Disrupt (AI) Summit Agenda

Step into the future of product management with an Iron Man twist! In this session, we will explore how different innovative tools supercharge product development teams worldwide. I will share the agentic AI workflows I use to drive efficiency, spark creativity, and generate game-changing value for companies.

Like Tony Stark’s transformative journey, you will discover how to harness AI to revolutionize your product management approach. This session is designed to inspire, empower, and equip you with actionable strategies to excel as a product manager and builder. Whether you are refining your innovation process or scaling your development efforts, join us and unlock a new era of success in the digital age. Prepare to be challenged, transformed, and ready to lead with the power of AI. Walk away with the mindset and tools to revolutionize your career and drive innovation forward.

Artificial Intelligence isn’t a futuristic concept — it’s here, reshaping businesses operations and the way we work. In this session, we take you behind the scenes of AI in finance, sharing real-world lessons from our journey at XM. From revolutionizing client engagement with AI-powered chatbots to optimizing customer experience, we explore how AI is transforming the brokerage industry and beyond. Deploying AI at scale comes with challenges — from managing hallucinations to balancing cost, speed, and accuracy. We’ll dive into some key insights, pitfalls to avoid, and the trade-offs every company must navigate. Join us as we cut through the hype, uncover the realities of AI adoption, and highlight the strategic choices that will define the future of financial services.

As AI agents evolve, their true power lies not in generalization but in verticalization—tailoring AI to deeply understand and transform industry-specific workflows. In this session, Jacob George Director of Product, Founders Factory will explore how vertical AI agents are reshaping industries by embedding intelligence directly into core operations. Drawing from my work in AI-driven therapy for speech & language disorders (Ogma) and AI-powered insurance claims automation (InsureAI), I will showcase how specialized agents can enhance efficiency, accessibility, and scalability.

From revolutionizing clinical workflows to automating claims processing, vertical AI agents are moving beyond generic automation to domain expertise—augmenting professionals, improving outcomes, and unlocking new economic models. But scaling these agents requires more than just fine-tuned models; it demands robust data pipelines, industry-aligned design, and human-in-the-loop intelligence.

This session will provide a framework for building and deploying vertical AI agents across sectors—demonstrating how AI’s next frontier is not just intelligence, but specialization.

The online betting industry is a steeply growing form of digital entertainment in Greece. Thousands of users  are registering, navigating and playing within a wide variety of betting products.

On the other hand data sets consist the trace of customer journeys and preferences for decision makers who need to deeply understand customer needs in order to launch new products, features or commercial actions.

The explosion of data volume and complexity puts machine learning in the "poll position" for actionable insights delivery, fast and relevant proactive B to C actions and data driven product optimizations.  In that context "real business life" examples are displayed to showcase how  Segmentation Models drive product and promotion relevance, how Propensity Models drive the speed of proactive CRM and how Forecasting Models drive Marketing Investment Mix optimization. 

In this session we will showcase how machine learning has become for OPAP a day to day reality, upgrading constantly the online customer experience.

As development accelerates in the age of AI, traditional approaches to code governance are struggling to keep up. With everything now expressed as code, organizations face growing complexity, fragmentation, and risk. Manual controls and scattered processes no longer scale.

This session advocates for a robust and embedded governance model that fits how modern teams build and ship software. Instead of slowing things down, governance should support fast, secure, and reliable delivery—built into workflows from the start, not bolted on after the fact.

If you're navigating the tension between speed and standards or looking to modernize your governance approach without getting in the way of innovation, this talk offers practical, grounded insights.

This session will explore how Engel & Völkers is - a global real estate brokerage operating in 35 markets - face the challenges of modernizing a large, distributed organization by driving digital transformation across legacy platforms, while simultaneously introducing AI-powered tools to enhance customer satisfaction and organizational efficiency. Learnings will be shared from real-world experience in aligning global product strategy, navigating change management, and delivering measurable value at scale.

Great product management isn’t just about reacting to feedback—it’s about anticipating needs before they’re voiced. As AI capabilities accelerate, the role of the product manager is evolving into one that blends intuition, experimentation, and technical fluency.

In this session, Ioannis Papikas offers a practical deep dive into what it means to lead AI-driven product development in 2025. From gathering the right data and framing the right problems, to running experiments and validating solutions, this is a crash course in building intelligent products that users love—and trust.

What to expect:
1.A walkthrough of the AI product lifecycle—from idea to implementation
2.Techniques for integrating AI into the discovery and validation process
3.Strategies for balancing innovation with usability and impact
4.Tools and mindsets to help PMs lead in fast-moving, high-uncertainty environments

Whether you’re launching your first AI feature or scaling existing capabilities, this session will help you reframe your approach—and lead from a step ahead.

Great product management isn’t just about reacting to feedback—it’s about anticipating needs before they’re voiced. As AI capabilities accelerate, the role of the product manager is evolving into one that blends intuition, experimentation, and technical fluency.

In this session, Ioannis Papikas offers a practical deep dive into what it means to lead AI-driven product development in 2025. From gathering the right data and framing the right problems, to running experiments and validating solutions, this is a crash course in building intelligent products that users love—and trust.

What to expect:
1.A walkthrough of the AI product lifecycle—from idea to implementation
2.Techniques for integrating AI into the discovery and validation process
3.Strategies for balancing innovation with usability and impact
4.Tools and mindsets to help PMs lead in fast-moving, high-uncertainty environments

Whether you’re launching your first AI feature or scaling existing capabilities, this session will help you reframe your approach—and lead from a step ahead.

AI is rewriting the rules of product analytics—turning chaos into clarity. In this session, we’ll explore how AI automates data workflows, ensures trusted insights through smart observability, and unlocks access for all via natural language. The result? Faster decisions, deeper personalization, and product growth driven by intelligence, not guesswork.

The AI boom has unleashed a torrent of possibilities, but turning models and demos into real, user‑trusted solutions remains an uphill battle, especially for organizations not born AI‑first. In this session, I will cut through the noise and share hard‑won lessons on shifting mindsets, choosing the right problems, and steering clear of the traps that derail AI product development. Drawing on personal experience and case studies, I will unpack what it takes to go beyond hype and land on product‑market fit.

Topics include:
AI Mindset Shift for Non‑AI‑Native Companies
Choosing the Right Problems When Tech Outpaces Needs
Avoiding common pitfalls that derail AI product development

Whether you’re defining your first AI use case, rallying cross‑functional teams, or wrestling with the tension between innovation and clarity, this session equips you with the know‑how and real stories to make your AI products stick long after the demo fades.

Despite significant investment, 90% of AI models never see production. Why? Because AI isn’t a product—until you deliberately shape it into one.

Too often, AI initiatives falter because they begin as technical experiments disconnected from clear business goals. Teams frequently build sophisticated models without first articulating a precise problem, securing stakeholder alignment, or establishing metrics to measure genuine impact.

In this interactive session, you'll learn how to transform AI concepts into tangible products that deliver measurable business results. Drawing on real-world case studies from the gaming industry and beyond, we'll outline a proven approach to tackling ambiguous AI requests, utilizing data-driven insights to identify meaningful problems, and ensuring AI features integrate seamlessly with your broader product strategy and KPIs. 

Key takeaways include: 
Practical strategies for shifting from AI experimentation to impactful products 
Methods to define and track AI success metrics that genuinely matter 
Techniques for aligning AI initiatives with overarching product and business objectives 

As AI capabilities evolve, many companies are re-evaluating how to scale internal operations without overburdening their teams. In this session, we’ll explore how Intelligencia AI has approached this challenge within the context of clinical data curation—a process that involves harmonizing more than 1.5 billion data points on a daily basis.

Rather than framing AI as a replacement for human expertise, Intelligencia focused on designing tools and workflows that support and extend the capacity of their Clinical Data Experts. Over the past two years, this has required deliberate choices about which problems to address with AI, how to balance exploratory research with product strategy, and where the use of large language models (LLMs) added value—or fell short.

This session will cover:
1.Decision-making around build vs. don’t-build when it comes to internal AI tools
2.How product and research teams collaborated to stay aligned
3.What worked, what didn’t, and what’s still in progress when it comes to AI integration
4.Reflections on maintaining team wellbeing in the face of scaling demands

The discussion aims to offer a candid look at the practicalities of embedding AI into operational workflows, with lessons applicable to any team navigating similar trade-offs.