Generative artificial intelligence (GenAI) is emerging as a game changer in the chemicals and materials industry. This technology, which combines advanced machine learning with vast data resources, has the potential to transform the industry by driving innovation, efficiency, and ecologically sound practices. Gen AI allows for faster research and development (R&D), resulting in shorter timelines and lower costs. It enables material optimization, which improves product performance and sustainability. Predictive maintenance and supply chain optimization are now possible, resulting in reduced downtime and more efficient logistics. Thus, GenAI has the potential to address the industry's growing demand for novel materials and environmentally friendly practices in a cost-efficient manner. However, complex regulatory landscapes, a talent gap in AI and data science, and the need for high-quality data present challenges.
This research service identifies the pain points across various business functions in the chemicals and materials industry, determining how they can be addressed by harnessing Gen AI. It presents an impact analysis of GenAI in the industry, along with a timeframe in which GenAI is expected to address bottlenecks. The study also examines the investment landscape, identifies the key industrial and academic players in this space, and highlights growth opportunities enabling the development and adoption of Gen AI technology in the chemicals and materials industry. The base year is 2022, and the forecast period is from 2023 to 2030.
Why Is It Increasingly Difficult to Grow?The Strategic Imperative 8™: Factors Creating Pressure on Growth
The Strategic Imperative 8™
The Impact of the Top 3 Strategic Imperatives on Generative Artificial Intelligence (GenAI) in the Chemicals and Materials Industry
Growth Opportunities Fuel the Growth Pipeline Engine™
Research Methodology
Emerging Trends and Critical Needs in the Chemicals and Materials Industry
Emerging Trends and Critical Needs in the Chemicals and Materials Industry (continued)
Overview of Key Subtasks Across Business Functions in the Chemicals and Materials Industry
Overview of Key Subtasks Across Business Functions in the Chemicals and Materials Industry (continued)
Overview of Key Subtasks Across Business Functions in the Chemicals and Materials Industry (continued)
Overview of Key Subtasks Across Business Functions in the Chemicals and Materials Industry (continued)
Evolution of GenAI from Concept to Creation
Evolution of GenAI from Concept to Creation (continued)
Comparison of GenAI Technology with Conventional Digital Tools
Comparison of GenAI Technology with Conventional Digital Tools (continued)
Transformative Aspects of GenAI in the Chemicals and Materials Industry
Growth Drivers
Growth Restraints
Scope and Segmentation
Application of GenAI in Chemicals and Materials R&D
Application of GenAI in Chemicals and Materials R&D (continued)
Application of GenAI in Chemicals and Materials R&D (continued)
Application of GenAI in Chemicals and Materials R&D (continued)
Application of GenAI in Chemicals and Materials R&D (continued)
Application of GenAI in Chemicals and Materials Manufacturing and Processing
Application of GenAI in Chemicals and Materials Manufacturing and Processing (continued)
Application of GenAI in Chemicals and Materials Manufacturing and Processing (continued)
Application of GenAI in Chemicals and Materials Manufacturing and Processing (continued)
Application of GenAI in Chemicals and Materials Manufacturing and Processing (continued)
Application of GenAI in Chemicals and Materials Commercialization
Application of GenAI in Other Domains of the Chemicals and Materials Industry
Application of GenAI in Other Domains of the Chemicals and Materials Industry (continued)
Application of GenAI in Other Domains of the Chemicals and Materials Industry (continued)
Application of GenAI in Other Domains of the Chemicals and Materials Industry (continued)
Impact Analysis of GenAI Across Chemicals and Materials Activities
Impact Analysis of GenAI Across Chemicals and Materials Activities (continued)
Impact Analysis of GenAI Across Chemicals and Materials Activities (continued)
Leading GenAI Solutions for the Chemicals and Materials Industry
Leading GenAI Solutions for the Chemicals and Materials Industry (continued)
Academic Research for Developing Chemicals and Materials by Leveraging GenAI
Academic Research for Developing Chemicals and Materials by Leveraging GenAI (continued)
Partnerships and Collaborations Aiming to Accelerate the Adoption of GenAI Capabilities
Funding and Investment Analysis on Expanding GenAI Capabilities for the Chemicals and Materials Industry
Use Cases of Implementing GenAI Capabilities in the Chemicals and Materials Industry
Use Cases of Implementing GenAI Capabilities in the Chemicals and Materials Industry (continued)
Examples of Chemicals and Materials Companies Trying to Explore or Implement GenAI Technology Across their Business Functions
Examples of Chemicals and Materials Companies Trying to Explore or Implement GenAI Technology Across their Business Functions (continued)
Analyst Perspective on GenAI’s Potential to Revolutionize the Chemicals and Materials Industry
Growth Opportunity 1: Quantum-powered GenAI for Optimizing Materials Properties
Growth Opportunity 1: Quantum-Powered GenAI for Optimizing Materials Properties (continued)
Growth Opportunity 2: Cloud-based GenAI Services for Accelerated Materials Discovery
Growth Opportunity 2: Cloud-based GenAI Services for Accelerated Materials Discovery (continued)
Growth Opportunity 3: GenAI with RPA for QC Compliance
Growth Opportunity 3: GenAI with RPA for QC Compliance (continued)
Technology Readiness Levels (TRL): Explanation
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Generative artificial intelligence (GenAI) is emerging as a game changer in the chemicals and materials industry. This technology, which combines advanced machine learning with vast data resources, has the potential to transform the industry by driving innovation, efficiency, and ecologically sound practices. Gen AI allows for faster research and development (R&D), resulting in shorter timelines and lower costs. It enables material optimization, which improves product performance and sustainability. Predictive maintenance and supply chain optimization are now possible, resulting in reduced downtime and more efficient logistics. Thus, GenAI has the potential to address the industry's growing demand for novel materials and environmentally friendly practices in a cost-efficient manner. However, complex regulatory landscapes, a talent gap in AI and data science, and the need for high-quality data present challenges.
This research service identifies the pain points across various business functions in the chemicals and materials industry, determining how they can be addressed by harnessing Gen AI. It presents an impact analysis of GenAI in the industry, along with a timeframe in which GenAI is expected to address bottlenecks. The study also examines the investment landscape, identifies the key industrial and academic players in this space, and highlights growth opportunities enabling the development and adoption of Gen AI technology in the chemicals and materials industry. The base year is 2022, and the forecast period is from 2023 to 2030.
| Deliverable Type | Technology Research |
|---|---|
| Author | Abhishek Paul Choudhury |
| Industries | Chemicals and Materials |
| No Index | No |
| Is Prebook | No |
| Keyword 1 | Generative AI Trends in Materials |
| Keyword 2 | Chemicals & Materials Tech Trends |
| Keyword 3 | Future Trends in AI Technology |
| Podcast | No |
| WIP Number | DAC0-01-00-00-00 |
Generative AI in the Chemicals and Materials Industry: Technology Advances and Growth Opportunities
Generative AI in the Chemicals and Materials Industry: Technology Advances and Growth Opportunities
Generative AI Integration Promises Transformational Growth with Higher ROI and Increased Margins
RELEASE DATE
31-Oct-2023
31-Oct-2023
REGION
Global
Global
Deliverable Type
Technology Research
Technology Research
Research Code: DAC0-01-00-00-00
SKU: CM_2023_276
$4,950.00
In stock
SKU
CM_2023_276