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.

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.

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.

In this talk, Konstantinos Kanistras, Head of Insights and Decision Science, Advisory Senior Manager at PWC, will explore the significant role of Conversational Artificial Intelligence in today's business landscape. Specifically, he will focus on how businesses are leveraging this technology to enhance customer interactions and maintain a competitive edge.

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.

The Power of AI in Business Intelligence (BI) from the perspective of Data extraction is immense. BI Developers and Data Scientists are well-versed in manipulating data once they have it. However, obtaining the data in a structured manner and establishing connections can be a significant challenge, especially for rapidly growing organizations that deal with numerous documents. In such cases, employees often have to manually input data into systems or Excel files.

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.

In this session, Elisavet Kyritsi, the Alliances Director EMEA at Teradate, will explore the ever-changing realm of Artificial Intelligence (AI) and its significant influence on fostering business innovation.

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.

In this session Kyriakos Georgiou, Chief Risk and Data Science Officer at Finloup, will delve into the topic of forecasting customer churn in a non-contractual setting. Taking inspiration from the latest developments in machine learning that incorporate multiple time intervals, we present an inventive approach for training and evaluating known as the sliding multi-time slicing (SMTS) technique.

To tackle the flexibility and complexity of 5G networks, we need solutions that prioritize security, reliability, and resource allocation for customers. These solutions should be dynamic, robust, and trustworthy, while also reducing the environmental impact of the networks.

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.

In recent months, there has been a surge of AI-powered products flooding the market. In this session, we will guide you through identifying user needs and utilizing AI as a catalyst to address genuine customer requirements.

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.

In this session, Stathis Onasoglou, Fintech Principal at Google Cloud, will delve into the strategic landscape of Generative AI. He will analyze its value chain and discuss Fintech business cases where Gen AI has had a transformative impact. The talk will also address the significant risks associated with leveraging Gen AI in an Enterprise environment and provide best practices for governance and de-risking the Gen AI journey.

In this workshop, we will explore efficient methods and approaches for performing queries in a billion-dimensional vector space. In recent years, we have accumulated vast amounts of data and transformed them into meaningful embedding vectors using machine learning models.

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.

In this session, Panos Bassios, Digital, Data & Analytics Director at MSD, will provide a comprehensive historical overview of the evolution of Artificial Intelligence (AI). With his extensive personal experience and unique perspective, he will delve into the captivating subject of "AI and Ethics" and specifically address the widely discussed "alignment problem."
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.

In this session, George Kastrinakis, Director of Data Science at Orfium, will guide you on how to ensure maximum adaptation and value delivery from internal AI systems. By collaborating closely with the Product team, Orfium has successfully avoided the common pitfall of AI projects ending up unused or lacking real value. During the session, you will gain insights into effective practices and strategies for creating a shared development cycle. Additionally, you will learn how to distribute ownership of common workflows, fostering collaboration and maximizing the utilization of AI across various business areas. This session aims to empower you with the knowledge and tools needed to make the most out of your AI initiatives.

In this session, Michalis Rikakis, SVP of Product at Workable will delve into the ways in which artificial intelligence (AI) influences the product roadmaps of technology companies and how it can support Product Managers in their daily responsibilities. Additionally, the talk will present tangible examples from real-life scenarios to illustrate these concepts.

In this talk Stijn Schuermans Head of Product at Satori Analytics, will discuss his experiences with implementing real-world Azure Open AI scenarios in the energy, financial services, and manufacturing sectors - based on data owned by enterprise businesses. Stijn will explain how by utilizing Open AI alongside proprietary data, enterprises can greatly enhance productivity. This can be achieved through various applications such as developing internal search assistants and chatbots, using language models for feature extraction, summarization, and documentation creation, as well as integrating it into process automation. During the talk, we will explore how to create tangible business value, going beyond the hype surrounding Open AI. Additionally, we will address common challenges faced by enterprises, including dealing with messy data, ensuring security, and protecting data privacy. Enterprises have already recognized the long-term significance of Open AI. Establishing a Centre of Excellence will be crucial for their competitive success.

In the ever-changing world of communication platforms, the integration of AI has completely transformed our interactions and collaborations. In this session, we will explore how AI can empower teams to streamline processes and increase engineering productivity in various domains. We will specifically focus on areas such as Site Reliability Engineering, Incident Management, Change Management, and more.

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.

In this session, Ioannis Gkekas, Data & AI Managing Director at Accenture, will delve into the profound impact of the modern New Space economy. He will explore how the convergence of Artificial Intelligence (AI) and space technology has revolutionized Earth Observation and satellite data analytics. We will examine the pivotal role that AI plays in harnessing the vast wealth of space data to fuel innovation, promote sustainability, and drive economic growth.

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.