimicking Brazilian granite with added lightness and strength, involved extensive manual iteration. The R&D team would search existing formulas, tweak them, create test batches, and conduct numerous tests-a process that could take weeks or months per cycle.
With the AI platform, this process is streamlined. Users can specify desired attributes-color, hardness, stain resistance, weight, and material cost. The AI then analyzes available data, runs simulations, and proposes a select few promising formulas. Scientists then focus their testing efforts on these highly probable candidates, compressing the early-stage development from months to potentially hours or days.
This accelerated approach offers several key advantages:
- Faster Market Response: Enables Cosentino to quickly develop surfaces matching emerging design trends, such as a specific shade of matte blue, without falling behind competitors.
- Discovery of Novel Materials: The AI can suggest unconventional ingredient combinations that human researchers might overlook, potentially leading to breakthrough materials.
- Resource Optimization: Reducing the number of physical prototypes lowers costs associated with raw materials, energy, and labor, while also minimizing waste.
- Exploration of New Material Types: Facilitates the investigation of entirely new material categories, such as composites incorporating recycled waste or ultra-lightweight materials for facades.
Cosentino plans a phased rollout of the platform, training its R&D teams to collaborate with the AI as a partner. Human experts will retain final decision-making authority, but with the support of a more powerful and efficient tool.
Impact of AI-Driven Materials Discovery on Products and Sustainability
While consumers may not often consider the materials science behind their chosen surfaces, significant research underpins every countertop and floor tile. Cosentino’s products are used in demanding environments-homes, hotels, restaurants, hospitals, and offices-where they face constant wear from heat, spills, cleaning agents, and traffic.
Faster materials discovery translates to improved surfaces for all stakeholders. Designers gain access to desired aesthetics, builders benefit from easier-to-install materials, and homeowners receive durable, low-maintenance surfaces. For building facades, AI can help design lighter, stronger panels that offer enhanced resistance to weather and UV radiation, potentially improving building energy efficiency and safety.
Future applications could include surfaces with integrated antimicrobial properties or self-cleaning capabilities, simulated and validated by AI before production. Furthermore, the AI’s ability to efficiently explore formulations using recycled or bio-based ingredients supports Cosentino’s sustainability goals. By reducing failed experiments, the company conserves raw materials and energy. This aligns with the broader industry trend towards eco-friendly construction materials, addressing the significant environmental footprint of the sector.
Cosentino’s existing sustainability initiatives, such as solar power and water recycling at its Almeria factory, complement this AI-driven approach to developing greener products.
Microsoft’s Strategic Role in Industrial AI Adoption
Microsoft is positioned as a strategic partner for Cosentino, assisting in the integration of AI into its core research and development processes, beyond merely providing a software license.
This collaboration is part of Microsoft’s broader strategy to embed AI within traditional industries like manufacturing and construction. While AI’s application in consumer-facing technologies like chatbots and image generators garners significant attention, Microsoft sees substantial potential in optimizing physical-world processes, from product design to supply chain efficiency and waste reduction.
The Discovery platform, initially developed for pharmaceutical and academic research, has proven adaptable to any field reliant on scientific discovery. Cosentino serves as a crucial test case for the platform’s efficacy in commercial manufacturing, potentially paving the way for adoption by other industrial companies.
The partnership also highlights Cosentino as the first Spanish industrial company to implement the platform, offering mutual public relations benefits. Cosentino is showcased as an innovator, while Microsoft gains a valuable reference case for its AI solutions.
Microsoft provides the necessary cloud computing infrastructure, allowing Cosentino to scale its AI capabilities without substantial upfront investment in hardware. This model ensures flexibility and access to the latest technology, with Microsoft managing system maintenance and updates.
While financial terms remain undisclosed, the agreement is likely a multiyear commitment that includes ongoing support and training. Cosentino’s R&D personnel will receive instruction on utilizing the new tools, with Microsoft experts facilitating the transition. A key consideration for AI effectiveness is data quality; Cosentino will need to ensure its historical research data is accurate and well-organized for the AI to generate reliable predictions, a process Microsoft likely supported during onboarding.
It’s important to note that AI cannot entirely replace physical testing. Simulations provide valuable insights, but real-world validation remains essential. The AI’s role is to significantly reduce the number of less promising prototypes, thereby accelerating the path to market and ensuring that physical tests are focused on the most viable candidates.
The Future of Cosentino with AI-Driven Research and Development
Cosentino’s integration of AI into its R&D is a developing initiative. As the platform is implemented, its full impact will unfold over time. However, the anticipated outcomes are significant.
The development timeline for new surface materials is expected to shorten considerably. Projects that once took two to three years from concept to launch might now be completed in six to twelve months, providing a substantial competitive edge in a rapidly evolving market.
Furthermore, the AI’s capacity to conduct thousands of virtual experiments rapidly allows Cosentino to explore avenues previously unfeasible due to time and resource constraints. This expanded scope increases the potential for genuine innovation and the discovery of groundbreaking materials.
Regarding the workforce, while concerns about AI replacing human roles exist, Cosentino emphasizes that the objective is to augment, not replace, its scientists and technicians. By automating routine tasks like data analysis and literature searches, AI frees up researchers to concentrate on higher-level creative and strategic work. This collaborative approach aims to enhance overall productivity and innovation within the R&D department.
Frequently Asked Questions
How is Cosentino using AI to develop new materials?
Cosentino is using Microsoft's AI Discovery platform to accelerate the research and development of new surface materials. The AI analyzes data, runs simulations, and suggests promising formulations, significantly reducing the time and resources needed for material discovery and testing.
What is the Microsoft Discovery platform?
It's an advanced tool that combines agentic AI (AI that can act independently), high-performance computing, and advanced knowledge management. It's designed to speed up scientific research by automating data analysis, pattern recognition, and hypothesis generation.
How does AI speed up material development at Cosentino?
Instead of lengthy physical testing cycles, the AI can simulate material properties and suggest optimal ingredient combinations. This allows Cosentino to identify the most promising candidates for physical testing much faster, potentially reducing development timelines from months to days or even hours for initial research.
What are the benefits of using AI for Cosentino's materials discovery?
Benefits include faster response to market trends, the potential discovery of entirely new material types, reduced costs and waste from fewer physical prototypes, and the ability to explore more innovative and sustainable material options.
Will AI replace human scientists at Cosentino?
Cosentino states the goal is to augment, not replace, its R&D teams. AI will handle routine data analysis and literature searches, freeing up human experts for higher-level creative work and final decision-making.
How does this AI adoption impact sustainability?
By reducing the number of failed physical experiments, Cosentino wastes less raw material and energy. The AI can also more efficiently explore formulations using recycled or bio-based ingredients, supporting the development of greener products.
What role does Microsoft play in this partnership?
Microsoft acts as a strategic partner, providing the Discovery platform and the cloud computing infrastructure. They also assist Cosentino in integrating the AI into its R&D workflow and provide training and support.
