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Belgium 19-3-26 Country Members Physical french
Moins de Partenaires : La consolidation vaut-elle le risque ? Le problème est la prolifération des fournisseurs : trop d'outils causant de la complexité, une taxe d'intégration paralysante et de la redondance. La Taxe d'Intégration est le coût caché (en temps, en échecs et en ressources) d'essayer de faire fonctionner ensemble des systèmes disparates. Cet échange se concentre sur des stratégies éprouvées pour simplifier de manière agressive le parc technologique, consolider les fournisseurs et élever certains fournisseurs clés au rang de partenaires stratégiques.
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Belgium 24-3-26 Invitation Only Physical english
Every organisation has them, projects that keep running long after their purpose has faded. No one remembers who asked for them, but shutting them down feels riskier than keeping them alive. And eventually, people stay assigned, budgets stay allocated, and energy drains into work that no longer matters. Inertia at its finest. Ending a project is rarely a technical decision. It’s emotional, political, and often tied to past promises or personal reputation. The longer something runs, the harder it becomes to admit it’s time to stop. Yet clearing that backlog of half-dead initiatives is often the only way to make room for new ones. So how do you decide when to pull the plug? What signals show that value is gone, and who gets to say so? How can governance encourage honest calls without punishing those who make them? Let’s discuss how to end gracefully, refocus teams, and turn closure into confidence rather than blame. Bullet in the head? Is that how you kill a zombie, or was it a silver bullet in the heart? A closed conversation on how to make progress by learning to stop.
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Belgium 26-3-26 Invitation Only Virtual english
AI projects continue to multiply, but proving their value remains difficult. Most organisations can track activity, not impact. Dashboards count pilots and models, yet few translate to measurable business outcomes. The result is familiar: success stories without clarity on what they actually delivered. The real issue is measurement. Traditional ROI metrics fail when AI changes decisions more than results. Financial indicators miss the operational gains, while qualitative benefits often sound too vague to defend. Without clear evidence, budgets come under scrutiny and confidence erodes. This session focuses on how to connect AI work with business outcomes through structured metrics, governance, and accountability. We’ll explore how value tracking evolves from experimentation to scale, which indicators earn trust at board level, and where measurement stops being meaningful. A closed exchange for comparing methods, tools, and lessons learned in defining, proving, and sustaining AI impact.
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March 24, 2026 Squad Session Invitation Only Physical english
Every organisation has them, projects that keep running long after their purpose has faded. No one remembers who asked for them, but shutting them down feels riskier than keeping them alive. And eventually, people stay assigned, budgets stay allocated, and energy drains into work that no longer matters. Inertia at its finest.
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March 26, 2026 Squad Session Invitation Only Physical english
AI projects continue to multiply, but proving their value remains difficult. Most organisations can track activity, not impact. Dashboards count pilots and models, yet few translate to measurable business outcomes. The result is familiar: success stories without clarity on what they actually delivered.
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March 31, 2026 Squad Session Invitation Only Physical english
Composability sounds elegant in theory: small, independent parts that come together to form something greater, but in practice, it’s messy. What happens when modules overlap, APIs evolve differently across domains, and governance struggles to keep pace? What was meant to simplify architecture sometimes ends up multiplying it.
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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
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Digital Transformation is redefining the future of health care and health delivery. All stakeholders are convinced that these innovations will create value for patients, healthcare practitioners, hospitals, and governments along the patient pathway. The benefits are starting from prevention and awareness to diagnosis, treatment, short- and long-term follow-up, and ultimately survival. But how do you make sure that your working towards an architecturally sound, secure and interoperable health IT ecosystem for your hospital and avoid implementing a hodgepodge of spot solutions? How does your IT department work together with the other stakeholders, such as the doctors and other healthcare practitioners, Life Sciences companies, Tech companies, regulators and your internal governance and administrative bodies?
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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.
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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.
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