The agentic AI in digital engineering market size has grown exponentially in recent years. It will grow from $6.03 billion in 2025 to $9.87 billion in 2026 at a compound annual growth rate (CAGR) of 63.8%. The growth in the historic period can be attributed to computer-aided design adoption, digital engineering tool evolution, growth of simulation software, early AI integration in engineering, demand for faster product development.
The agentic AI in digital engineering market size is expected to see exponential growth in the next few years. It will grow to $69.23 billion in 2030 at a compound annual growth rate (CAGR) of 62.7%. The growth in the forecast period can be attributed to complex product design requirements, expansion of smart manufacturing, demand for automated engineering validation, rising adoption of digital twins, integration of AI across product lifecycles. Major trends in the forecast period include autonomous engineering design systems, AI-driven digital twin optimization, self-learning engineering workflows, agent-based simulation and testing, explainable AI in engineering decisions.
The increasing demand for automation is expected to drive the growth of agentic AI in the digital engineering market in the coming years. Automation refers to the use of technology to carry out tasks or processes with minimal human involvement, improving efficiency and accuracy. The rising demand for automation is fueled by the need to lower operational costs and reduce human errors across different industries. Agentic AI in automation supports systems in making independent, intelligent decisions and optimizing workflows. For example, in September 2025, the International Federation of Robotics, a Germany-based industry association promoting robotics research, reported that the total number of industrial robots in operation worldwide reached 4,664,000 units in 2024, an increase of 9% from the previous year. Therefore, the growing demand for automation is contributing to the expansion of agentic AI in the digital engineering market.
Key players in the agentic AI in digital engineering market are focusing on innovations such as AI-driven digital labor platforms to boost workforce productivity, streamline engineering processes, and enable intelligent task automation. These platforms use autonomous AI agents to automate tasks, improve decision-making, and optimize workflows across digital engineering, software development, and enterprise operations. For instance, in March 2025, Salesforce Inc., a U.S.-based cloud software company, launched Agentforce 2dx, the latest version of its digital labor platform. This upgrade allows AI agents to operate autonomously beyond chat interfaces, integrating seamlessly with existing data systems and business logic. It enables AI to anticipate needs, take action dynamically, and enhance efficiency, agility, and scalability.
In January 2025, HCLTech Ltd., an India-based technology company, partnered with Salesforce Inc. to accelerate AI-driven innovation in enterprise applications. This collaboration aims to transform enterprise applications by advancing from basic chatbots to sophisticated AI-driven agents that enhance customer experiences, improve operational efficiency, and drive innovation in agentic AI. Salesforce Inc. uses Agentic AI to enhance automation, customer engagement, and enterprise workflows in digital engineering.
Major companies operating in the agentic AI in digital engineering market are Siemens AG, Accenture plc, NVIDIA Corporation, Capgemini SE, HCL Technologies Limited, Dassault Systèmes, PTC Inc., UiPath Inc., Persistent Systems Limited, GlobalLogic Inc., Altair Engineering Inc., Kent PLC, PagerDuty, Cigniti Technologies Limited, Indium Software Limited, Aisera Inc., Sinequa SAS, Adept AI Labs Inc., Ampcome Technologies Pvt. Ltd., Orby AI Inc.
North America was the largest region in the agentic AI in digital engineering market in 2025. The regions covered in the agentic AI in digital engineering market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa. The countries covered in the agentic AI in digital engineering market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Taiwan, Russia, South Korea, UK, USA, Canada, Italy, Spain.
Tariffs have impacted the agentic AI in digital engineering market by increasing costs of high-performance computing hardware and specialized engineering software infrastructure. Engineering firms in North America and Asia Pacific are affected due to dependence on imported compute systems. Higher costs have influenced investment timelines for advanced simulation and design automation projects. Organizations are prioritizing high-impact engineering use cases. Tariffs are also encouraging development of regional engineering cloud platforms. This is strengthening domestic digital engineering capabilities and reducing long-term infrastructure dependency.
The agentic AI in digital engineering market research report is one of a series of new reports that provides agentic AI in digital engineering market statistics, including agentic AI in digital engineering industry global market size, regional shares, competitors with a agentic AI in digital engineering market share, detailed agentic AI in digital engineering market segments, market trends and opportunities, and any further data you may need to thrive in the agentic AI in digital engineering industry. This agentic AI in digital engineering market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.
Agentic artificial intelligence (AI) in digital engineering refers to AI systems capable of operating autonomously, making decisions, and completing complex engineering tasks with minimal human intervention. The goal is to automate processes such as design, testing, and optimization, enhancing efficiency, accuracy, and innovation in digital product development.
The primary technologies of agentic AI in digital engineering include generative AI for engineering design, digital twins and AI-driven simulations, AI in robotics and automation, explainable AI (XAI) for engineering, and other related technologies. Generative AI for engineering design uses algorithms to autonomously generate innovative design solutions based on specified parameters, optimizing factors such as functionality, performance, and cost-efficiency. These technologies are deployed through various models, including on-premise and cloud-based solutions, and serve a broad range of applications, such as product design and development, predictive engineering analytics, process automation and workflow optimization, AI-enhanced simulation and testing, intelligent infrastructure, and smart manufacturing. Major industries utilizing these technologies include automotive and aerospace, energy and utilities, construction and civil engineering, electronics and semiconductors, healthcare and medical devices, among others.
The agentic AI in digital engineering market consists of revenues earned by entities by providing services such as generative design, autonomous simulation, and predictive maintenance. The market value includes the value of related goods sold by the service provider or included within the service offering. The agentic AI in digital engineering market also includes sales of simulation tools, smart sensors, and data analytics tools. Values in this market are ‘factory gate’ values, that is, the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors, and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.
The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD unless otherwise specified).
The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.
This product will be delivered within 1-3 business days.
The agentic AI in digital engineering market size is expected to see exponential growth in the next few years. It will grow to $69.23 billion in 2030 at a compound annual growth rate (CAGR) of 62.7%. The growth in the forecast period can be attributed to complex product design requirements, expansion of smart manufacturing, demand for automated engineering validation, rising adoption of digital twins, integration of AI across product lifecycles. Major trends in the forecast period include autonomous engineering design systems, AI-driven digital twin optimization, self-learning engineering workflows, agent-based simulation and testing, explainable AI in engineering decisions.
The increasing demand for automation is expected to drive the growth of agentic AI in the digital engineering market in the coming years. Automation refers to the use of technology to carry out tasks or processes with minimal human involvement, improving efficiency and accuracy. The rising demand for automation is fueled by the need to lower operational costs and reduce human errors across different industries. Agentic AI in automation supports systems in making independent, intelligent decisions and optimizing workflows. For example, in September 2025, the International Federation of Robotics, a Germany-based industry association promoting robotics research, reported that the total number of industrial robots in operation worldwide reached 4,664,000 units in 2024, an increase of 9% from the previous year. Therefore, the growing demand for automation is contributing to the expansion of agentic AI in the digital engineering market.
Key players in the agentic AI in digital engineering market are focusing on innovations such as AI-driven digital labor platforms to boost workforce productivity, streamline engineering processes, and enable intelligent task automation. These platforms use autonomous AI agents to automate tasks, improve decision-making, and optimize workflows across digital engineering, software development, and enterprise operations. For instance, in March 2025, Salesforce Inc., a U.S.-based cloud software company, launched Agentforce 2dx, the latest version of its digital labor platform. This upgrade allows AI agents to operate autonomously beyond chat interfaces, integrating seamlessly with existing data systems and business logic. It enables AI to anticipate needs, take action dynamically, and enhance efficiency, agility, and scalability.
In January 2025, HCLTech Ltd., an India-based technology company, partnered with Salesforce Inc. to accelerate AI-driven innovation in enterprise applications. This collaboration aims to transform enterprise applications by advancing from basic chatbots to sophisticated AI-driven agents that enhance customer experiences, improve operational efficiency, and drive innovation in agentic AI. Salesforce Inc. uses Agentic AI to enhance automation, customer engagement, and enterprise workflows in digital engineering.
Major companies operating in the agentic AI in digital engineering market are Siemens AG, Accenture plc, NVIDIA Corporation, Capgemini SE, HCL Technologies Limited, Dassault Systèmes, PTC Inc., UiPath Inc., Persistent Systems Limited, GlobalLogic Inc., Altair Engineering Inc., Kent PLC, PagerDuty, Cigniti Technologies Limited, Indium Software Limited, Aisera Inc., Sinequa SAS, Adept AI Labs Inc., Ampcome Technologies Pvt. Ltd., Orby AI Inc.
North America was the largest region in the agentic AI in digital engineering market in 2025. The regions covered in the agentic AI in digital engineering market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa. The countries covered in the agentic AI in digital engineering market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Taiwan, Russia, South Korea, UK, USA, Canada, Italy, Spain.
Tariffs have impacted the agentic AI in digital engineering market by increasing costs of high-performance computing hardware and specialized engineering software infrastructure. Engineering firms in North America and Asia Pacific are affected due to dependence on imported compute systems. Higher costs have influenced investment timelines for advanced simulation and design automation projects. Organizations are prioritizing high-impact engineering use cases. Tariffs are also encouraging development of regional engineering cloud platforms. This is strengthening domestic digital engineering capabilities and reducing long-term infrastructure dependency.
The agentic AI in digital engineering market research report is one of a series of new reports that provides agentic AI in digital engineering market statistics, including agentic AI in digital engineering industry global market size, regional shares, competitors with a agentic AI in digital engineering market share, detailed agentic AI in digital engineering market segments, market trends and opportunities, and any further data you may need to thrive in the agentic AI in digital engineering industry. This agentic AI in digital engineering market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.
Agentic artificial intelligence (AI) in digital engineering refers to AI systems capable of operating autonomously, making decisions, and completing complex engineering tasks with minimal human intervention. The goal is to automate processes such as design, testing, and optimization, enhancing efficiency, accuracy, and innovation in digital product development.
The primary technologies of agentic AI in digital engineering include generative AI for engineering design, digital twins and AI-driven simulations, AI in robotics and automation, explainable AI (XAI) for engineering, and other related technologies. Generative AI for engineering design uses algorithms to autonomously generate innovative design solutions based on specified parameters, optimizing factors such as functionality, performance, and cost-efficiency. These technologies are deployed through various models, including on-premise and cloud-based solutions, and serve a broad range of applications, such as product design and development, predictive engineering analytics, process automation and workflow optimization, AI-enhanced simulation and testing, intelligent infrastructure, and smart manufacturing. Major industries utilizing these technologies include automotive and aerospace, energy and utilities, construction and civil engineering, electronics and semiconductors, healthcare and medical devices, among others.
The agentic AI in digital engineering market consists of revenues earned by entities by providing services such as generative design, autonomous simulation, and predictive maintenance. The market value includes the value of related goods sold by the service provider or included within the service offering. The agentic AI in digital engineering market also includes sales of simulation tools, smart sensors, and data analytics tools. Values in this market are ‘factory gate’ values, that is, the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors, and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.
The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD unless otherwise specified).
The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.
This product will be delivered within 1-3 business days.
Table of Contents
1. Executive Summary
2. Agentic AI in Digital Engineering Market Characteristics
3. Agentic AI in Digital Engineering Market Supply Chain Analysis
4. Global Agentic AI in Digital Engineering Market Trends and Strategies
5. Agentic AI in Digital Engineering Market Analysis of End Use Industries
7. Global Agentic AI in Digital Engineering Strategic Analysis Framework, Current Market Size, Market Comparisons and Growth Rate Analysis
8. Global Agentic AI in Digital Engineering Total Addressable Market (TAM) Analysis for the Market
9. Agentic AI in Digital Engineering Market Segmentation
10. Agentic AI in Digital Engineering Market, Industry Metrics by Country
11. Agentic AI in Digital Engineering Market Regional and Country Analysis
12. Asia-Pacific Agentic AI in Digital Engineering Market
13. China Agentic AI in Digital Engineering Market
14. India Agentic AI in Digital Engineering Market
15. Japan Agentic AI in Digital Engineering Market
16. Australia Agentic AI in Digital Engineering Market
17. Indonesia Agentic AI in Digital Engineering Market
18. South Korea Agentic AI in Digital Engineering Market
19. Taiwan Agentic AI in Digital Engineering Market
20. South East Asia Agentic AI in Digital Engineering Market
21. Western Europe Agentic AI in Digital Engineering Market
22. UK Agentic AI in Digital Engineering Market
23. Germany Agentic AI in Digital Engineering Market
24. France Agentic AI in Digital Engineering Market
25. Italy Agentic AI in Digital Engineering Market
26. Spain Agentic AI in Digital Engineering Market
27. Eastern Europe Agentic AI in Digital Engineering Market
28. Russia Agentic AI in Digital Engineering Market
29. North America Agentic AI in Digital Engineering Market
30. USA Agentic AI in Digital Engineering Market
31. Canada Agentic AI in Digital Engineering Market
32. South America Agentic AI in Digital Engineering Market
33. Brazil Agentic AI in Digital Engineering Market
34. Middle East Agentic AI in Digital Engineering Market
35. Africa Agentic AI in Digital Engineering Market
37. Agentic AI in Digital Engineering Market Competitive Landscape and Company Profiles
38. Agentic AI in Digital Engineering Market Other Major and Innovative Companies
41. Agentic AI in Digital Engineering Market High Potential Countries, Segments and Strategies
42. Appendix
Executive Summary
Agentic AI In Digital Engineering Market Global Report 2026 provides strategists, marketers and senior management with the critical information they need to assess the market.This report focuses agentic AI in digital engineering market which is experiencing strong growth. The report gives a guide to the trends which will be shaping the market over the next ten years and beyond.
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Description
Where is the largest and fastest growing market for agentic AI in digital engineering? How does the market relate to the overall economy, demography and other similar markets? What forces will shape the market going forward, including technological disruption, regulatory shifts, and changing consumer preferences? The agentic AI in digital engineering market global report answers all these questions and many more.The report covers market characteristics, size and growth, segmentation, regional and country breakdowns, total addressable market (TAM), market attractiveness score (MAS), competitive landscape, market shares, company scoring matrix, trends and strategies for this market. It traces the market’s historic and forecast market growth by geography.
- The market characteristics section of the report defines and explains the market. This section also examines key products and services offered in the market, evaluates brand-level differentiation, compares product features, and highlights major innovation and product development trends.
- The supply chain analysis section provides an overview of the entire value chain, including key raw materials, resources, and supplier analysis. It also provides a list competitor at each level of the supply chain.
- The updated trends and strategies section analyses the shape of the market as it evolves and highlights emerging technology trends such as digital transformation, automation, sustainability initiatives, and AI-driven innovation. It suggests how companies can leverage these advancements to strengthen their market position and achieve competitive differentiation.
- The regulatory and investment landscape section provides an overview of the key regulatory frameworks, regularity bodies, associations, and government policies influencing the market. It also examines major investment flows, incentives, and funding trends shaping industry growth and innovation.
- The market size section gives the market size ($b) covering both the historic growth of the market, and forecasting its development.
- The forecasts are made after considering the major factors currently impacting the market. These include the technological advancements such as AI and automation, Russia-Ukraine war, trade tariffs (government-imposed import/export duties), elevated inflation and interest rates.
- The total addressable market (TAM) analysis section defines and estimates the market potential compares it with the current market size, and provides strategic insights and growth opportunities based on this evaluation.
- The market attractiveness scoring section evaluates the market based on a quantitative scoring framework that considers growth potential, competitive dynamics, strategic fit, and risk profile. It also provides interpretive insights and strategic implications for decision-makers.
- Market segmentations break down the market into sub markets.
- The regional and country breakdowns section gives an analysis of the market in each geography and the size of the market by geography and compares their historic and forecast growth.
- Expanded geographical coverage includes Taiwan and Southeast Asia, reflecting recent supply chain realignments and manufacturing shifts in the region. This section analyzes how these markets are becoming increasingly important hubs in the global value chain.
- The competitive landscape chapter gives a description of the competitive nature of the market, market shares, and a description of the leading companies. Key financial deals which have shaped the market in recent years are identified.
- The company scoring matrix section evaluates and ranks leading companies based on a multi-parameter framework that includes market share or revenues, product innovation, and brand recognition.
Report Scope
Markets Covered:
1) By Technology: Generative AI For Engineering Design; Digital Twins And AI-Driven Simulations; AI In Robotics And Automation; Explainable AI (Xai) For Engineering; Other Technologies2) By Deployment Model: On-Premise; Cloud-Based
3) By Application: Product Design And Development; Predictive Engineering Analytics; Process Automation And Workflow Optimization; AI-Augmented Simulation And Testing; Intelligent Infrastructure And Smart Manufacturing; Other Applications
4) By Industry Vertical: Automotive And Aerospace; Energy And Utilities; Construction And Civil Engineering; Electronics And Semiconductor; Healthcare And Medical Devices; Other Industry Verticals
Subsegments:
1) By Generative AI For Engineering Design: Algorithm-Driven Design Generation; Parametric And Topology Optimization; Design Space Exploration; Product Lifecycle Management2) By Digital Twins And AI-Driven Simulations: Virtual Prototyping; Predictive Maintenance And Diagnostics; Real-Time Monitoring And Analysis; Simulation-Based Optimization
3) By AI In Robotics And Automation: Autonomous Manufacturing Systems; Robotic Process Automation (RPA); AI-Powered Collaborative Robots (Cobots); AI-Driven Supply Chain Robotics
4) By Explainable AI (XAI) For Engineering: Transparent Decision-Making Models; Model Interpretability In Engineering Systems; AI Model Validation And Verification; Trust And Compliance In AI Systems
5) By Other Technologies: AI-Enhanced Augmented Reality (AR) For Design; AI In Additive Manufacturing (3D Printing); Cognitive Engineering And Problem-Solving AI; AI-Powered Computational Fluid Dynamics (CFD)
Companies Mentioned: Siemens AG; Accenture plc; NVIDIA Corporation; Capgemini SE; HCL Technologies Limited; Dassault Systèmes; PTC Inc.; UiPath Inc.; Persistent Systems Limited; GlobalLogic Inc.; Altair Engineering Inc.; Kent PLC; PagerDuty; Cigniti Technologies Limited; Indium Software Limited; Aisera Inc.; Sinequa SAS; Adept AI Labs Inc.; Ampcome Technologies Pvt. Ltd.; Orby AI Inc.
Countries: Australia; Brazil; China; France; Germany; India; Indonesia; Japan; Taiwan; Russia; South Korea; UK; USA; Canada; Italy; Spain.
Regions: Asia-Pacific; South East Asia; Western Europe; Eastern Europe; North America; South America; Middle East; Africa
Time Series: Five years historic and ten years forecast.
Data: Ratios of market size and growth to related markets, GDP proportions, expenditure per capita.
Data Segmentation: Country and regional historic and forecast data, market share of competitors, market segments.
Sourcing and Referencing: Data and analysis throughout the report is sourced using end notes.
Delivery Format: Word, PDF or Interactive Report + Excel Dashboard
Added Benefits:
- Bi-Annual Data Update
- Customisation
- Expert Consultant Support
Companies Mentioned
The companies featured in this Agentic AI in Digital Engineering market report include:- Siemens AG
- Accenture plc
- NVIDIA Corporation
- Capgemini SE
- HCL Technologies Limited
- Dassault Systèmes
- PTC Inc.
- UiPath Inc.
- Persistent Systems Limited
- GlobalLogic Inc.
- Altair Engineering Inc.
- Kent PLC
- PagerDuty
- Cigniti Technologies Limited
- Indium Software Limited
- Aisera Inc.
- Sinequa SAS
- Adept AI Labs Inc.
- Ampcome Technologies Pvt. Ltd.
- Orby AI Inc.
Table Information
| Report Attribute | Details |
|---|---|
| No. of Pages | 250 |
| Published | February 2026 |
| Forecast Period | 2026 - 2030 |
| Estimated Market Value ( USD | $ 9.87 Billion |
| Forecasted Market Value ( USD | $ 69.23 Billion |
| Compound Annual Growth Rate | 62.7% |
| Regions Covered | Global |
| No. of Companies Mentioned | 21 |
