.png)
Belgium 15-09-2026 Squad Only Virtual english
AI pilots are easier to launch than to embed into daily operations. The challenge is changing how work happens once AI becomes part of decisions, tasks, handovers, and controls. Three pressure points tend to decide whether adoption holds. - Workflow fit matters: AI has to enter the flow of work as part of the process. - Ownership needs to be clear: someone must own the process, the controls, the exceptions, and the outcome. - User trust has to be built: people need to know when to rely on AI, when to challenge it, and when to escalate. The working question is simple: how do we move AI from promising pilots into daily work while keeping clarity, accountability, and risk control? If this is part of your current reality, let’s compare choices, constraints, and lessons learned.
Read More
Belgium 17-09-2026 Country Members Physical french
Pendant longtemps, le TCO donnait une impression de contrôle. On investissait, on amortissait, on optimisait. Les coûts étaient visibles, relativement prévisibles, et structurés autour d’une logique claire entre CAPEX et OPEX. Ce modèle ne suffit plus à expliquer où va réellement l’argent. Aujourd’hui, une part croissante des dépenses IT ne repose plus sur ce que l’on possède, mais sur ce que l’on consomme: des tokens générés par l’IA des agents qui exécutent des actions en continu des outils SaaS qui se multiplient dans les équipes du cloud qui s’adapte en permanence à l’usage Le coût ne disparaît pas, mais il devient plus diffus, plus dynamique, et souvent plus difficile à attribuer, à expliquer, et à maîtriser. C’est là que des approches comme le Technology Business Management, ou TBM, redeviennent particulièrement utiles: non pas comme un exercice de reporting supplémentaire, mais comme un moyen de relier concrètement les dépenses aux services, aux usages, et aux décisions. Et c’est là aussi que la question du “Saint Graal” revient, mais sous une autre forme. Vous vous demandez peut-être: Comment garder de la maîtrise quand la dépense dépend du comportement, des usages, et parfois même de systèmes autonomes ? Comment piloter l’équilibre CAPEX/OPEX quand le cloud, le SaaS et l’IA déplacent progressivement les coûts vers des modèles variables ? Quels coûts restent encore trop souvent hors radar: ressources métier, formation, support, intégration, sécurité, gouvernance ? Et surtout, qu’est-ce qu’un “bon TCO” veut encore dire quand il faut le mettre en regard d’objectifs parfois plus stratégiques, plus longs à mesurer, ou plus difficiles à quantifier: qualité de service, résilience, agilité, expérience utilisateur, capacité d’innovation ? Ce sont précisément ces questions qui seront au cœur de notre rencontre: une discussion ouverte entre pairs, ancrée dans la réalité du terrain, pas pour débattre de modèles idéaux, mais pour comprendre comment chacun tente, concrètement, de mesurer, d’attribuer et de reprendre le contrôle, sans réduire la valeur d’un choix technologique à son seul coût.
Read More
Belgium 25-09-2026 Squad Only Physical english
Transformation has become constant. The challenge is managing the amount of change teams are expected to absorb while they continue to deliver existing work. Three pressure points show up quickly. - Capacity becomes stretched when teams face new tools, processes, AI practices, security requirements, and operating model changes at the same time. - Prioritisation becomes critical when many initiatives compete for attention. - Managerial discipline becomes essential because leaders need to decide what to stop, simplify, delay, or protect. The working question is simple: how do we keep transformation moving while giving teams enough focus and capacity to execute it properly? If your teams are absorbing constant change, let’s compare how others are managing capacity, sequencing, and focus.
Read More
CIONET Trailblazer: CISO: The Shift from Prevention to Resilience: Turning Visibility into Execution
Published on: January 28, 2026 @ 9:48 AM
CIONET Trailblazer: AI Transformation: Bridging the Cultural Divide to Achieve Competitive Advantage
Published on: December 17, 2025 @ 9:16 AM
Ferrari Advances Generative AI for Customer Personalization and Production Efficiency
Learn how Ferrari uses generative AI on AWS to enhance the customer and vehicle journeys to increase sales, experimentation, and productivity.
car configurations
vehicle simulations
of hyperpersonalized recommendations
Overview
Luxury Italian auto manufacturer Ferrari S.p.A. (Ferrari) has forged a globally recognized legacy that’s rooted in tradition and innovation over many decades. To continue to deliver the best possible experiences to customers and dealers, Ferrari has tapped into the power of generative artificial intelligence (AI) by turning to Amazon Web Services (AWS).
Ferrari has applied generative AI to several use cases, from accelerating the vehicle design process to providing personalized services to its customers. “Every day, we try to find new ways of achieving excellence while improving our customers’ experiences and their connection with our brand,” says Silvia Gabrielli, chief digital and data officer at Ferrari.
Opportunity | Building a Cloud Foundation on AWS with Ferrari
Founded in 1947 for sports car racing, Ferrari epitomizes the power of a lifelong passion and the beauty of limitless human achievement. Ferrari, which has cultivated a loyal fan base, has focused on reaching fans and potential customers by offering unique digital experiences on its website and mobile applications. In 2021, Ferrari selected AWS as its preferred cloud provider to advance its compute, analytics, and storage capabilities. “AWS has been key to our IT transformation,” says Gabrielli. “We started our cloud journey a couple of years ago as a strategic initiative. Today, all our critical workloads are on AWS.”
To free its teams from managing the infrastructure for its applications, Ferrari has invested in fully managed services, such as AWS Fargate, a serverless compute solution for containers. “We’ve reduced the total cost of ownership for our infrastructure from 70 percent to 40 percent,” says Alessio Glorioso, product manager at Ferrari. The company has also seen improvements in the reliability and scalability of its applications. For example, the company can run simulations in its product lifecycle management software 60 percent faster than before.
Ferrari remains committed to furthering its technology road map with generative AI, seeing it as an opportunity to improve the vehicle and customer journeys. “Generative AI is something that every company needs to consider,” says Gabrielli. “It’s a game changer. We can use generative AI to increase our productivity and make it simpler for our fans, dealers, and employees to have the best digital experiences with Ferrari.”

We can use generative AI to increase our productivity and make it simpler for our fans, dealers, and employees to have the best digital experiences with Ferrari.”
Silvia Gabrielli
Chief Digital and Data Officer, Ferrari
Solution | Greater Speed and Ease of Choice Personalizing a Ferrari Using Amazon Bedrock
To bring the luxury experience to customers around the world, Ferrari developed the car configurator on AWS, giving its customers the ability to personalize their own Ferrari, from wheel selection to paint colors to interior options. “There are millions of possible configurations,” says Simone Canditone, digital experience manager at Ferrari. “We want to help our dealers and customers effectively customize their vehicle to suit their needs.”
To do so, Ferrari uses large language models (LLMs) in Amazon Bedrock, a fully managed service that offers a choice of high-performing foundation models, along with Amazon Personalize to elevate the customer experience with personalization powered by machine learning (ML). Since rolling out the car configurator, Ferrari has increased its sales leads and reduced configuration times by 20 percent by offering a more personalized experience where customers can visualize a vehicle with 3D imagery that can be rotated and zoomed in and out. It also allows a customer to virtually experiment with different options.
Ferrari also enhances the after-sales experience with a generative AI chatbot. To assist its sales professionals and technicians, the company fine-tuned LLMs in Amazon Bedrock—including Amazon Titan, Claude 3, and Llama—on its documentation. “Amazon Bedrock has simplified our approach,” says Mauro Coletto, head of business analytics and AI at Ferrari. “We can connect to a single layer of APIs to quickly test, benchmark, and deploy different models.”
Ferrari combines its use of Amazon Bedrock with Amazon SageMaker JumpStart, an ML hub with foundation models, built-in algorithms, and prebuilt ML solutions that can be deployed with only a few clicks. Using these services, Ferrari has trained its chatbot to classify and summarize customer care tickets and answer commonly asked questions that help to reduce human error while improving productivity.
Ferrari uses AI and ML to optimize the production of its vehicles as well. For example, Ferrari uses Amazon Lookout for Vision to spot product defects using computer vision to automate quality inspections. Using AI, the company can detect missing or defective parts in the assembly line before a vehicle goes to testing, helping it save on costs.
The company has improved the vehicle design with generative AI across F1 vehicles and sports cars by being able to test more designs. Using generative AI, Ferrari can reduce its time to market while relying less on physical prototyping. “We can run analytics and simulations and make correlations that were not possible in the past,” says Gabrielli. “It really speeds up and improves our product development.” Creating full car body physical prototypes is time and resource intensive, and by running virtual simulations on the cloud, Ferrari can run thousands or even millions of simulations in parallel at a very low cost. Additionally, Ferrari is training generative AI text-to-image capabilities that facilitate text-based prompts to make vehicle render improvements and design changes quickly.


Thanks to the configurator, everything was possible within seconds so I could try many different colors, many different interiors, and make it a reality. You can really see the car just like you would in reality, but in a virtual world.”
Charles Leclerc
Official driver, Scuderia Ferrari HP
Outcome | Experimenting with Generative AI
With a strong cloud foundation on AWS, Ferrari used generative AI solutions to gain measurable impacts across its business. Ferrari will continue expanding its use of generative AI to better serve customers and dealers. The company is also exploring cloud services that will help it meet its carbon neutrality commitment by 2030.
“Innovation is in Ferrari’s DNA, since the first days of our founder,” says Gabrielli. “We see AWS as a strategic collaborator in our innovation efforts. We really align in terms of our values around excellence, innovation, and customer obsession.”
Italian luxury sports car manufacturer Ferrari has built a legacy upon decades of sporting success that epitomizes craftsmanship and innovation. Ferrari continues to uphold its tradition of racing with its professional racing team, Scuderia Ferrari.
Amazon Bedrock Amazon Personalize Amazon SageMaker AWS Fargate
597 Views 0 Likes Read More
CIONET’s Cyber Circle: a new three-event programme exclusively focusing on the most urgent, complex, and high-impact challenges in cybersecurity today. Launched in 2026, this initiative brings together CISOs, CIOs, and senior IT executives with a strong interest in cybersecurity for three curated gatherings each year. As part of CIONET’s trusted executive community, the Cyber Circle provides a confidential, peer-driven environment to exchange insights, share real-world experiences, and address evolving cyber threats. Each session is designed to foster strategic dialogue, strengthen resilience, and elevate cybersecurity as a core driver of business value.
Read More
The Telenet Business Leadership Circle powered by CIONET, offers a platform where IT executives and thought leaders can meet to inspire each other and share best practices. We want to be a facilitator who helps you optimise the performance of your IT function and your business by embracing the endless opportunities that digital change brings.
Read More
Découvrez la dynamique du leadership numérique aux Rencontres de CIONET, le programme francophone exclusif de CIONET pour les leaders numériques en Belgique, rendu possible grâce au soutien et à l'engagement de nos partenaires de programme : Deloitte, Denodo et Red Hat. Rejoignez trois événements inspirants par an à Liège, Namur et en Brabant Wallon, où des CIOs et des experts numériques francophones de premier plan partagent leurs perspectives et expériences sur des thèmes d'affaires et de IT actuels. Laissez-vous inspirer et apprenez des meilleurs du secteur lors de sessions captivantes conçues spécialement pour soutenir et enrichir votre rôle en tant que CIO pair. Ne manquez pas cette opportunité de faire partie d'un réseau exceptionnel d'innovateurs numériques !
Read More
CIONET is committed to highlighting and celebrating female role models in IT, Tech & Digital, creating a leadership programme that empowers and elevates women within the tech industry. This initiative is dedicated to showcasing the achievements and successes of leading women, fostering an environment where female role models are recognised, and their contributions can ignite progress and inspire the next generation of women in IT. Our mission is to shine the spotlight a little brighter on female role models in IT, Tech & Digital, and to empower each other through this inner network community.
Read More
Would you like to know more about CIONET Belgium, membership or partnership opportunities? Do you have feedback or any other question? Send us a message!
You can either send us a registered handwritten letter explaining why you'd like to become a member or you can simply talk to us right here!