Conference Day 2, Friday, 5 December 2025

• This workshop provides an overview of AI Foundry and Co-Pilot capabilities, demonstrating

how these tools support the development and orchestration of agentic AI systems through

practical, hands-on examples.

• Demonstrates core features of AI Foundry for scalable AI model development and

deployment, enabling autonomous agent behavior in complex workflows.

• Explores Co-Pilot integration to enhance developer productivity with AI-assisted coding

and automation, facilitating multi-agent collaboration and decision-making.

• Walks participants through real-world scenarios showcasing AI Foundry and Co-Pilot in

action, highlighting their role in building and managing agentic AI systems.

Pooja Bhatia

Data & AI Cloud Solution Architect
Microsoft

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• Definition of intelligence and decision-making in the context of AI, questioning the

assumption that more data automatically leads to better outcomes

• Application of agentic systems to augment human creativity, enable adaptive operations,

and support long-term innovation across sectors.

• Assessment of AI’s broader impact on society, governance, and human agency over the

coming decades, including ethical and economic implications

Daniel Hulme

Chief AI Officer
WPP

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• Redefining the Production Pipeline - How AI compressed our workflows and enabled new forms of storytelling.

• Building AI Literacy in Creative Teams - Practical strategies for upskilling traditional media professionals and overcoming resistance in established broadcast environments

• Ethical AI - Implementing transparent AI usage policies, ensuring data privacy compliance, and maintaining trust with audience and regulators • Measuring Success Beyond Efficiency - KPIs for AI transformation in public service media: audience engagement, creative satisfaction, and long-term sustainability metrics

Calle Gisselsson

Exekutiv producent / Projektledare
SVT (Sveriges Television AB)

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• Exploring fundamental technical aspects of AI agents, including core capabilities and

architectures enabling agentic behavior.

• Discussing multi-agent systems with collaborative and competitive AI agents pursuing

shared objectives, and their superior use cases.

• Highlighting challenges in deploying multi-agent systems, such as error amplification and

suboptimal system behavior, and implications for business users.

Bogdan Pirvu

Head of Data & Analytics
Novomatic AG

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• How autonomous agents are being integrated into engineering workflows across the

product lifecycle, supply-chain, purchasing and manufacturing operations.

• Use cases for AI in product life cycle (PLM) systems and within design teams.

• Breaking silos in manufacturing and using agents to unite the path from design phase to

final customer experience

Haydar Vural

Chief Digital Officer (Cdo)
Karsan

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• How a global organization transitioned from a centralized AI unit to a federated model, redefining roles and responsibilities across business functions

• Lessons learned from building a cross-functional AI culture — from AI product owners and prompt engineers to data domain stewards

• Practical insights into business-user enablement, governance balance, and training programs that make AI adoption sustainable and scalable

• Insights into how new team structures align with regulatory expectations and support

scalable, cross-functional AI deployment.

Jose Ramon Reboredo Mera

Head Data Analytics & AI
Grupo Pinero

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• Leveraging GenAI not only for descriptive outputs, but combining it with predictive and prescriptive analytics to generate actionable insights.

• Tackling the complexity of targeting diverse data foundations across multiple business units, balancing scalability with quality.

• Lessons learned from Sanofi Consumer Healthcare’s journey, including successes, mistakes, and next steps in moving from experimentation to enterprise adoption.

Jordi Escayola

Global Head Advanced Analytics, Artificial Intelligence & Data Science
Sanofi

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• Showcasing real-world applications of agentic AI across automotive, pharma, finance, and insurance sectors.

• Examining how enterprises structure secure, compliant multi-agent systems using frameworks like Semantic Kernel and Autogen.

• Reviewing evaluation strategies for GenAI quality and responsible AI design under evolving regulatory expectations.

• Connecting LLM-powered agents to internal systems through APIs to automate tasks across domains such as customer service, compliance, and operations.

• Introduction of middleware strategies, API wrappers, and lightweight orchestration layers to ensure robust and secure AI-to-system interactions.

• Governance and team enablement challenges in exposing enterprise functionality to GenAI tools while maintaining control and compliance.

• How GenAI transformed our R&D Risk and knowledge

management by introducing our R&D chatbot “nexi”

• A solution built for 120 R&D specialists iand its integration into

a global IT AI strategy for a >10.000 employee company.

• Lessons learned and how we are approaching challenges

like organizational boundaries, resource and competence

constraints, accuracy, relevance, hallucination, speed, AI

adoption in the teams and balancing the AI hype within the

company

Ulrike Petrusch

Project Manager
Nexperia Germany Gmbh

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• Showcasing Knight Frank’s journey in scaling agentic AI to transform real estate intelligence workflows, with examples from research summarization to brochure data extraction.

• Outlining the path from proof-of-concept to production: identifying client needs, iterative prototyping, user evaluation, and readiness testing.

• Highlighting governance, ethical considerations, and how agents add value across backend automation and clientfacing interactions.

Nikos Papapesios

Associate, Head of Innovation Analytics
Knight Frank LLP

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