Recorded Sessions Library
Watch business and technology-focused sessions from the Configuration Lifecycle Management Summit 2026.
Real-world Cases.
Proven Transformation Journeys.
The 11th edition of CLM Summit 2026 brought leaders from around the globe that created space for sharing knowledge, best case example and how to navigate manufacturing sector in the AI era.
Welcome from the CEO
Explore This Year’s Sessions
Business Day
Keynote – Mastering Customization Complexity: CLM as the Foundation for AI-Driven Growth
Wilhelm Bielert, PhD, CDO & Senior Vice President,
Premier Tech
AI Disruption in Manufacturing
Damantha Boteju, Chief Product and Technology Officer, CPTO,
Configit
One Configuration Truth – CNH’s CLM approach for Scalable Customization and Servitization
Alberto Russo, IT Project Manager,
CNH
From Customization to Resilience: Building an End-to-End Digital Thread with CLM
Rüdiger Stern, Managing Director,
Accenture Industry X
Building a Scalable Configuration Backbone – The Vestas Approach
Peter à Porta, Product Owner Configuration Management Systems,
Vestas
Driving Global Consistency and Speed with CLM: Sidel’s Quoting Transformation
Andrea Pancirolli, Director of the Equipment Quotation Transformation Project,
Sidel
Panel Discussion – Navigating AI Disruption in Manufacturing: the Path to Success
Moderator: Damantha Boteju, Chief Product and Technology Officer, CPTO, Configit
Panelists: Premier Tech, Vestas, PTC, Accenture
Technology Day
Keynote – From Variant Complexity to Lifecycle Control: CLM in Regulated MedTech
Rene Zoelfl, Senior Director, Global Industry Advisor MedTech,
PTC
CLM + PLM: Creating a Reliable Foundation for Digital Threads and Agentic AI
Sigrún Ívarsdóttir, Product Manager,
Configit
Deloitte’s Case Study on Managing Customization Complexity
Thomas Kaufmann, Senior Manager,
Deloitte Consulting
Ace Prompt: Leveraging Gen-AI with Determinism
Laura Beckwith, PhD, Director of Product Management,
Configit
CLM as the Backbone of Software-Defined Product Lifecycles
Marcus Krastel, PhD, Managing Director,
Engineering Methods AG
Profitable Customization at Scale with CTO and Partial ETO
Henrik Hulgaard, PhD, VP Product Management and Co-founder,
Configit
Delivering Great Customer Experiences for Configurable Products
David Nedergaard, Product Manager,
Configit
Questions & Answers from the Live Event
What are the costs and ROI considerations of investing in AI for PLM and CLM systems?
AI investments should be evaluated like any other business initiative, with a focus on tangible value creation. While the industry is still in the early stages, organizations are already seeing significant productivity improvements through targeted use cases. Examples include AI-assisted robot programming, where algorithms can handle 50–70% of the work before human validation, and engineering copilots that can substantially increase engineer productivity. Case studies commonly indicate efficiency gains in the range of 20–40% through better data structuring and the use of existing AI tools. ROI will vary by organization and use case, but measurable time savings and productivity improvements are already emerging.
Wilhelm Bielert, PhD, CDO & Senior Vice President, Premier Tech
What AI-related initiatives is Configit currently exploring?
Configit is focused on helping organizations safely adopt AI within Configuration Lifecycle Management (CLM). A key area of development is creating a trusted layer around AI systems that helps prevent hallucinations and incorrect recommendations. Configit aims to leverage its strengths in logic and configuration management to provide rapid integration capabilities and reliable responses for AI-driven systems. The vision is to act as an "air traffic control system" or "prefrontal cortex" for AI agents, ensuring decisions remain grounded in validated logic and rules.
Damantha Boteju, Chief Product and Technology Officer, CPTO, Configit
What data is extracted from SAP during a CLM implementation?
In the example discussed, product master data and rules are initially defined within PLM systems and then transferred to SAP, where configuration data is managed through SAP Variant Configuration. The implementation extracts tables containing rules, commercial descriptions, market-specific information, product details, and pricing data. Configit Extractor reads this information, translates it into rule syntax, compiles the rules, and generates configuration packages that are consumed by configurator libraries.
Alberto Russo, IT Project Manager, CNH
What are the biggest barriers to adopting a CLM approach?
Three primary barriers are commonly observed:
1. Legacy systems and data quality challenges – Organizations often struggle with disconnected systems, unclear data ownership, and inconsistent data quality.
2. Organizational change management – CLM is a strategic capability that requires new ways of working and cross-functional alignment.
3. Business case development – Many organizations fail to clearly quantify the financial value of CLM initiatives before starting.
Successful adoption typically requires assessing the current state, defining a future vision, building a value-based roadmap, and ensuring every implementation phase delivers measurable business benefits.
1. Legacy systems and data quality challenges – Organizations often struggle with disconnected systems, unclear data ownership, and inconsistent data quality.
2. Organizational change management – CLM is a strategic capability that requires new ways of working and cross-functional alignment.
3. Business case development – Many organizations fail to clearly quantify the financial value of CLM initiatives before starting.
Successful adoption typically requires assessing the current state, defining a future vision, building a value-based roadmap, and ensuring every implementation phase delivers measurable business benefits.
Rüdiger Stern, Managing Director, Accenture Industry X
Do you maintain the Global Characteristic Definition (GCD) directly in Configit Ace® or another application?
In the example shared, the GCD is maintained directly within SAP. While the characteristic definitions could technically be managed in different systems, SAP was selected because it aligned best with the organization's governance and business requirements. Other systems receive only the subset of characteristic information they need, while SAP remains the master source for the complete definition.
Peter à Porta, Product Owner Configuration Management Systems, Vestas
Are any ISO or IEC standards used to define the characteristic classification model?
No specific ISO or IEC standards were used. Instead, the classification approach was developed pragmatically based on the capabilities and governance requirements the business needed to achieve. The classification framework can be expanded over time if future business needs require additional structure or categorization.
Peter à Porta, Product Owner Configuration Management Systems, Vestas
How does the GCD relate to configured variants and variant reuse?
The GCD serves as the definition repository for individual characteristics but does not define how those characteristics are combined into configurable products. When characteristics are transferred into systems such as Windchill, they are organized into option sets that govern product configurability. Sales configurations are then based on the design content available at that point in time. Characteristics are retained throughout their lifecycle to support both current and historical product configurations, with lifecycle controls indicating whether a characteristic remains active for future use.
Peter à Porta, Product Owner Configuration Management Systems, Vestas
What benefits have organizations achieved by controlling product complexity?
Managing complexity through a configuration model helps ensure that the right level of expertise is involved at the right stage of the process. Simple configurations can be handled automatically through front-end tools, while more complex configurations can trigger expert involvement when validation or technical guidance is required. This approach allows organizations to manage complexity proactively, improve efficiency, and ensure resources are applied where they add the most value.
Andrea Pancirolli, Director of the Equipment Quotation Transformation Project, Sidel
What AI initiatives is PTC currently pursuing within its PLM portfolio?
PTC has adopted an AI strategy based on the framework "Assist, Advise, and Automate." While AI has been part of PTC solutions for some time, two notable AI capabilities have recently been introduced within the Windchill PLM environment. The first helps organizations identify duplicate parts and drive parts rationalization, reducing complexity and improving efficiency across the value chain. The second is a Copilot agent that enables users to better understand and navigate data stored within Windchill by generating document summaries and revealing relationships between information. Additional AI capabilities are planned for release over the coming months.
Rene Zoelfl, Senior Director, Global Industry Advisor MedTech, PTC
Should technical configuration and commercial configuration remain separate?
A degree of separation is beneficial because engineering teams focus primarily on technical feasibility, while sales teams concentrate on market opportunities, customer needs, and revenue generation. However, these disciplines should not operate in isolation. Maintaining strong connections between technical and commercial configuration helps organizations reduce risk, improve efficiency, and ensure alignment throughout the product lifecycle.
Rene Zoelfl, Senior Director, Global Industry Advisor MedTech, PTC
The custom application demonstrated how organizations can align engineering intent from PLM systems such as PTC Windchill with commercial intent from ERP systems and bring that information into Configit Ace®.
How was this application built?
The application was built using rich public APIs combined with AI-assisted development techniques. AI was used to accelerate the creation of the solution, while the flexibility of the underlying APIs enabled rapid integration and customization. This reflects a broader strategy of making APIs increasingly AI-ready, allowing organizations to use generative AI tools to build applications faster and more efficiently on top of existing platforms.
Sigrún Ívarsdóttir, Product Manager, Configit
What are the benefits of taking a cross-functional approach from the beginning of a configuration transformation rather than optimizing individual departments in isolation?
The primary benefit of taking a cross-functional approach from the outset is the establishment of a shared vision across all stakeholders before implementing individual systems. Instead of allowing sales, engineering, marketing, and other functions to define requirements independently, organizations can align on common use cases, processes, and objectives upfront. This alignment enables the creation of a consistent data foundation that supports end-to-end configuration processes across the business, helping to improve collaboration, reduce inefficiencies, and ensure a more reliable transformation outcome.
Thomas Kaufmann, Senior Manager, Deloitte Consulting
How can organizations better manage the gap between sales and engineering when engineering work is outsourced to suppliers?
There are two critical aspects. First, organizations must establish effective collaboration with suppliers by clearly defining requirements and agreeing on what configuration data needs to be exchanged throughout the lifecycle. Second, when supplier data is received, it must be documented and validated consistently. This requires clear rule definitions, common standards, or automated translation mechanisms that can interpret different rule formats. Configuration Lifecycle Management (CLM) helps address this challenge by enabling organizations to compare supplier-provided rules against their own configuration models and verify that the delivered solution aligns with what is being sold.
Thomas Kaufmann, Senior Manager, Deloitte Consulting
How does Ace Prompt differ from using a general-purpose GenAI tool such as ChatGPT?
While general-purpose AI tools can assist with product modeling, they lack the domain-specific knowledge and best practices that Configit has developed over more than 25 years. Ace Prompt incorporates expertise on how to build effective product models, including guidance on structuring families, creating sub-models, and applying proven modeling practices. In addition, customers have reported that Ace Prompt performs particularly well when extracting and interpreting information from images and PDFs. This advantage comes from combining generative AI capabilities with specialized configuration knowledge and purpose-built tooling that guides the AI toward better outcomes.
Laura Beckwith, PhD, Director of Product Management, Configit
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