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We’ll unpack how foundational concepts like large language models, vector search, and knowledge augmentation are being applied in strategic contexts across industries. More importantly, we’ll address what true readiness looks like—organizationally, technically, and culturally. Through real-world examples and a pragmatic lens, you’ll be invited to assess both your company’s AI maturity and your own role in guiding its evolution.
If you’re navigating transformation or simply asking “what now?”, this session is designed to inform, challenge, and engage—not to sell, but to spark a more meaningful conversation.
Executive Learning Opportunity:
This discussion also introduces our executive-level Generative AI course: a focused 20-hour program built for C-suite leaders. The course provides the frameworks, language, and actionable roadmap needed to lead AI adoption with confidence. By linking strategic insights to hands-on decision-making, it ensures leaders don’t just understand AI—they can act on it.
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Hosted in an elegant setting at the Benaki Museum, the dinner will gather speakers, distinguished guests, corporate leaders, policy-makers, and partners for an exclusive networking experience in a relaxed yet prestigious atmosphere.
Purpose & Experience:
- Executive AI Course Launch – The evening will feature the exclusive unveiling of our AI Executive Education Program for C-level Leaders. This initiative is designed to:
1. Equip executives with a strategic understanding of AI’s transformative potential across industries.
2. Provide actionable frameworks for AI-driven growth, governance, and ROI-focused decision-making.
3. Address leadership challenges in scaling AI adoption, building AI-ready cultures, and aligning innovation with business objectives.
4. Offer a capstone module tailored to each executive’s strategic priorities, ensuring immediate applicability within their organizations.
- Foster Connections – Provide a unique space for meaningful conversations among top-level executives, innovators, and thought leaders.
- Cultural & Culinary Experience – Guests will enjoy a curated dining experience
The Gala Dinner will embody the Forum’s vision: where leadership meets AI innovation, and relationships are forged to define the future.
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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.
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Future workflows will harness self-directed AI agents capable of navigating vast datasets, uncovering novel insights, and optimizing complex simulations—dramatically shortening the path from concept to application. By drawing on principles such as neuroplasticity-inspired frameworks and reversible computing, agentic AI will enhance efficiency, reduce computational waste, and remain ethically aligned.
This keynote ny Simon See, Global Head Nvidia AI Technology Centre, NVIDIA will explore how agentic AI is reshaping discovery itself—unlocking new frontiers in scientific reasoning while ensuring innovation remains sustainable, responsible, and human-centered.
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This session takes a clear-eyed look at the current state of agent-based AI systems: what they are, how they function, and where they’re genuinely creating value. Through real-world examples and use cases, we’ll move past the buzz and explore the practical, evolving relationship between humans and intelligent tools.
Expect insights on:
1.The capabilities (and limitations) of agentic AI today
2.What “copilot” really means in different work contexts
3.How to evaluate value, not just novelty, when deploying AI tools
Designed for those who want to engage critically—and constructively—with AI’s next frontier.
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This session will introduce an innovative AI testing framework designed specifically for LLM and GenAI applications. It will explore the latest advancements in automated evaluation tools, real-world performance metrics, and domain-specific benchmarks that measure AI effectiveness beyond traditional accuracy scores. Attendees will gain actionable insights into testing methodologies that ensure AI models are robust, unbiased, and scalable across various industries and datasets.
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This session challenges product and strategy leaders to look beyond surface-level integrations and rethink how AI informs their core value proposition, team structures, and roadmap decisions. It’s not just about adding intelligence to existing products—it’s about building products and organizations that are fundamentally more adaptive, data-driven, and aligned with emerging user behaviors.
We’ll cover:
1.Why the “copilot phase” is just the beginning—and what comes next
2.The mindset shift required to move from reactive to strategic AI integration
3.The emerging role of the AI Product Manager as a cross-functional catalyst
4.How to structure experimentation and product discovery around fast-moving technology
5.Approaches for gathering meaningful product requirements in a landscape where user needs are still forming
This is a conversation for those ready to evolve—beyond features, beyond hype—and shape what the next generation of intelligent products can be.
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We’ll begin by experimenting with prompt engineering, where participants will explore different ways to structure inputs to guide AI responses. By adjusting tone, specificity, and constraints, they will see how small modifications can significantly improve relevance, coherence, and accuracy.
Next, we will dive into response optimization techniques, demonstrating how settings like temperature, response length, and system instructions impact AI-generated content. Attendees will practice adjusting these parameters through interactive exercises, gaining intuition on how to tailor AI behavior for different use cases.
Finally, we’ll discuss efficiency and best practices, showing how to make interactions smoother, reduce hallucinations, and achieve more reliable outputs. By the end of this session, participants will have a hands-on understanding of how to effectively work with GenAI models, empowering them to leverage AI assistants like a pro.
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We will start with the fundamental principles of Generative AI, explaining how models like Llama and DeepSeek-R1 generate human-like responses. Participants will gain insights into key architectural components, including transformers, attention mechanisms, and tokenization, as well as the differences between training and inference processes.
Moving beyond the basics, we will explore essential optimization techniques used to enhance model performance. This includes strategies for improving response accuracy, reducing latency, and balancing computational efficiency. Attendees will also learn about the latest advancements in fine-tuning methods, parameter-efficient training, and the trade-offs between different deployment strategies.
By the end of this session, participants will have a strong conceptual understanding of Generative AI, equipping them with the knowledge to build and optimize AI applications in the next hands-on session.
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In this session we'll examine:
1.Core principles of agentic AI and how it differs from traditional reactive systems
2.Real-world case studies in healthcare, finance, and customer service
3.Potential benefits, including improved efficiency and decision-making accuracy
4.Challenges in implementation, including integration with existing systems and processes
5.Ethical considerations and the need for human oversight
6.Concrete examples and critical analysis, which will assess whether agentic AI represents a genuine leap forward in decision-making or just an overhyped trend. Attendees will gain insights into the current state of agentic AI and its potential impact on their industries.
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This workshop is designed for anyone looking to dive deeper into building practical and impactful GenAI solutions. Don’t miss this opportunity to enhance your skills and bring your ideas to life!
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This workshop is designed for anyone looking to dive deeper into building practical and impactful GenAI solutions. Don’t miss this opportunity to enhance your skills and bring your ideas to life!
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What does this mean for the role of testing in the next few years? What changes will we have to adapt to and what will the role of testing look like in ten years? Will software testing, as we know it today, still play a role in the future? And if so, do we still need humans for this? In my talk, I would like to shed light on the current status of testing with AI, show possible future scenarios and try to find plausible answers to these questions.
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You'll also see how developers can use Generative AI to create specification documents, generate documentation, understand complex code, and more. This enhances productivity and streamlines the development process.
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Reliability in AI will be addressed, with an emphasis on thorough testing and error handling. We'll identify challenges like complexity and data privacy, and discuss solutions such as regulatory frameworks. A case study on brAInbank, a NextGen Knowledge Management System powered by Agentic AI, will offer practical insights.
Finally, we'll look at future directions in AI, including emerging trends and innovations, and wrap up with a summary and Q&A session.
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Ethically, LLMs face issues such as bias amplification, where they might perpetuate existing stereotypes in their outputs. Misinformation is another concern, with the potential misuse of LLMs to create convincing yet false narratives. Privacy risks emerge from LLMs possibly memorizing and revealing personal data. Moreover, societal challenges include the impact on employment, as LLMs could automate tasks but also lead to job displacement. These challenges highlight the need for careful management and ethical considerations in the deployment of LLMs
In this talk, Ahmed will highlight the key challenges and technical debt associated with LLMs' deployment, which demands customization and sophisticated engineering solutions not readily available in broad-use machine learning libraries or inference engines
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Central to overcoming these challenges is the role of memory. Memory within AI systems is not only essential for retaining operational data but also for enabling adaptive learning, entity profiling, and customized interactions. Different types of memory, such as short-term and long-term memory, play distinct roles in supporting an agent’s functionality. This talk will delve into the architecture of Agentic Systems and examine how various forms of memory—working memory, data stores, profilers, and toolboxes—contribute to creating robust, efficient, and scalable AI solutions. Attendees will gain insight into how memory is leveraged to enable learning from past executions, personalize interactions, and enhance system capabilities in complex AI applications.
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This session aims to offer insight into mitigating these issues by delving into RAGAS (Real-World Application and Generalization Assessment Score), a novel framework designed to quantitatively measure the performance of LLM-driven applications. Drawing from well-established practices in the software testing world, it demonstrates how RAGAS can guide the development and deployment of LLM technologies with tangible benefits. A short demo is also included as a practical demonstration of how RAGAS's ability to evaluate LLM effectiveness can be translated into real-world impact.
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Creating the right product is a cross-functional effort—engineering, product and design must evolve their processes to harness the power of agentic AI. We outline a practical roadmap for upskilling teams, fostering AI literacy, and integrating agentic capabilities across disciplines. Through real-world examples, we demonstrate how collaboration between technical and non-technical stakeholders can accelerate AI adoption while mitigating risks.
Beyond technical implementation, organizations must undergo a fundamental shift to support agentic products at scale. We discuss key organizational transformations, including restructuring workflows, redefining success metrics, and cultivating an AI-first culture. Whether you're just starting your AI journey or looking to enhance existing capabilities, this session provides actionable insights on kickstarting agentic initiatives within your organization.
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In this session Despina Paparchrysanthou, EVP for Global Processes and Continuous Improvement at Telemeperformance will showcase tangible case studies and AI-powered solutions in the revolutionization of workflows which optimize customer interactions, and enhance the efficiency overall.
You will leave with lessons as to how to delve into the dynamic interplay between human expertise and AI innovation and grasp the method in which this synergy propels systematic, data-driven enhancements.
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Many organizations rely on a complex array of products that were not designed to support today's highly distributed environment. Additionally, as breach vectors multiply, enterprise application stacks become more complex, and new threats emerge daily, the time and resources required for businesses to remain secure and operational have grown exponentially.
In this session, Evi Kechagia, Cybersecurity Technical Solutions Architect at Cisco Greece, Cyprus and Malta will examine how teams can proactively identify threats before they become incidents within their organizations. This can be achieved by harnessing the power of Artificial Intelligence and Machine Learning models through pattern recognition. We will also explore how teams can establish secure and resilient networks and streamline operations by utilizing tools and systems that simplify the tasks of IT and Security teams. These techniques are particularly crucial in situations where data analysis is complex and resource-intensive.
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In this session, we will focus on the "hub and spoke" models that our organization uses to address these challenges in two key areas: technology and product management. Specifically, we will explore the following aspects:
Technology Aspect: We will examine the gaps in data consolidation and homogenization, and discuss the data modelling and data quality framework that has been established to create a common analytics layer. We will also delve into the data engineering framework that supports development at scale and in parallel by multiple vendors, including the Cloud accelerator. Additionally, we will explore the MLOps techniques and guidelines that have been implemented to support the simultaneous lifecycle of models in a large number of countries.
Management Aspect (Cultural): We will discuss the adoption of the SAFe model within the IT department to execute all initiatives, not just those related to AI/ML and Analytics. We will address the project vs. capacity paradox and its consequences, as well as efforts to change the mindset within a traditional organization. Finally, we will share stories from Azure DevOps and other platforms about monitoring and scaling with multi-vendor teams inside the products.
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The session will illustrate these concepts through the story of a digital agriculture product developed by the National Observatory of Athens in collaboration with Corteva Agriscience for cotton farmers in Greece. The comprehensive case study covers all aspects of the project, from product development to on-field deployment. We'll specifically focus on how causal AI techniques were used to accurately estimate the incremental impact of the product on the farmers' yield, which served as the primary measure of success.
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Moreover, Nikos will focus on identifying pain points specific to the Greek landscape, particularly within SMEs, addressing their immaturity in AI adoption, and proposing innovative solutions to bridge this gap. The session's insights will illuminate the path forward for AI in product development in an ever-evolving technological landscape.
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In this speech, Marion Nikoloudaki, Head of Data Science and Machine Learning in Light & Wonder will unlock the potential of AI adoption by addressing the common obstacles and providing actionable solutions that empower companies to thrive in the age of AI.
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1. The potential of AI to enhance SMBs' products, services, processes, and customer experiences.
2. The importance of adopting AI in a responsible and ethical manner, taking into account potential risks and impacts.
3. How SMBs can leverage AI to unlock new opportunities and gain a competitive edge.
Additionally, we will provide valuable insights and resources for SMBs embarking on or expanding their AI journey, including:
1. Strategies for identifying and prioritizing the most relevant and feasible AI use cases based on their goals and challenges.
2. Guidance on accessing and utilizing available AI tools and platforms to swiftly and effortlessly deploy AI solutions.
3. Advice on fostering a culture of learning and innovation within their organization through AI education and training.
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Businesses are constantly in search of innovative solutions to move beyond traditional rule-based bots and simple voice assistants like "Hey Siri." They are now embracing the new era of human-like AI implementations that offer numerous benefits such as operational efficiency, quality control, cost savings, lead generation, improved satisfaction, and enhanced customer experience and engagement.
The applications of Conversational AI span across various industries, from e-commerce giants to healthcare providers, financial institutions to customer service hubs. Its impact is widespread and far-reaching, revolutionizing the way businesses interact with their customers.
Join ut to discover how natural language processing and machine learning have paved the way for AI systems that understand and respond to human interactions in ways never imagined before.
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This is where AI becomes a game-changer for BI Developers. It enables us to access data that was previously inaccessible, making the process easier and faster. With more data at our disposal, we can achieve more accurate results and uncover hidden opportunities for business growth. The potential for faster expansion is tremendous.
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Elisavet will delve into the intricacies of harnessing the potential of generative AI, shedding light on its role and limitations. Additionally, we will demonstrate how to unlock the full potential of data analytics and machine learning in conjunction with generative AI to propel corporate performance and bolster competitiveness. Lastly, we will dispel prevalent misconceptions and tackle the obstacles that arise when implementing generative AI in practical scenarios.
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To address this challenge, a major project was initiated: the development of a tool that can summarize, generate Q&As, and compose corporate circulars. The ultimate goal is to improve the quality of document production.
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Artificial Intelligence (AI) and Machine Learning (ML) have gained global recognition as crucial tools for future networks. Christos Rizos, Head of Big Data, Analytics, AI, Orchestration at Intracom Telecom, will analyze how to strategically focus on AI & ML to drive innovation and maintain a competitive edge. The main objectives to be analyzed include:
1. Minimizing energy consumption and carbon footprint in 5G network deployments.
2. Proactively identifying and addressing performance and reliability issues.
3. Intelligently managing and mitigating interference.
3. Predicting and enhancing the Customer Network Experience.
4. Optimizing Network Planning.
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Sofia Michili, Group Product Manager at Hotjar, will demonstrate insights on identifying use cases for AI in your product and integrating them into your product development roadmap. Sofia will also explore the challenges and considerations associated with these developments, providing strategies to overcome them.
Lastly, you will learn how Hotjar identified and solved real user needs with their new AI features in a short timeframe.
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As a result, there are now numerous use-cases where we need to find the closest match from a large set of high-dimensional vectors. However, exhaustive search is not feasible due to its high computational cost and time limitations.
To address this challenge, we will focus on techniques and practices implemented in the FAISS library. We will identify the basic indexes and provide solutions to make the billion-scale problem achievable.
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br> Throughout the presentation, Panos will take us on a journey through the development of AI, highlighting key milestones and breakthroughs that have shaped its progression over time. Drawing from his own experiences in the field, he will offer valuable insights into the challenges and advancements that have propelled AI to its current state.
One of the central themes the session will explore is the ethical implications of AI. As AI continues to advance and become more integrated into various aspects of our lives, it raises important questions about how we ensure its responsible and ethical use. The concept of the "alignment problem" will be a focal point of discussion, as it pertains to the challenge of aligning AI systems with human values and goals.
Attendees can expect to gain valuable insights into the evolution of AI and the critical importance of addressing ethical concerns in this rapidly advancing field.
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One of the main concerns surrounding AI integration is data privacy. In this session, Spiros Economakis Head of Cloud Infrastructure at Mattermost, will discuss how organizations can harness the power of AI without compromising the security of their private data or sharing it with third parties. Additionally, the session will delve into the role of Open Source AI Models.
In an era defined by collaboration and collective innovation, open-source models have become essential tools for making AI accessible to all. We will uncover how these models can be utilized within a communication platform, allowing for customization and adaptation to meet specific organizational needs.
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As we embark on this exciting journey into the era of Space Analytics, we will uncover the transformative power of AI. It is propelling the next wave of industrial operational efficiency, environmental stewardship, and economic growth, making it an indispensable and compelling force in the global economy.
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