Agenda October 14-15,2025

Welcome to the Disrupt Lead AI Forum 2025! In this energizing opening session, George Nikolaropoulos and Ioannis Papikas set the stage for an exciting journey—where leaders, innovators, and changemakers unite to shape how AI will redefine the future of business.

AI is no longer just a tool—it’s a strategic force that’s redefining how organizations create value. This session brings together leading Greek board members, CEOs, and AI strategists to explore how corporate governance must evolve in the face of rapid AI transformation. The discussion will focus on how boards can lead responsibly, align AI with long-term goals, and ensure their companies remain competitive and ethical in a fast-changing world.

Too often, AI enters product roadmaps as a checkbox for innovation rather than a driver of meaningful value. This session reframes AI adoption through the lens of product management strategy: starting from business cases, grounding in discovery, and measuring outcomes. We’ll look at the risks of hype-driven implementation, and instead propose methods to identify AI use cases that strengthen your competitive edge and deliver tangible results. Participants will gain a toolkit to critically evaluate AI’s role in their strategy and to lead AI discussions with clarity and confidence.

Discover cutting-edge AI solutions in action. This session offers sponsors the opportunity to showcase their products, demonstrating real-world applications and the value they bring to businesses and leaders. Attendees will gain insights into innovative tools, practical use cases, and the tangible impact these technologies can have when integrated into strategy and operations.

Discover cutting-edge AI solutions in action. This session offers sponsors the opportunity to showcase their products, demonstrating real-world applications and the value they bring to businesses and leaders. Attendees will gain insights into innovative tools, practical use cases, and the tangible impact these technologies can have when integrated into strategy and operations.

AI has moved from the realm of experimentation to becoming a core enabler of business transformation. This session will explore how Greek enterprises are translating AI strategies into tangible outcomes—reshaping operations, customer experience, and decision-making. Leaders who are driving AI adoption within their organizations will share insights on bridging the gap between ambition and implementation, overcoming internal resistance, and building sustainable, data-driven cultures.

This keynote explores the multifaceted role of leadership in the age of Generative AI (GenAI). It highlights how executives can move beyond tool adoption to actively shape the future of their organizations and industries. Leaders are called to act as visionaries and architects of transformation, balancing innovation with responsibility.

The session will unpack five critical dimensions of GenAI leadership:


1.Understanding — Developing a clear, grounded view of GenAI’s real strengths and boundaries.
2.Shaping Strategy — Reimagining business models, accelerating growth, and cultivating long-term competitive advantage through AI.
3. Building Trust — Embedding ethics, fairness, and transparency into every stage of AI adoption.
4.Protecting Foundations — Safeguarding data, privacy, and compliance as essential cornerstones of sustainable progress.
5.Empowering People — Creating the culture, skills, and structures that enable teams to thrive in the GenAI era.

By weaving these dimensions together, the keynote positions leaders not as passive adopters but as active stewards who define how AI transforms organizations and society at large.

The integration of agentic AI into science discovery and engineering is poised to redefine workflows, accelerating innovation through autonomous reasoning, adaptive experimentation, and interdisciplinary synthesis. Unlike traditional AI models that passively assist with data processing, agentic AI actively formulates hypotheses, designs experiments, and refines methodologies in real time. This paradigm shift enables dynamic collaboration between AI systems and human experts, fostering breakthroughs in areas such as materials science, drug discovery, and sustainable engineering. Future workflows will leverage self-directed AI agents capable of navigating vast datasets, identifying novel patterns, and optimizing complex simulations—significantly reducing the time between theoretical conception and practical application. By integrating principles from neuroplasticity-inspired frameworks and reversible computing, agentic AI will enhance efficiency while minimizing computational waste. Moreover, its ability to maintain ethical alignment and adaptability ensures responsible deployment across critical sectors. As agentic AI evolves, it will not only streamline problem-solving but also unlock new frontiers in scientific reasoning, driving human-centric advancements that balance precision, sustainability, and ethical integrity in the next era of discovery.

As organizations embed AI into critical systems, a fundamental question arises: Who owns AI accountability? This panel addresses the shift from ad-hoc or siloed oversight models to a deliberate, organization-wide governance framework, where responsibility for ethical, safe, and transparent AI is clearly distributed across business functions.

Participants will explore how leading enterprises are designing cross-functional AI governance structures that scale with complexity and risk. From legal and technical teams to product and ethics advisors, the session highlights what true accountability looks like at the enterprise level—and how to operationalize it.

Many enterprises face significant challenges when attempting to integrate AI into legacy IT environments. This session will explore practical strategies for modernizing outdated infrastructure, transitioning to AI-powered cloud architectures, and strengthening cybersecurity resilience. From system interoperability to risk mitigation, we’ll unpack the technical and organizational levers needed to transform legacy systems into AI-ready foundations.