TechEx Learning Hub Europe

This workshop presents the frameworks, methods, and lessons the Digital Twin Consortium has developed moving digital twins from concept to operational deployment.

The session traces the Digital Twin evolution to understand how composable digital twins architected from required capabilities, and extended to AI-enabled twins through use of generative AI and autonomous agents.

DTC’s main initiatives covered in the workshop include the  the Digital Twin Maturity Model, the Digital Twin and  AI Agent Capabilities Periodic Tables, the Platform Stack Reference Architectural Framework comprising an overall composability framework. 

The first segment addresses how to compose. Using the DTC Composability Framework attendees develop a tailored capabilities-first method: defining  specific use case requirements with the Digital Twin Capabilities Periodic Table (CPT) across its six categories: Data Services, Integration, Intelligence, User Experience, Management, and Trustworthiness and then map those requirements onto the platform stack.

The second segment addresses where generative AI can bring added value:

Attendees learn to use the two periodic tables together in a dual development flow— the Digital Twin CPT to identify the capabilities of the twin, and the AI Agent Capabilities Periodic Table (AIA CPT) to identify the capabilities that bring added value through automation..

The final segment addresses trusted AI agents for production deployment: applying the Trustworthiness capability category — security, privacy, safety, reliability, and resilience, and the AI Agent Governance and Safety Capabilities, including defining the evidence required to show adherence to the ten laws of the AI Agent Manifesto.

A facilitated discussion closes the workshop, where attendees select use cases and share workshop results in discussion including alignment to the collaborative work of DTC working groups and mapping to the Digital Twin System (DTS).

Attaendees leave with a practical method: capability-based requirements for the twin, capability-based requirements for the agents, and evidence required.

Enterprise AR can transform task guidance, inspection, remote support, training and knowledge sharing, but scaling beyond successful pilots remains a challenge.

This workshop helps participants identify high-value AR opportunities, build a practical use case, develop a credible ROI business case and plan for successful adoption. Using real-world examples, participants will explore where AR delivers measurable operational value and how to overcome technical, organisational and workforce barriers.

Participants leave with a prioritised AR use case, an initial business case and a practical implementation roadmap.

Interactive and Hands-On Elements

1. AR Use-Case Development

Working in groups, participants apply a structured framework to a real business challenge by:

• Defining the process, users and key pain points
• Identifying where AR adds the greatest value
• Selecting the most appropriate AR approach
• Defining technical requirements and pilot success metrics

Each group produces a prioritised AR use-case canvas.

2. Building the ROI Business Case

Participants create an evidence-based business case by assessing:

• Current costs, time and error rates
• Expected productivity, quality and training improvements
• Implementation costs and pilot KPIs

They will identify the data required to validate ROI before and after deployment.

3. Overcoming Adoption Barriers

Using an adoption-readiness framework, participants assess challenges including leadership support, user adoption, usability, IT integration, security and skills, before developing mitigation plans using the SIMPLE framework.

The workshop concludes with peer feedback on each group’s use case, ROI and implementation strategy.

AI is creating new possibilities for organizations, but competitive advantage comes from the ability to translate AI investments into strategic outcomes and measurable business results. Many are defining AI use cases and launching pilots, yet are seeking to better understand how these investments can collectively advance the organization’s strategy and deliver tangible business value.

In this interactive workshop, participants learn a practical approach, supported by a proven strategy to execution framework, to create a clear line of sight from business strategy through capabilities to AI initiatives, enabling alignment and optimization of AI investments.

Through facilitated discussion, peer exchange, and live input, participants explore strategy to execution as an organizational capability, discuss key challenges and opportunities, and examine how leading organizations leverage capability-driven thinking to enable more coherent enterprise action.

Participants then apply the golden thread within the strategy to execution approach to their own context, identifying which AI initiatives to prioritize, where duplication or gaps exist, and how to better align investments with business strategy. We reinforce this with a practical example worked through together.

The session concludes with a set of practical next steps and tools to support immediate application within participants’ organizations.

With open source present in 96% of commercial products and accounting for 75% of global code, the Cyber Resilience Act (CRA) creates a new reality by holding manufacturers accountable for every component. This session explores how organizations can demonstrate compliance in this evolving landscape.

Grounded in work by the Eclipse Foundation’s Open Regulatory Compliance (ORC) Community, the training translates core requirements, such as SBOMs, risk assessments, voluntary security attestations, vulnerability management, and due diligence, into clear, practical terms. Participants will learn how the CRA impacts open source usage and gain actionable strategies to continue leveraging open source effectively and compliantly.

Key Learning Outcomes

● Distinguishing CRA roles and scope: Gain clarity on how regulatory responsibilities are distributed among open source stewards, projects, and commercial manufacturers.
● Essential technical foundations: Explore the critical functions of Software Bill of Materials (SBOMs), rigorous due diligence, and maintaining supply chain integrity.
● Security by design principles: Understand the practical application of secure development lifecycle standards within the open source ecosystem to mitigate risk.
● Executing primary CRA mandates: Discover how to manage vulnerability handling and due diligence through real-world scenarios, focusing on the consumption of upstream projects.

AI will not replace you. The person who knows how to use it will.

This interactive workshop turns that uncomfortable idea into a practical exercise. Participants start by breaking their own role down into its real components: decisions, judgement, relationships, repetitive execution, knowledge retrieval. They then score each component against a simple replaceability matrix and see, in their own handwriting, which parts of their job an AI system can already absorb and which parts only they can hold.

The second half is about what to do with that picture. Working in small groups, participants redesign one process from their daily work: what to delegate to AI, what to keep under human judgement, and where the handover between the two actually happens. We close with an open discussion on what these choices mean for teams, hiring and leadership over the next two years, grounded in what the analyst data is actually showing about adoption.

Everyone leaves with a completed personal matrix and one concrete redesigned workflow they can apply the following Monday. No slideware, no hype, no vendor pitch.