We will delve into the critical aspects of ensuring that artificial intelligence systems are developed and implemented in a way that fosters trust among users. By examining issues such as bias mitigation, transparency in algorithms, and the reliability of AI-driven decision-making processes. Additionally, we will address critical issues surrounding the security risks and data privacy challenges associated with artificial intelligence by featuring experts, researchers, and industry professionals to discuss strategies and best practices for protecting AI systems from potential threats and ensuring the privacy of sensitive data.

april 3 labsssss

april 3 labs

april 3 bootcamp

april 2 test

In a time when Generative AI is reshaping markets, workflows, and even leadership expectations, senior decision-makers face a pressing challenge: how to cut through the hype and act with clarity. This 30-minute session creates space for critical reflection—not on what AI can do, but on what it should do for your organization.

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.

The Networking Dinner of this year’s forum will serve as the culminating highlight of the conference — a sophisticated evening designed to celebrate innovation, leadership, and collaboration in the AI era.

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.

AI is reshaping the very foundation of how businesses operate, demanding a new kind of leadership at the top. For C-level executives, keeping pace with this transformation means more than adapting—it requires a fundamental shift in how they think, lead, and make decisions. The stakes are high, and the speed of change is relentless. In this panel, we explore what it means to lead with intelligence—and how senior executives can develop the mindset, fluency, and capabilities needed to drive AI impact at scale. From understanding agentic systems and responsible AI governance to collaborating with technical teams and rethinking decision-making processes, this conversation unpacks the critical competencies required to lead in an AI-powered world.

As artificial intelligence continues to reshape industries, Mergers & Acquisitions (M&A) involving AI-driven companies are accelerating. For C-suite executives, AI M&A presents unique challenges and opportunities—whether acquiring AI startups to enhance innovation, integrating AI capabilities into legacy enterprises, or positioning their own organizations for acquisition. This session will provide C-level executives with a strategic framework for navigating AI-related M&A, covering valuation strategies, due diligence, integration challenges, and regulatory considerations. With AI playing a critical role in business transformation, leaders must be equipped to assess AI-driven opportunities and make informed acquisition decisions that drive long-term value.

As AI systems evolve from assistive to autonomous, CTOs are at the forefront of an enterprise redesign. This panel explores how technology leaders are architecting intelligent, adaptive platforms that go beyond automation—creating infrastructure that supports continuous learning, decision-making, and scalable autonomy. We’ll dive into the real technical and organizational challenges of deploying agentic models across complex environments, and how forward-thinking CTOs are aligning architecture, data, and ops to deliver enterprise-grade intelligence.

In today’s enterprise landscape, bottlenecks in application development, legacy complexity, and limited capacity for software development talent are common roadblocks to innovation. In this live session, Comsys CEO Vassilis Galakos demonstrates how enterprises can design, build and deploy secure, cloud-optimized business applications at speed using Jaggle, an AI-powered application generation platform engineered for organizations that demand software systems that are functionally rich, secure, and with unlimited integration capabilities. Designed for Innovation Leaders, this session will demonstrate the development of a real-world application using low-code visual development and AI assistance. Attendees will see how Jaggle accelerates delivery time and bridges the gap between business demands and application development latency without compromising best-in-class standards.

In a world of rapidly evolving regulations, compliance has become one of the most resource-intensive challenges for businesses. This session will explore how AI can help legal departments and compliance teams manage complexity, reduce risk, and dramatically cut the cost of research and contract review. Through a live demonstration, we’ll show how AI turns dense regulation into actionable insight — saving time, lowering external counsel spend, and empowering leaders to make faster, safer decisions at scale.

Every CEO knows that growth depends on talent. But in a world where skills expire quickly, traditional training no longer keeps up. This session explores how AI-enabled learning platforms like TalentLMS transform training into a growth engine. Learn how AI personalizes learning paths, reduces training time, and provides actionable insights that drive performance. Walk away with a clear understanding of how TalentLMS helps businesses turn learning into a competitive advantage.

Τhe next wave of AI brings a shift from supportive tools to self-directed agents, business leaders are entering a new era of opportunity—and accountability. This panel unites trailblazing CEOs and strategic thinkers to explore how Agentic AI is revolutionizing enterprise value, competitive positioning, and scalable growth. From integrating autonomous agents into key business functions to rethinking leadership models for an AI-first future, the conversation will provide strategic insights and real-life examples of how top executives are embedding AI deep within their organizations—not just as a feature, but as a foundation.

The EU AI Act is ushering in a new regulatory paradigm—classifying AI systems by risk level, imposing specific obligations on high-risk applications, and introducing penalties for non-compliance. Meanwhile, other jurisdictions are shaping their own approaches, creating a fragmented landscape that global companies must manage across markets and teams. In this panel, top legal experts, compliance officers, tech executives, and policymakers will unpack the practical implications of current and upcoming AI regulations. We’ll dive into how forward-looking enterprises are designing governance structures that align with evolving standards while preserving innovation. From legal audits and algorithmic impact assessments to cross-border harmonization strategies, we’ll outline what it means to be “AI-regulation ready” in 2025—and beyond.

As we open the second day of the Forum, George Nikolaropoulos and Despina Kitsou will set the stage for a program focused on moving from vision to execution. Building on the strategic insights shared the previous sessions, the 2nd day’s sessions will emphasize practical applications, leadership imperatives, and the pathways for organizations to translate AI potential into measurable impact

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.

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.

The rise of agentic AI marks a turning point in science and engineering, moving beyond passive data analysis to active hypothesis generation, real-time experimentation, and adaptive problem-solving. This new paradigm enables AI systems to work hand-in-hand with human experts, accelerating breakthroughs in materials science, drug discovery, and sustainable engineering.
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.

AI is no longer optional — it’s a strategic imperative. Yet most organizations struggle to go beyond experimentation. In this session, we’ll move past the hype and focus on how to build a real-world, actionable AI adoption roadmap tailored to business needs, resources, and risk profile. Whether you’re in manufacturing, finance, healthcare, or services, the key to AI success lies not in chasing tools — but in aligning technology with your core processes, data maturity, and human workflows. We’ll explore the lifecycle of AI adoption through practical phases: business alignment, capability assessment, data infrastructure readiness, model integration, and continuous improvement. You’ll see how to transition from “isolated use cases” to full-fledged AI-enabled workflows that deliver measurable ROI. We’ll also discuss the most common traps companies fall into — from overinvesting in infrastructure to neglecting user trust and model feedback loops. Attendees will leave with a visual framework for decision-making, a maturity checklist, and key metrics of how to track progress. If you’re planning to adopt AI — or struggling to scale it — this session will give you the clarity and structure to move forward with confidence.

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.

Artificial Intelligence is transforming the financial services landscape, and NBG is actively investing in building strong AI capabilities to stay ahead. In this session, we will unpack the bank’s strategic vision for AI and the factors driving this transformation. Participants will gain insights into the specific areas where NBG is applying AI, from enhancing customer experience and operational efficiency to strengthening risk management and innovation capacity.

 Manufacturing plants, offshore platforms, and vessels generate critical operational data but often lack reliable connectivity for cloud-based AI solutions. This session explores how deploying intelligent systems directly at remote locations enables immediate decision support, reduces operational costs, and maintains business continuity regardless of network availability. Learn how industrial operators and maritime crews are using on-site AI to diagnose equipment issues, optimize processes, and access expert knowledge instantly—transforming isolated assets into autonomous, intelligent operations. We'll examine real-world deployments where local AI capabilities have prevented production losses, reduced satellite communication costs, and enabled 24/7 operational intelligence without cloud dependency.

In the era of AI-driven cyberattacks, organizations must evolve beyond traditional defense. ClearSkies™ TDIR (Threat Detection, Investigation & Response) platform empowers enterprises to detect earlier, respond faster, and adapt continuously by combining holistic telemetry, Generative AI augmentation, and Agentic AI autonomy. This session will showcase how ClearSkies™ transforms Security Operations into an AI-orchestrated resilience engine, enabling smarter workflows, reduced analyst fatigue and automated response at machine speed—helping teams stay secure, compliant, and resilient in the age of AI threats.

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.

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.

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.

Agentic AI and copilots are quickly becoming part of everyday workflows—but what do they actually enable, and how should we think about their role in the way we work, decide, and build?

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.

As enterprises increasingly integrate Large Language Models (LLMs) and Generative AI (GenAI) into mission-critical applications, ensuring their accuracy, efficiency, and reliability has become a top priority. Traditional testing methodologies fall short in capturing the dynamic nature of AI models, necessitating a new paradigm in automated testing and benchmarking.

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.

Prompt Engineering is a new field that focuses on creating and improving prompts to get the best results from language models (LMs), diffusion models, and other advanced technologies. The Crafting AI Prompts Framework is split into two parts: IPE and IVPE. This framework helps users effectively use Generative AI for writing and creating visual content, while also promoting ethical and responsible use. Through this deep dive the participants will be able to understand basic concepts around the framework and effectively apply it to use GenAI effectively and responsibly in a daily manner!

As AI-powered copilots become standard across industries, their presence is no longer a differentiator—it’s the baseline. The real opportunity now lies in how companies reshape their product strategies to lead in an AI-native world.

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.

With a solid understanding of Generative AI, it’s time to explore how to effectively interact with and optimize AI assistants—without writing a single line of code. In this hands-on session, participants will engage with a custom-built Generative AI assistant powered by Llama, Llama, and DeepSeek-R1. Through guided, no-code exercises, attendees will experience firsthand how to refine AI outputs and maximize performance.

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.

Generative AI is reshaping industries by enabling powerful applications in content generation, automation, and decision-making. However, to truly unlock its potential, one must understand not just how it works, but also how to optimize it for efficiency and accuracy. This session provides a structured introduction to Generative AI, making it accessible for novice students and AI enthusiasts.

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.

Agentic AI systems are emerging as powerful tools that can anticipate needs and make autonomous decisions. This session explores the practical applications and implications of these proactive AI agents across industries.

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.

Securing LLMs is critical for GenAI success, yet it remains one of its toughest challenges. From mitigating prompt injection and adversarial vulnerabilities to ensuring compliance, the complexities can feel overwhelming. This session introduces an actionable checklist, grounded in real-world scenarios, to help attendees simplify and structure their approach to LLM security.

AI goes far beyond chatbots—its real impact lies in Highly Autonomous and Agentic AI-driven operations, where Networks are managed with Intents, and AI translates Data Engineering high-level objectives into machine-executable actions. This session explores how Generative AI is shaping the future of telecoms enabling self-optimizing networks, and how GenAI-driven data platforms simplify operations for engineers across industries. We’ll also discuss how AI is driving sustainability, optimizing data center energy use and network efficiency to reduce costs and carbon footprints. This is not just about short-term automation but long-term innovation!

Join us for an exclusive workshop where you’ll learn how to build your own Generative AI (GenAI) application using Retrieval-Augmented Generation (RAG). In this hands-on session, we will guide you through creating an AI chatbot that retrieves relevant information from contextualized data. You’ll gain practical experience in storing vector embeddings in a vector database, a crucial component for efficient similarity searches in AI applications. Additionally, we’ll delve into the RAG architecture, exploring how integrating retrieval mechanisms with generative models enhances the accuracy and relevance of AI-generated responses.

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!

Prompt Engineering is a new field that focuses on creating and improving prompts to get the best results from language models (LMs), diffusion models, and other advanced technologies. The Crafting AI Prompts Framework is split into two parts: IPE and IVPE. This framework helps users effectively use Generative AI for writing and creating visual content, while also promoting ethical and responsible use.

Prompt Engineering is a new field that focuses on creating and improving prompts to get the best results from language models (LMs), diffusion models, and other advanced technologies. The Crafting AI Prompts Framework is split into two parts: IPE and IVPE. This framework helps users effectively use Generative AI for writing and creating visual content, while also promoting ethical and responsible use.

Join us for an exclusive workshop where you’ll learn how to build your own Generative AI (GenAI) application using Retrieval-Augmented Generation (RAG). In this hands-on session, we will guide you through creating an AI chatbot that retrieves relevant information from contextualized data. You’ll gain practical experience in storing vector embeddings in a vector database, a crucial component for efficient similarity searches in AI applications. Additionally, we’ll delve into the RAG architecture, exploring how integrating retrieval mechanisms with generative models enhances the accuracy and relevance of AI-generated responses.

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!

Thanks to the general availability and widespread use of large language models such as ChatGPT, Gemini & Co., we have become aware of the disruptive importance of AI for our discipline. It is obvious that when testing AI systems, we must deal with new technologies, test techniques and therefore new requirements and skillsets for testers. Above all, AI-based systems will have a massive impact on the work of testers; large language models and other AI systems can already partially take over the work of testers.

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.

In this session, you'll learn how Generative AI is transforming the developer experience by speeding up tasks throughout the development lifecycle. It helps with researching and evaluating system designs, building secure and scalable applications, upgrading existing ones, and optimizing performance. Generative AI can simplify these processes.

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.

This session will explore AI applications, focusing on their definition and importance. We'll cover bias in AI, looking at its types, impacts, and ways to reduce it. We'll also discuss transparency in AI, highlighting its importance and how to achieve it through explainable AI and open-source models.
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.

Generative AI have become essential in advancing AI, enabling remarkable capabilities in natural language processing and understanding. However, the efficient deployment of LLMs in production environments reveals a landscape of challenges and technical debt

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

Agentic Systems and extensible compound AI systems are revolutionizing LLM applications, positioning themselves as critical tools in modern AI development. These advanced systems go beyond traditional automation, offering capabilities that drive significant productivity and efficiency gains in enterprise and commercial workflows. However, adopting AI Agents and Agentic Systems at scale poses unique challenges, particularly in ensuring consistent performance, reliability, and scalability.

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.

This immersive workshop is designed for AI professionals, testers, and developers who are eager to leverage the cutting-edge capabilities of AI to enhance their testing strategies, automate processes, and uncover bugs with unparalleled accuracy. By blending theoretical knowledge with practical exercises, participants will gain firsthand experience in harnessing the power of AI-Augmented to transform their approach to testing, making it more efficient, effective, and innovative. Throughout the workshop, attendees will explore the core concepts of generative AI and its application, including how to generate comprehensive test cases that cover every conceivable scenario and how to use AI to identify bugs in the most unexpected places. The workshop will also delve into the nuanced art of prompt engineering tuning, teaching participants how to craft effective prompts that guide AI in performing highly specialized testing tasks. Through a series of hands-on exercises, interactive sessions, and live demonstrations, attendees will learn how to integrate these AI-powered tools and techniques into their daily workflows, elevating the quality of their testing and the products they help to create. Key takeaways: Elevating Roles with AI: Understand how AI-augmented transforms the role of testers from routine task executors to strategic problem solvers. Learn how can leverage AI to focus on more complex, creative, and strategic aspects, thus elevating their role and value within development teams. Mastering AI-Augmented : Learn how to utilize AI-driven technologies to automate and enhance your processes. Gain hands-on experience with tools that enable you to generate comprehensive requirements, tests and code and automate complex scenarios, significantly improving efficiency and coverage. The Art of Prompt Engineering: Acquire skills in prompt engineering and fine-tuning, enabling you to craft effective prompts that guide generative AI in performing highly specialized testing tasks. Learn how to tailor these prompts to your specific needs, unlocking new dimensions of test engineering capabilities and enhancing your creatively and thoroughly.

This immersive workshop is designed for AI professionals, testers, and developers who are eager to leverage the cutting-edge capabilities of AI to enhance their testing strategies, automate processes, and uncover bugs with unparalleled accuracy. By blending theoretical knowledge with practical exercises, participants will gain firsthand experience in harnessing the power of AI-Augmented to transform their approach to testing, making it more efficient, effective, and innovative. Throughout the workshop, attendees will explore the core concepts of generative AI and its application, including how to generate comprehensive test cases that cover every conceivable scenario and how to use AI to identify bugs in the most unexpected places. The workshop will also delve into the nuanced art of prompt engineering tuning, teaching participants how to craft effective prompts that guide AI in performing highly specialized testing tasks. Through a series of hands-on exercises, interactive sessions, and live demonstrations, attendees will learn how to integrate these AI-powered tools and techniques into their daily workflows, elevating the quality of their testing and the products they help to create. Key takeaways: Elevating Roles with AI: Understand how AI-augmented transforms the role of testers from routine task executors to strategic problem solvers. Learn how can leverage AI to focus on more complex, creative, and strategic aspects, thus elevating their role and value within development teams. Mastering AI-Augmented : Learn how to utilize AI-driven technologies to automate and enhance your processes. Gain hands-on experience with tools that enable you to generate comprehensive requirements, tests and code and automate complex scenarios, significantly improving efficiency and coverage. The Art of Prompt Engineering: Acquire skills in prompt engineering and fine-tuning, enabling you to craft effective prompts that guide generative AI in performing highly specialized testing tasks. Learn how to tailor these prompts to your specific needs, unlocking new dimensions of test engineering capabilities and enhancing your creatively and thoroughly.

In the rapidly evolving landscape of AI, separating genuine advancements from the noise is crucial for both industrial practitioners and academic researchers. The non-deterministic nature of LLM-driven applications amplifies this challenge, leading to difficulty in applying common software testing practices and thereby quantifying application performance.

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.

Agentic systems represent a new software paradigm that enables products to act autonomously, adapt to dynamic environments, and make decisions in real-time. However, building production-grade agentic systems requires addressing key challenges in reliability, safety, and performance. In this session, we explore the core principles and best practices for designing robust, scalable, and trustworthy agentic solutions.
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.

As artificial intelligence moves beyond traditional automation and generative capabilities, ensuring AI’s reliability, transparency, and ethical integrity becomes a pressing challenge. This session introduces AI-Assurance, a new paradigm for validating and governing Agentic AI systems, which leverage Computer Use Automation (CUA), Chain of Thought (CoT), and GraphRAG architectures to enhance model-driven decision-making, self-learning, and adaptive agent-based CUA execution. Building on decades of advancements in cognitive engineering, AI and automation,, this talk explores how large action models (LAM), large vision models (LLaVA) and AI-driven software agents are redefining productivity & assurance across the software development lifecycle (SDLC). Attendees will gain insights into the evolution of building AI-infused system methodologies, the shift from traditional process automation to autonomous AI agents, and the role of governance models like ISO 42001 and AI risk compliance frameworks (AI TRiSM / ISO / NIST). Key topics include: Agentic AI and the Future of AI-Augmented Workflows – How AI systems move from passive assistance to active moral decision-making. GraphRAG and Chain of Thought Reasoning – How structured AI reasoning enhances software quality, transparency, and compliance. CUA and Large Action Models – The emergence of autonomous, neuro-symbolic, AI agents for real-time computer use execution. AI-Assurance in the Age of Regulation – Navigating compliance, ethical AI governance, and risk management frameworks. This session is essential for AI practitioners, modern software development, and business decision-makers seeking to integrate AI-Assurance governance into their AI-productivity or AI-workforce workflows while avoiding bans from emerging AI liability laws and EU AI Act compliance mandates.

This session aims to delve into the various factors that contribute to gender bias in AI algorithms and decision-making processes. We will closely examine real-life instances where AI systems inadvertently perpetuated gender stereotypes or discrimination. By gaining a comprehensive understanding of these challenges, we can proactively implement measures to mitigate risks and promote fairness in the realm of AI.

Generative AI offers businesses a powerful tool to revamp global processes. By integrating AI into their operations, companies can elevate their operational standards and achieve greater efficiency. Teleperformance, has strategically integrated Generative AI to redefine its operational standards.

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.

The attack surface is expanding as the IT environment undergoes significant changes. Cloud adoption is increasing, remote and hybrid users now dominate, and IoT devices are becoming more prevalent on corporate networks.

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.

The international retail company operates in a complex environment, both in terms of technology and organizational structure. This complexity presents significant challenges for data analytics initiatives. Each country within the company creates its own data ecosystem and processes, making it difficult to implement solutions that work across the entire organization.

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.

To effectively market a digital product, it's crucial to understand its impact on key user metrics and determine its level of success. In this session, George Giannarakis Data Scientist at National Observatory of Athens and Ilias Tsoumas Research Data Scientist at National Observatory of Athens will discuss the importance of this causal question, the challenges in providing rigorous answers, and introduce causal AI as a powerful tool to address these challenges.

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.

Nikolaos Epitropakis, Advanced Analytics & Strategy Manager at Delottie, will explore the evolution of AI projects, emphasizing the shifting needs and deliverables. The session will delve into the common misconceptions and needs of enterprises looking to embrace AI technology.

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.

In today's fast-paced business environment, harnessing the power of artificial intelligence is no longer an option; it's a necessity. Yet, many companies face significant resistance when it comes to embracing AI technologies.

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.

AI is revolutionizing the world, bringing forth unprecedented transformations and presenting both opportunities and challenges for businesses of all sizes. In this talk, we will delve into the ways in which AI can serve as a powerful tool for innovation, responsibility, and growth specifically for small and medium businesses (SMBs). In this discussion Nadine Karali, Commercial Director Corporate and SMB, Microsoft Greece, Cyprus & Malta will encompass the following key points:

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.