Pre-Conference Day

With AI adoption accelerating, software leaders are moving beyond experimentation and focusing on where AI can deliver measurable value across the development lifecycle. This interactive workshop will bring together industry practitioners to explore how leading organisations are deploying AI to streamline documentation, enhance testing, improve development efficiency, and support compliance activities; while maintaining the oversight, governance and quality standards required in regulated environments.

Join this session to:

• Leverage AI to automate documentation, requirements management and software development activities to reduce manual effort, improve efficiency and accelerate quality and regulatory workflows across the product lifecycle
• Drive workforce adoption through effective change management and stakeholder engagement by overcoming skepticism, managing expectations and helping employees transition from viewing AI as a one-shot solution to a collaborative tool that enhances decision-making
• Scale AI safely across the organisation through governance, security and operating frameworks, aligning with IT and compliance teams, selecting approved tools and maintaining flexibility without compromising data protection or regulatory obligations

As AI moves from experimentation to deployment, MedTech organisations face growing pressure to ensure AI-generated outputs are reliable, explainable and fit for purpose. While AI promises significant improvements in efficiency and decision-making, many software, quality and regulatory leaders are still grappling with how to validate AI systems, define appropriate oversight, measure success and justify continued investment. This interactive workshop will bring together industry leaders to explore practical frameworks for building trust in AI, balancing innovation with accountability, and creating the evidence needed to support adoption at scale.

Industry experts will cover:

• Anticipating evolving AI regulatory expectations to make better development decisions today by identifying common principles emerging across the AI Act, MDR and global regulatory frameworks
• Translating broad AI concepts into practical requirements for medical devices through interpreting expectations around transparency, human oversight and ML systems for real-world MedTech products rather than generic chatbot-focused guidance
• Developing pragmatic strategies for global compliance and risk management by documenting regulatory rationale, sharing best practices, engaging with authorities and aligning compliance activities with both company values and future worldwide market access objectives