Focus Day, Tuesday, 3 December 2025

• Proof-of-concept using a multi-agent architecture to replicate the internal decision

dynamics of a marketing department

• Agents work together using signals from traditional ML models (e.g. churn prediction,

personalization) to coordinate budgets, campaign strategies, and actions

• A hybrid system where humans remain in the loop to validate and approve outcomes,

reducing planning cycles from days to hours

Sabato Leo

Director of AI, Data Science and Research and Development
Tipico

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• How Personalization is Reshaping Customer Journeys

• Make sure you think with the customer in mind

• Don´t end up having a fragmented solution

• Defining agentic AI-powered data products that dynamically support personalised

customer experiences.

• Exploring how autonomous data products enable real-time customer engagement,

satisfaction, and loyalty through adaptive interactions.

• Presenting case studies demonstrating the impact of agentic AI data products in driving

successful personalisation outcomes.

Reserved for one of our business partners

• Personal AI generally refers to AI systems that are designed specifically for an individual,

learning from their unique data and behaviors

• How enterprises are combining traditional ML-based personalization signals with GenAI

agents to orchestrate dynamic, goal-driven marketing and customer engagement

workflows

• Practical challenges in deploying agentic systems—from data integration and model

oversight to aligning agent actions with brand, compliance, and campaign strategy

• The evolving role of AI teams, marketing leaders, and human reviewers in co-piloting

agentic workflows that accelerate planning, content creation, and decision cycles

• Exploring Telefónica’s use of generative AI to enhance customer-facing virtual assistant 

Aura for more natural, flexible dialogues.

• Addressing challenges of hallucination, data privacy, and latency in deploying generative

AI in customer service.

• Highlighting ongoing efforts to advance from deterministic bots to agentic AI systems

capable of dynamic reasoning and personalized responses.

Tina Rahman

Chief Product Owner Conversational AI (Voice and Chatbots)
Telefonica

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• Aligning operational and commercial strategies to enable agile, scalable personalisation

that delivers measurable ROI within stringent regulatory frameworks

• How to measure the success?

• Demonstrating ROI and ongoing optimization of GenAI tools

• Connect AI with KPIs

• llustrate how generative AI and proprietary systems support dynamic pricing and

personalized offers in the used car market.

• Outline the orchestration of hyperpersonalized campaigns across digital channels using

internal and external tooling.

• Examine the data infrastructure, governance practices, and organizational enablers

needed to scale AI-driven personalization.

• Implementation of GenAI-driven personalization engines to dynamically tailor content,

promotions, and product recommendations across customer touchpoints.

• Integration of real-time behavioral data with customer profiles to trigger individualized

experiences in web, mobile, and email channels.

• Approach to safely scaling personalization in retail environments, balancing privacy,

performance, and brand control.

• Use of GenAI platforms to dynamically generate marketing copy, product

recommendations, and branded messages tailored to audience segments or individual

profiles.

• Integration of model outputs with email automation, web personalization engines, and

CRM systems for real-time campaign adaptation.

• Frameworks for human-in-the-loop review, tone-of-voice alignment, and brand safety in

high-scale content generation environments.

• Aligning operational and commercial strategies to enable agile, scalable personalisation

that delivers measurable ROI within stringent regulatory frameworks.

• Leveraging first-party data responsibly with privacy-by-design approaches to power

compliant and effective personalisation initiatives.

• Building future-proof technical architectures that combine advanced analytics, AI,

and machine learning to deliver secure, adaptive, and scalable personalised customer

experiences.

• In this immersive 2.5-hour workshop, participants will learn how to shift from traditional

UI/UX paradigms to a conversation-first design approach for AI-powered assistants. Using

real-world case studies and guided collaboration, attendees will explore how to structure

user-agent interactions that are natural, scalable, and production-ready.

• Understand the foundations of conversation design and why it is essential for building

effective AI-driven customer experiences.

• Practice mapping realistic conversation flows to surface business requirements and

define necessary backend functions.

• Prototype assistant behavior using fake data and prompt engineering before involving

development teams.

• Explore how to design multilingual, dynamic, and accessible AI agents that adapt across

contexts and customer needs.

Emily Stretton

Growth Executive
Holiday Extras

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Sarah Page

Innovation & AI Lead
Holiday Extras

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