WeAreDevelopers Logo WeAreDevelopers
Sign in
For You LIVE
World Congress 2026 Europe - Virtual Stage • Jul 2, 2026 • Session details

AI in Regulated Industry - Validating AI-Enabled Products with PLM and Digital Twins

Murli Mohan Srinivas

In regulated industries, unexplained AI is just a confident guess. Discover how integrating PLM and digital twins makes probabilistic models safe, traceable, and fully certifiable.

Pause
Mute Enter Fullscreen
#1 about 2 min

Explainability requirements for AI in regulated industries

Using AI in high-stakes fields requires convincing regulators that decisions are safe, traceable, and explainable.

#2 about 4 min

Validating probabilistic AI behaviors in high-stakes environments

Unpredictable and adaptive AI models require rigorous end-to-end traceability across defense and medical applications.

#3 about 3 min

Overcoming validation gaps in traditional engineering models

Complex product lifecycles require moving validation from a late-stage activity to a continuous closed-loop process.

#4 about 4 min

Shifting to smart validation for probabilistic AI models

Because AI systems are probabilistic and prone to edge-case failures, static testing must be replaced by continuous simulation.

#5 about 4 min

Treating AI models as regulated product artifacts

Embedding AI data and pipelines into a closed-loop product lifecycle management system ensures auditable and governable behavior.

#6 about 3 min

Simulating edge cases using digital twin technology

Digital twins allow teams to test rare failures and edge cases continuously before models hit production.

#7 about 2 min

Maintaining human oversight for responsible AI automation

Capturing traceable human decisions within the validation loop guarantees that automated processes remain supervised and compliant.

#8 about 4 min

Implementing an architecture blueprint for continuous validation

A four-layer architecture combining governance, digital twins, runtime monitoring, and human control enables an auditable AI system.

#9 about 3 min

Securing innovation through traceability and continuous validation

Success with AI in regulated environments depends on treating models as components and closing the validation loop.

Matching moments

3:08 min

Managing the impact of AI on software trust

Serge Baumberger Serge Baumberger · Europe 2026 Virtual

4:37 min

Strengthening cross-functional controls and risk management

Seppe Housen Seppe Housen · Europe 2026 Virtual

3:32 min

Transitioning toward a trustworthy AI development life cycle

Matteo Meucci Matteo Meucci · Europe 2026 Virtual

3:20 min

Bridging constraints between product management and software engineering

Alexandre Guenoun Alexandre Guenoun +3 · World Congress 2026 Europe

1:40 min

Addressing data sovereignty and compliance blind spots within AI

Sebastian Kister Sebastian Kister · World Congress 2026 Europe

2:17 min

Overcoming integration challenges in regulated industry AI deployments

Benedikt Höck Benedikt Höck +3 · World Congress 2026 Europe

More from World Congress 2026 Europe - Virtual Stage

One Does Not Simply Make Architecture Decisions Alone thumbnail
36:15
30 days ago

One Does Not Simply Make Architecture Decisions Alone

Vladas Diržys

From Black Box to Glass Box : Bedrock AgentCore Observability thumbnail
21:15
about 1 month ago

From Black Box to Glass Box : Bedrock AgentCore Observability

Yasemin Aktürk

Leading in Rhythm: How Women Make Better Decisions with Biological Intelligence thumbnail
30:41
about 1 month ago

Leading in Rhythm: How Women Make Better Decisions with Biological Intelligence

Julia Grosse

Better Together: Leveraging Your Observability Tools as a SIEM thumbnail
39:06
about 1 month ago

Better Together: Leveraging Your Observability Tools as a SIEM

Mathias Palmersheim

ChatGPT Apps: From Chat to Checkout thumbnail
30:29
about 1 month ago

ChatGPT Apps: From Chat to Checkout

Aaron Koivunen

Interior Decorating (TypeScript Decorators) thumbnail
29:22
about 1 month ago

Interior Decorating (TypeScript Decorators)

Michael Dowden

Upcoming sessions on this topic

Open session

World Congress 2026 North America

Who Tests the AI? Building Trustworthy AI Systems at Enterprise Scale

Him Raj Singh

PayPal, Manager, Software Engineer

Him Raj Singh
Open session

World Congress 2026 North America

Beyond the Code: Human-AI Synergies in Product Development

Ajita Kanchivakam Ananth

Staff Technical Program Manager at Google

Ajita Kanchivakam Ananth
Open session

World Congress 2026 North America

Reinventing Testing Practices in the AI Era

Eric Deandrea

Java Champion & Senior Principal Software Engineer, IBM

Eric Deandrea
Open session

World Congress 2026 North America

AI Decision Observability: Enabling Transparency and Trust in Intelligent Systems

Amjad Shaikh, Soumil Mandal

Amjad Shaikh
Soumil Mandal
Open session

World Congress 2026 North America

AI ROI: The Hard Unit Economics of AI-Native Engineering

Manu Gurudatha

Manu Gurudatha, VP of Engineering at PagerDuty

Manu Gurudatha
Open session

World Congress 2026 North America

You Can’t Re-Run Sunlight: Designing ML Data Architectures for Physical AI

An Phan

Senior Data Infrastructure Engineer @ Hippo Harvest

An Phan

Related videos

AI in High-Stakes Industries: Lessons Learned thumbnail
31:27
World Congress 2026 Europe • about 1 month ago

AI in High-Stakes Industries: Lessons Learned

Alexandre Guenoun, Jaipal Singh, Nicolò Robba, Tomislav Tipurić

Introduction to Responsible AI: Balancing Value and Risk thumbnail
31:21
Europe 2026 Virtual • about 1 month ago

Introduction to Responsible AI: Balancing Value and Risk

Seppe Housen

Building Products in the era of GenAI thumbnail
59:39
LIVE • over 2 years ago

Building Products in the era of GenAI

Julian Joseph

Running AI at Scale: The Secret Ingredients thumbnail
30:04
World Congress 2026 Europe • about 1 month ago

Running AI at Scale: The Secret Ingredients

Boris Hecker, Max Tschochohei, Peter Kürpick, Tomislav Tipurić

Building Trustworthy AI in Industry: Beyond Traditional Cybersecurity thumbnail
25:50
Europe 2026 Virtual • about 1 month ago

Building Trustworthy AI in Industry: Beyond Traditional Cybersecurity

Matteo Meucci

The Limits of LLMs in Real-World Applications thumbnail
31:07
World Congress 2026 Europe • about 1 month ago

The Limits of LLMs in Real-World Applications

Deivids Vilkinsons, Guillaume Esnou, Laura Moritz, Mariam Hakobyan

Related articles

From learning to earning

Jobs that call for the skills explored in this talk.