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Belgium 10-09-2026 Squad Only Physical english

Building the Infrastructure AI Needs: From computer and data access to scalability, cost control, and operational readiness.

AI is moving from pilots into operational use, and the infrastructure question is becoming more concrete. The challenge is deciding what needs to be built, expanded, controlled, or delayed as usage grows. Three pressure points usually appear first. - Compute capacity requires careful planning: teams need enough GPU, cloud, or specialised processing power, while keeping utilisation and cost under control. - Data movement becomes more demanding: AI needs access to data across systems, with latency, security, integration, and quality managed from the start. - Operational control becomes essential: monitoring, access rights, resilience, cost visibility, and ownership need to scale with usage. The working question is simple: how do we support AI at scale while keeping infrastructure efficient, governed, and financially sustainable? If you are working through these choices, let’s compare approaches with others facing similar constraints.

Belgium 15-09-2026 Squad Only Virtual english

Turning AI Pilots into Daily Workflows: How to move from experimentation to adoption by redesigning work, ownership, controls, and habits.

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.

Belgium 17-09-2026 Country Members Physical french

Les Rencontres: CTO: Le Saint Graal?

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.

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CA-GIP scales with Red Hat Ansible Automation Platform

Crédit Agricole Group Infrastructure Platform (CA-GIP) provides IT infrastructure services and production support for the group’s insurance, corporate banking, and investment banking businesses. To scale automation across tens of thousands of servers, CA-GIP replaced its community automation solution with Red Hat Ansible Automation Platform.

Benefits:

Achieved return on investment (ROI) in just one year
Automated operations for 20,000 Linux servers in the equivalent of one employee’s work hours
Simplified adoption of new automation capabilities
Improved infrastructure security with a central automation approach

Founded in 1894, Crédit Agricole Group is the largest cooperative financial institution and tenth largest bank in the world. The bank established the Infrastructure Platform team (CA-GIP) in 2019 to manage its IT infrastructure and technology and services operations for its insurance, corporate banking, and investment banking services.

As demand for digital financial services rapidly increased, CA-GIP sought to improve the group’s operational efficiency to keep pace. The group decided to replace its community Ansible solution with cost-effective technology that could integrate a variety of systems for current and future business needs. Additionally, CA-GIP sought to support reuse of established scripts as commands or application programming interfaces (APIs) to save time on repetitive automation management tasks and reduce risk of human error.

Adopting stable, supported enterprise automation technology from Red Hat

Based on its successful past adoption of Red Hat platform technology, CA-GIP decided to adopt Red Hat Ansible Automation Platform to manage infrastructure provisioning, configuration, and patching.

Red Hat Ansible Automation Platform is an agentless solution for managing complex deployments and repetitive tasks across enterprise environments of any scale. Ansible's simple YAML language, in the form of Ansible Playbooks, lets teams across an organization share, vet, and manage automation content. In the first phase of CA-GIP’s deployment, Ansible Automation Platform was used to automate processes across more than 20,000 Linux servers.

Although it had already applied automation to support a variety of business needs, CA-GIP engaged Red Hat Consulting to work with the group’s senior engineering staff and help its teams quickly build related skills.

Investing in operational efficiency across teams

Achieved return on investment (ROI) in just one year
Significantly reduced automation effort and resources, achieving automated operations for 20,000 Linux servers in the equivalent of one employee’s work hours
Simplified adoption of new automation capabilities with Red Hat OpenShift operators, modular software for packaging, deploying, and managing Kubernetes-native applications
Improved infrastructure security with supported enterprise technology and a central automation approach across DevOps teams
Improved talent management with less need for proprietary specialists

Planning an improved IT experience with automation-centric DevOps

After its initial success with its enhanced, automation-centric DevOps approach, CA-GIP plans to expand its Red Hat Ansible Automation Platform to a total of 45,000 Linux and Microsoft Windows servers.

“Red Hat offered us a path to our future goal of providing a seamless experience to all of CA-GIP’s DevOps teams through a single technical solution,” said Liozon.

Technologies

Red Hat Ansible Automation Platform

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