The PTC China Industry Elite Summit series is a high-end, invitation-only exchange platform created by PTC for decision-makers of leading domestic enterprises, focusing on how business leaders, in an era of widespread AI adoption, can rely on frontier AI technology and business process restructuring to respond to the iterative transformation of organizational collaboration and operating models — helping enterprises seize development opportunities in a complex market environment, achieve digital-intelligent transformation, and solidify their core competitiveness.
Currently, industrial AI is moving from concept pilots to the critical stage of business value deployment. Generative AI for engineering scenarios, business agents, digital threads, ontology modeling, knowledge graphs and other industrial digitalization technologies are deeply penetrating the automotive industry, reshaping the full value chain of product R&D, production delivery and O&M services. Driven by the waves of electrification, intelligence, connectivity and sharing, the automotive industry is accelerating its transformation toward software-defined vehicles, with opportunities and challenges coexisting: product software-hardware coupling keeps deepening, R&D iterations speed up and system scenarios grow increasingly complex, while cost reduction and efficiency gains, functional safety and overseas compliance have become practical issues that automakers urgently need to solve.
Standing at the tide of industrial transformation, on September 2, 2026, the PTC China Automotive Industry Elite Summit was successfully held in Hefei. With "The AI-Empowered Journey of Digital Transformation for Automakers" as its core theme, the conference brought together PTC global executives, local technical experts and industry ecosystem partners, and assembled digitalization leaders from benchmark enterprises in commercial vehicles, passenger vehicles, components and new energy. More than 160 industry colleagues gathered on site for in-depth exchanges around topics such as PTC's AI strategy, engineering AI scenario deployment, digital transformation practices of local enterprises, full-chain business innovation and software compliance building, jointly exploring viable paths for AI to empower high-quality transformation of the automotive and energy industries.
Welcome Address
Mr. Liu Qiang, PTC Senior Vice President and President of Greater China
Mr. Liu Qiang, PTC Senior Vice President and President of Greater China, delivered a welcome address. He said that over the past year, the speed of AI-driven industry transformation has been unprecedented; Chinese local large-model and agent innovation is advancing rapidly, bringing enormous changes to traditional manufacturing. Around the theme "The AI-Empowered Journey of Digital Transformation for Automakers," the conference focused on three major topics for in-depth discussion: PTC's global AI strategy and product layout, domestic customer innovation cases, and innovative practices combining PTC products with AI. Mr. Liu also introduced the distinguished guest lineup, including senior technical experts from PTC's global automotive industry and representatives of benchmark enterprise customers. Finally, Mr. Liu said PTC will continue to promote AI-driven full-value-chain innovation and bring more practical deployment cases to the industry.
PTC's Intelligent Product Lifecycle Strategy
Mr. Tom Bianchi, Senior Vice President of Global Marketing at PTC
Mr. Tom Bianchi, Senior Vice President of Global Marketing at PTC, shared PTC's intelligent product lifecycle strategy. The traditional product lifecycle can hardly match today's pace of change; fragmented tools, manual processes and data silos are becoming obstacles to growth. The intelligent product lifecycle is powered by product data, connected through openness, and driven by AI as the core engine, connecting planning, definition, design, production and service, helping enterprises build products faster, more cost-effectively and with higher quality. Companies such as Lamborghini, Schneider Electric and Johnson & Johnson have achieved faster R&D, higher service revenue and stronger collaboration through this model.
Supporting this strategy is PTC's unified AI platform, covering the model layer, semantic layer, data layer and agent layer, and providing specialized agents for BOM, design, DFM, requirements, test cases, service insights and more in products such as Windchill, Creo, Codebeamer, ServiceMax and Servigistics — some officially released, more on the roadmap. "We don't serve AI; AI serves us." Mr. Bianchi emphasized that PTC advances AI deployment on the premises of precision, manufacturability, traceability and intellectual property protection. Currently, many leading Chinese industry enterprises have long-term cooperation with PTC in CAD, PLM, ALM and SLM, continuously deepening their intelligent product lifecycle practices.
AI-Empowered Digital Transformation of Automotive R&D
Mr. Shi Zhanbei, CTO of PTC Greater China
Mr. Shi Zhanbei, CTO of PTC Greater China, delivered the keynote "AI-Empowered Digital Transformation of Automotive R&D." Citing multiple industry research data, he pointed out that global AI investment continues to rise and most enterprises have started AI pilots, but only a few have truly realized business value, with many projects stuck at the pilot stage and struggling to scale. From an enterprise strategy perspective, Mr. Shi broke down the multi-dimensional risks of technology, data, organization and culture in manufacturing AI transformation, directly pointing to the industry's two core data pain points: MBD model-based development suffers from semantic context gaps, and full-lifecycle multi-form BOMs and product configurations struggle to guarantee cross-business consistency.
PTC proposed a four-layer R&D paradigm architecture — AI technology foundation, AI-native data layer, intelligent business flow layer and innovation application layer — reconstructing the traditional R&D model through ontology modeling, knowledge graphs and Agent Flow process orchestration. Mr. Shi highlighted AI-empowered Order-to-Delivery (OTD) deployment cases, intuitively presenting efficiency, accuracy and cost improvement benefits through the real business effects of agents for requirements extraction, configuration recommendation, BOM generation, 3D duplicate checking and control plan preparation. Finally, he presented the five-stage manufacturing AI transformation roadmap — from cognitive learning, pilot validation and business integration to scaled application and strategic transformation — providing automakers with a systematic implementation reference path for moving from experience-driven discrete R&D to AI-collaborative innovative R&D.
AI-Integrated Vehicle Requirements Management Solution
Mr. Yang Wei, Business Development Manager at PTC
Mr. Yang Wei, Business Development Manager at PTC, shared the AI-integrated vehicle requirements management solution, focusing on automakers' R&D pain points amid automotive electrification and intelligentization, providing a new path for forward R&D in the industry. As the automotive industry transforms toward software-defined vehicles, OTA iterations and personalized scenario experiences have become mainstream, but domestic automakers generally face fragmented requirements management, high cross-domain collaboration barriers, difficult data traceability and high dependence on manual work, constraining R&D efficiency and product compliance.
The solution builds a complete vehicle requirements management business architecture covering the full process from requirements collection, definition and decomposition to verification, with core capabilities such as platform-based product line engineering, full-chain RFLPT traceability, multi-dimensional compliance control, and performance-functional requirements coordination, adapting to domestic and international automotive safety standards such as ISO 26262 and ASPICE. At the same time, the solution introduces AI capabilities in scenarios such as requirements translation and duplicate checking, intelligent decomposition, consistency checking and automatic test case generation, driving cross-domain collaboration from human-driven to data-driven, helping automakers connect the full R&D chain, achieve traceable requirements and controllable changes, consolidate R&D competitiveness in the software-defined vehicle era, and support the transformation toward full-lifecycle service operations.
The Path to Excellence in Vehicle Requirements Management at Leading German Automakers
Mr. Frank Möring, Vice President of Technology at PTC Europe
Mr. Frank Möring, Vice President of Technology at PTC Europe, presented "The Path to Excellence in Vehicle Requirements Management at Leading German Automakers," sharing Codebeamer's outstanding practices at BMW and Volkswagen. Industry trends such as intelligentization, electrification and globalization are driving up product complexity. German automakers pay great attention to mechatronic-software multi-domain collaboration, compliance-fulfilling traceability, and reusability; they regard requirements as the source of product development that runs through the entire product lifecycle, and requirements engineering has become a strategic capability of the enterprise.
In Germany, both BMW and Volkswagen have adopted PTC Codebeamer for requirements management — covering not only software requirements but also vehicle-level and system-level requirements — and achieved traceability management that meets compliance requirements. Volkswagen Group has also introduced AI capabilities, actively promoting AI-driven, data-based end-to-end requirements management. Finally, Mr. Frank concluded that PTC's ALM solutions can effectively help enterprises improve time-to-market in global markets, profitability, safety and quality.
ALM Digitalization Case Sharing from a Leading Domestic Energy Enterprise
A digitalization leader from a leading domestic energy enterprise shared an enterprise-grade ALM system building case. Against the backdrop of the global energy structure accelerating its transformation toward multi-energy complementarity of "solar, storage, wind and hydrogen," software has become the core control hub of energy systems. At present, the software R&D model suffers from pain points such as tool silos, missing chain traceability, insufficient software-hardware collaboration, and difficulty reusing knowledge assets — severely constraining software R&D quality and delivery efficiency. To address this, the enterprise launched enterprise-grade ALM system construction, creating a full-chain integrated software collaborative R&D platform covering the complete cycle of requirements, design, development, testing and release, achieving bidirectional traceability across requirements, versions, design, code and testing.
On the core solution: through process standardization, end-to-end full-chain connectivity, deep toolchain integration, software shelf and enterprise knowledge base building, R&D management is being pushed from extensive "rule by people" to standardized "rule by data," breaking tool silos, achieving platform-level knowledge asset accumulation and reuse, and making the R&D process fully visible and controllable. The ALM system platform is built on PTC's ALM product Codebeamer, leveraging its powerful bidirectional traceability, high performance and high integrability to break tool barriers and accumulate R&D knowledge assets. The platform implementation follows the strategy of "commonality first, then individuality; pilots first, then replication" — seed users first, then rollout to business units. Next, the enterprise will deeply integrate AI capabilities into the ALM platform, deploying scenarios such as requirements parsing, automatic test case generation and intelligent defect analysis, continuously releasing digital R&D effectiveness and supporting high-quality innovative development of new energy products.
Intelligent Product Design and AI Applications
Mr. Chen Limin, Senior Technical Manager at PTC
Mr. Chen Limin, Senior Technical Manager at PTC, presented intelligent product design and AI applications. Combining industry research data, he analyzed the practical challenges manufacturers commonly face — difficulty achieving on-time mass production delivery of new products, prominent innovation pressure and persistently high R&D costs — and introduced Creo 13's modern R&D system driven by the dual wheels of "model-based product development MBD/MBE + artificial intelligence," fully explaining Creo's three-tier, stepped local AI capabilities of advise, assist and automate:
- The first tier, advisory level, provides knowledge base Q&A, software operation guidance and troubleshooting;
- The second tier, assistive level, can read and parse 3D models, outputting targeted design suggestions based on geometric features and parameter information;
- The third tier, automation level, supports automatically generating and executing design scripts through natural-language interaction, achieving automated processing of design tasks — and all capabilities support localized deployment on enterprise intranets, eliminating the security risk of model data spillover.
The presentation introduced Creo's localized AI Skill Market capability: the platform preloads parameterized design skills for generic components such as gears and screws, supporting quick installation and activation; enterprises can also encapsulate proprietary Skills based on their own process standards and design templates, accumulating unique engineering knowledge and expanding CAD intelligent business capabilities on demand. He also demonstrated a similar-part retrieval agent application, effectively resolving long-standing pain points of R&D, standardization and procurement departments such as one-part-many-codes, duplicate modeling and material code inflation, achieving efficient part reuse, material standardization analysis and intelligent procurement price comparison. In addition, Mr. Chen introduced Creo 13's new version features in large-assembly performance optimization, brand-new harness and electrical design, composite material design, multiphysics simulation and more, demonstrating through measured comparison data several-fold to over ten-fold performance improvements in core operations such as global interference, clearance analysis and assembly regeneration. The presentation concluded with Creo AI's future evolution strategy, looking ahead to CAD's development from intelligent assistant to intelligent engineering agent.
The New Windchill Helps R&D Cut Costs and Boost Efficiency
Mr. Zhou Haitao, Senior Manager of Automotive Industry Solutions at PTC
Mr. Zhou Haitao, Senior Manager of Automotive Industry Solutions at PTC, shared the development direction of the PTC PLM platform around "The New Windchill Helps R&D Cut Costs and Boost Efficiency." Automotive enterprises' R&D management currently faces practical challenges such as cumbersome operations that make it hard to release data value, single-channel and inefficient internal/external collaboration, and high learning costs from personnel turnover. Mr. Zhou introduced the innovative evolution directions of the new Windchill platform, covering multiple core capabilities including the new-generation user experience, AI for PLM, the Jetstream dedicated collaboration platform, the MCP Model Context Protocol, SaaS-based deployment, and DFX design for manufacturing and service, and announced the product version naming plan: Windchill 13.1.2 will be the last numerically numbered version, after which year-based versions such as Windchill 2027 and 2028 will be adopted.
On AI deployment in industrial PLM, he used the full engineering change process as a typical business scenario, demonstrating how multiple types of AI agents enable intelligent operations of problem reporting, impact analysis and design verification, combining the technical architecture of business flow definition, agent planning, ontology modeling and data connectivity to achieve AI efficiency gains while ensuring the rigor and accuracy of output results. He also introduced user-side capabilities such as the PTC Jetstream online collaboration solution, role-based UI/UX optimization, and Creo View WEB lightweight browsing. Finally, he pointed out the pain points of traditional Windchill upgrades — hard-to-assess risks, heavy workloads and high dependence on expert experience — and proposed that PTC is exploring embedding AI into the full upgrade lifecycle, relying on multiple types of agents to complete assessment surveys, code migration and automated testing, significantly reducing project implementation cycles and costs, ultimately helping enterprises solidify their R&D platform foundation and achieve R&D cost reduction, efficiency gains and business innovation growth.
R&D Digitalization Construction Practice and Exploration at a Leading Domestic Commercial Vehicle Enterprise
A leader from a leading domestic commercial vehicle enterprise shared on the theme "R&D Digitalization Construction Practice and Exploration." As a leading domestic medium- and heavy-duty commercial vehicle company, the enterprise has built an integrated PDM R&D environment centered on Windchill and CVPDM, connecting the end-to-end product data value chain from planning, design, process, manufacturing and sales to the aftermarket, and highlighted two key digitalization construction projects: whole-vehicle DMU and frame hole groups. Addressing the business pain points of traditional whole-vehicle DMU — inefficient manual assembly checking, high missed-detection risk and difficult heterogeneous CAD collaboration — the DMU project achieved automatic model assembly and batch automatic clearance/interference checking, compressing whole-vehicle assembly time from 8 hours manually to 10–15 minutes and greatly improving whole-vehicle model verification coverage; the frame hole group project completed part-based and parametric transformation of hole groups, connecting the digital chain from design to the factory's three-side punching, reducing design errors and omissions and greatly reducing the factory's secondary processing costs each year.
Looking toward future intelligent evolution, she introduced the enterprise's AI planning and layout: sorting out AI scenarios around design, verification and product data release, carrying out a Creo GTO structural part generative design pilot, and attempting to achieve design-simulation integrated iteration to shorten product development cycles. She said the enterprise will continue to deepen its CAD/PLM platform capability building, gradually integrate AI capabilities into the full product R&D process, and continuously improve whole-vehicle R&D quality and efficiency, supporting the continuous enhancement of product competitiveness.
How to Address Software Compliance Development in the AI Era
Ms. Duan Lihua, Automotive Industry Business Development Manager at PTC
Ms. Duan Lihua, Automotive Industry Business Development Manager at PTC, presented "How to Address Software Compliance Development in the AI Era." With the intensive deployment of multiple strong standards for batteries and autonomous driving, automotive software compliance has entered "deep water." Meanwhile, the closing compliance window and rising overseas thresholds are evolving automotive software compliance from single-dimension common-standard responses into a three-dimensional cross matrix of "horizontal common standards + vertical professional strong standards + global market access thresholds" — with complexity growing exponentially and compliance capability becoming a new "technical barrier."
Facing this predicament, enterprises urgently need to build a unified data foundation, addressing compliance challenges through "one horizontal, one vertical cross-regulation data sharing and reuse + AI efficiency gains." PTC proposed the "ontology-based AI compliance review solution," in which Codebeamer, as the data layer of the AI ontology architecture, plays the crucial role of "data cornerstone." Its powerful end-to-end bidirectional traceability can break through data silos across the full chain from requirements, design, code, testing, defects and changes to release; its embedded out-of-the-box compliance templates such as ISO 26262 and ASPICE provide a unified, high-quality compliance entry for the ontology data layer; and relying on architectural capabilities such as the ontology and tool layer and the orchestration and execution layer of the compliance ontology, it deploys compliance scenarios intelligently. This solution can improve review efficiency by 95%, achieve 100% coverage, and move the average problem discovery point forward by 60% — freeing engineers from repetitive compliance review labor, reducing compliance costs and improving product quality. At the same time, the unified data foundation supports multi-standard one-time investment and cross-project reuse, helping enterprises calmly face overseas compliance challenges. PTC is using Codebeamer as the foundation to make compliance leap from a "cost center" to a "competitiveness."
Localized ALM AI Technology Practice
Mr. Liu Zhihao, Director of AI Innovation Strategy at Beijing Soin Technology Co., Ltd.
Mr. Liu Zhihao, Director of AI Innovation Strategy at Beijing Soin Technology Co., Ltd., was invited to attend and delivered the keynote "Localized ALM AI Technology Practice," combining Sointech's localized AI deployment experience on the PTC Codebeamer ALM platform to systematically break down the realistic path for scaled deployment of industrial AI in Chinese engineering scenarios for attending automaker representatives.
Mr. Liu first analyzed the six core challenges PTC's standard Codebeamer AI capabilities face when deployed at Chinese automakers: data compliance requirements, conflicts between cloud architecture and enterprise intranets, generic large models lacking industry and enterprise knowledge, engineering data assets difficult for AI to utilize, difficulties integrating with existing IT systems, and the need for continuous iteration of AI scenarios.
Against these challenges, he introduced the ALM AI localization technology architecture built by Sointech, consisting of three parts: the SOIN ALA intelligent assistant (a natural-language interaction entry for engineering personnel), the SOIN ADS knowledge engine (vectorization and retrieval augmentation of enterprise private knowledge and engineering data), and the SOIN AWE agent workflow engine (multi-agent orchestration and business process integration). The entire solution connects to Codebeamer in a non-intrusive way, supports private deployment on enterprise intranets, ensures engineering data never leaves the domain, and meets classified protection and industry compliance requirements.
On technical implementation, Mr. Liu highlighted five key technical capabilities: localized model inference scheduling, enterprise knowledge augmentation engine, multimodal engineering data processing chain, orchestratable workflows and system integration, and multi-agent collaboration with rapid iteration. He demonstrated on site requirements similarity checking, requirements quality checking and automatic test case generation — actual application scenarios already deployed at automaker customers — intuitively presenting efficiency and quality benefits.
He also shared the short-term deployment and medium/long-term evolution plan of SOIN's ALM AI localization solution: in the short term, quickly entering with high-frequency pain-point scenarios such as requirements quality and test case generation for value validation; in the medium and long term, continuously expanding to more engineering agent scenarios such as compliance review, change impact analysis and cross-system collaboration — helping automakers truly push AI from pilot to scaled business value without sacrificing data security and engineering rigor. Being invited to share SOIN's localized AI practice at the PTC Automotive Industry Elite Summit is recognition by the industry of Sointech's deployment capability in enterprise AI, especially in the automotive and equipment manufacturing ALM/PLM fields. Sointech will continue to cultivate industrial AI and agent engineering, joining hands with ecosystem partners such as PTC to provide Chinese automakers with more secure, more business-aware localized AI capabilities for digital transformation.
Integrated Product Engineering Solution
Ms. Xiao Rong, Senior Solution Consultant at PTC / Mr. Yang Dayu, Principal Solution Consultant at PTC
Ms. Xiao Rong, Senior Solution Consultant at PTC, and Mr. Yang Dayu, Principal Solution Consultant at PTC, jointly presented the Integrated Product Engineering (IPE) solution and deployment practices. The two consultants first introduced the IPE solution under PTC's Intelligent Product Lifecycle (IPL) strategy. Targeting pain points such as fragmented enterprise R&D toolchains, cross-department collaboration breakpoints and insufficient visibility of engineering information, they explained the three-layer architecture of orchestration, collaboration and product data foundation, and introduced several major new capabilities:
- Digital Product Traceability (DPT) relies on the OSLC open standard, using links rather than data copying to eliminate redundancy, achieving cross-system full-chain tracking across tools such as Windchill, Codebeamer and PTC Modeler;
- The Relationship Browser (PRE) visually presents cross-tool object relationships, supporting multi-dimensional filtering and retrieval;
- Task and Change Coordination (TCC) connects PLM and ALM change and task processes, synchronizing status bidirectionally while preserving each system's original workflows;
- The brand-new Ignition product architecture orchestrates systems engineering across tools, connecting mechanical, electronic/electrical and software multi-discipline design, completing the allocation from functions to logical architecture.
They then combined domestic localized deployment practices, sharing the experience of building ALM intelligent applications based on Codebeamer. The upper-layer intelligent applications are all independent APPs, with core data stored inside Codebeamer — no system switching required and a low entry barrier. They also introduced two typical scenarios: full-process ASPICE traceability, which displays full-chain traceability data through V-model visualization, where clicking a node shows related requirements, test cases, software versions and more; and one-stop DevOps integration, which connects tools such as Jenkins and Jira inside Codebeamer, associates requirements with software module dependencies, and shows CI/CD task status in real time, achieving full-process DevOps visibility.
Five AI-Themed Exhibition Booths
In addition, PTC prepared five AI-themed exhibition booths outside the conference room for attendees to have in-depth one-on-one exchanges with technical experts:
Ontology-Based AI Core Architecture: Facing typical AI agent deployment scenarios in manufacturing such as order BOM generation and compliance verification, PTC fuses ontology modeling, knowledge graphs and process orchestration technologies, relying on a localized AI foundation and semantic and rule-based reasoning to ensure the rigor and accuracy of AI output.
AI-Empowered Intelligent Product Design: A showcase of Creo AI intelligent design applications, covering PTC's native Creo AI capabilities, the Skill Market, AI similar-part search and other localized AI applications. Parameterized design skills for gears, shafts and fasteners can quickly complete component modeling; enterprises can also encapsulate their own design templates and process standards, accumulating proprietary engineering knowledge assets. The AI similar-part retrieval agent can perform material standardization analysis, quickly retrieve and reuse existing parts at the design stage, and provide data support for procurement price comparison.
AI-Empowered Software Lifecycle Management: A showcase of AI-empowered automotive software lifecycle management applications — Codebeamer role-based intelligent applications covering the full process of requirements, testing, CI/CD and compliance verification. It supports PDF requirements document parsing and conversion, AI requirements item translation, requirements quality checking based on INCOSE standards, AI automatic test case generation, connection to CI/CD R&D pipelines, and ASPICE compliance verification — supporting automotive software functional safety compliance.
AI-Empowered Digital Product Management: A showcase of Windchill AI applications, including PTC's official native AI capabilities (AI document assistant, similar-part retrieval) and localized AI applications for the automotive industry (intelligent material parsing and selection, AI-agent-driven change impact analysis, automatic order BOM generation, intelligent APQP/DFMEA/PFMEA generation and more).
The AI-Empowered Digital Innovation Journey: Presenting PTC's key exhibits at the 2026 Hannover Messe — an Intelligent Product Lifecycle (IPL) practice for the heavy equipment industry. Through connected, intelligent product lifecycle management, it links requirements engineering, detailed design, product data management, manufacturing and after-sales service, with AI capabilities further releasing full-chain efficiency in requirements assistants, test case generation, generative design, part optimization and duplicate checking, fault capture and analysis, work order summarization and intelligent dialogue.
The PTC China Automotive Industry Elite Summit in Hefei was successfully held. Through this event, automotive industry experts and enterprise representatives gained a deep understanding of the latest trends of enterprise digital transformation in the AI era and the application of PTC's latest product strategy and solutions through full exchanges. We look forward to the next stop of the PTC China Industry Elite Summit bringing more customer experience sharing and technical exchange from different industries.