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Rajat Dhawan - Group Chief Digital & Technology Officer at Soho House - How Data & AI Enhance Member Experiences
Germany Nov 17, 2025 Country Members Virtual english
Many AI initiatives stumble at the very beginning—often because the data foundation isn’t ready. Success requires balancing proven systems with new technologies and finding ways to apply AI across hybrid environments. In this session, speakers from Germany, Austria, and Switzerland will share their perspectives on how CIOs can turn these challenges into real progress.
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Belgium Nov 18, 2025 Invitation Only Physical english
As businesses navigate increasing demands for agility and digital transformation, aligning IT strategies with business goals is essential for success. This roundtable will bring together CIOs, CTOs, and Digital Leaders to explore how to develop and manage IT Operating Models that effectively support business objectives. The discussion will focus on the key components of an IT Operating Model, including people, processes, technology, and governance, and the importance of agility in today’s fast-paced environment.
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UK Nov 19, 2025 Country Members Physical english
Join us for the final community event of 2025 on 19th November in London. Join us for our community event on 21st May in London. Sponsored by Business Partners Cognizant, Orange Business, Entelect, Strategy, Stefanini & Thoughtworks.
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Belgium Nov 20, 2025 Invitation Only Physical english
Every organisation sits on a mountain of data, builds new platforms, and experiments with AI. Yet the key question remains: how much of this activity creates value that leaders can see and measure? Data in isolation delivers little; without clear decisions, it clutters rather than clarifies. The task is shifting from stockpiling information to making better, faster decisions that scale across every channel and moment that matters. How to close the gap between data investments and business outcomes? Which decisions should be centralised, and which remain distributed? What role should AI and automation play in orchestrating relevance?
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Germany Nov 20, 2025 Country Members Physical english
CIONET, BT und Cisco laden am 20. November 2025 ab 18 Uhr zu einem vertraulichen Dinner mit ausgewählten CIOs und IT-Verantwortlichen aus Enterprise- und Großunternehmen nach München ein – Teil einer länderübergreifenden CIO-Gesprächsreihe in Europas wichtigsten Märkten. Im Zentrum der Diskussion steht eine der drängendsten Fragen unserer Zeit: Wie können Unternehmen digitale Souveränität angesichts geopolitischer Risiken, wachsender Regulierung und technologischer Abhängigkeiten konkret umsetzen?
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Spain Nov 20, 2025 Country Members Physical spanish
Gala de entrega de los Premios CIONET Vocento 2025. Reconoceremos a las Compañías Líderes en Excelencia Tecnológica en Proyectos y a los Líderes Digitales del Año 2025.
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Workday Accelerates Generative AI & ML Product Development Using Amazon SageMaker
Learn how Workday fuels engineering productivity by using Amazon SageMaker.
with customers’ data residency requirements
of inference requests
engineering workflows
improvement for ML inference
Overview
Workday Inc. (Workday), a leading provider of solutions that help organizations manage their people and money, is highly focused on putting its engineering effort toward developing products that have built-in artificial intelligence (AI) capabilities. To help free its engineers from infrastructure maintenance, Workday adopted Amazon SageMaker, a fully managed service that helps its teams build, train, and deploy machine learning (ML) models for any use case. By using AWS services, Workday’s engineering teams can rapidly iterate and deploy complex models, including large language models (LLMs), to production.
Opportunity | Using AWS Regions to Meet Data Residency Requirements for Workday’s Global Customers
Workday offers software solutions that help its customers make accurate decisions and drive performance across human resources planning, financial planning, supply chain management, and other areas of their operations. For years, Workday has been investing in AI to help its customers make the most of their operational data with AI/ML-driven insights. “We consider ML a core backend technology for Workday,” says Shane Luke, head of Workday AI. “Our goal is to make AI-based solutions that provide our customers with real value.”
Because the company serves a global customer base, Workday needs to run its ML inference in alignment with its customers’ data residency requirements. “We have customers who are very sensitive,” says Luke. “We came to the realization that we needed a federated, distributed system that could run in many regions.” While building out a backend for its ML, the company wanted to avoid investing in its own regional private clouds.
Workday’s teams found that they can run their workloads in the AWS Region of their choice, which has supported the company’s business growth. “Our global expansion has been done on AWS,” says Luke. “It really has been a key point for us. We can deliver regionality to customers based in Europe, the Middle East, and Asia. For us, that’s been a major win.”
“Using AWS, we’ve gone from scaling to a thousand inference requests to tens of millions that are coming in daily,” says Luke. “It’s been very rewarding to see.” Further, the company has been able to scale with virtually no downtime.
Using AWS, we’ve gone from scaling to a thousand inference requests to tens of millions that are coming in daily. It’s been very rewarding to see.”
Shane Luke
Head of Workday AI
Solution | Improving Inference Latency by Five Times Using Amazon SageMaker
For its generative AI use cases, Workday uses Amazon SageMaker to simplify searching, evaluating, customizing, and deploying LLMs. “Workday has been an early adopter of LLMs, and we are actively building new generative AI capabilities that will help our customers increase productivity, grow, retain talent, streamline business processes, and drive better decision-making,” says Eddie Raffaele, vice president of Workday AI. “Workday can quickly tap into the power of generative AI and realize its value by bringing the best solutions to customers safely and responsibly.”
To support collaboration across its global teams, Workday provides its engineers access to Amazon SageMaker Studio, a web-based, integrated development environment for ML. Workday’s engineers can then compare and evaluate new foundation models by using Amazon SageMaker Jumpstart, an ML hub with foundation models, built-in algorithms, and prebuilt ML solutions. “For tasks such as creating job descriptions, which must be high quality, we use the model evaluation capability in Amazon SageMaker and select the best foundation model that reflects our company’s priorities and metrics in a responsible way,” says Luke.
Workday’s engineering team has also adopted Amazon SageMaker Ground Truth Plus, which applies human feedback across the ML lifecycle to create and evaluate high-quality models. The team has used this solution across eight labeling use cases, including named entity recognition, entity linking, sentiment and theme analysis, and more. “There’s a lot of labeling and annotating that is needed to manage our LLM outputs and receive high-quality data within our guaranteed SLAs,” says Luke. “Amazon SageMaker Ground Truth Plus has become an intrinsic part of our LLMs.”
Next, its engineers can fine-tune their LLMs with high-quality data by using Amazon SageMaker Notebook Instances to prepare and process the data to train their LLM models. Workday’s engineers then deploy their models for inference to achieve optimal performance and costs while reducing operational burden. For example, Workday used Amazon SageMaker to pilot a closed-book ML application that could analyze job descriptions, invoices, and contracts. During this pilot, Workday saw its ML inference latency improve by a factor of five.
Workday also uses LLMs to power friendly, personalized reminders that help its customers stay on track with their project and organizational goals. “There are more than 13,000 tasks available through Workday,” says Luke. “We’ve built and trained an ML model for a tenant that delivers the three top task recommendations based on the user’s activity.” With these tools at their fingertips, Workday’s customers can maximize their operational efficiency and prioritize projects with data-driven insights.
Outcome | Experimenting with Generative AI Using Amazon Bedrock
Workday received early access to Amazon Bedrock, a service that provides the simplest way to build and scale generative AI applications with foundation models. Workday uses Amazon Bedrock to facilitate product prototyping and test multibillion-parameter ML models. “We’re able to rapidly experiment and identify which AI capabilities we should invest in and put in front of our customers,” says Luke.
The Workday team is also working toward immediate deployment of new features for its customers instead of rolling out features one region at a time. “We’re pleased with the flexibility that AWS has given us,” says Luke. “We can deliver value to our customers and scale horizontally.”
More than 10,000 organizations worldwide rely on Workday to manage their most valuable assets—people and money. Workday provides customers with efficient financial and human resources solutions that help facilitate decision-making and performance.
Rajat Dhawan - Group Chief Digital & Technology Officer at Soho House - How Data & AI Enhance Member Experiences
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Hanna Huber - CTO at Flix Tech - Transforming Technology at Flix
Giuseppe Ficara - The Untold Story of Amplifon's Data & AI Transformation
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Jesús Oliva, Head of Data & AI at Moeve - From Data Challenges to AI Leadership
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Radosław Maćkiewicz - CEO at COI - Empowering Citizens Through Digital Innovation
Kalman Tiboldi - CTO & Founder at GemOne-TVH - Simplify or Die: Why Complexity Is the Real IT Challenge
The role of the CIO has evolved from managing systems to shaping outcomes: growth, resilience, and competitive edge are now won or lost in the technology arena. Today ’ s CIOs must balance stability with innovation, control costs while attracting scarce talent, and modernise legacy infrastructure while adopting emerging technologies.
As AI transitions from a specialised tool to an all-pervasive force, understanding its profound implications for our human lives is no longer merely academic but an urgent imperative for social well-being and strategic preparedness.
Geopolitical tensions have dominated the headlines for over two years now. In this context, the cyber threat landscape is also evolving rapidly. The protection and security of critical infrastructure – both physical and digital – is becoming increasingly important.
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