Conference Description
Key Takeaways
- Enterprise conference exploring artificial intelligence adoption with emphasis on data sovereignty and organisational flexibility
- Technical focus on hybrid cloud architecture, automation platforms, and open source infrastructure
- Designed for IT decision-makers, enterprise architects, developers, and technology executives across regulated industries
- Programme includes keynotes, customer case studies, AI-focused panels, product demonstrations, and expert consultations
- Takes place in Montevideo, Uruguay on 15 October 2026
Introduction
Red Hat Summit: Connect 2026 Montevideo brings together enterprise technology professionals to examine how organisations can implement artificial intelligence while maintaining control over their data and infrastructure choices. The conference addresses a central tension facing technology leaders today: the pressure to adopt AI rapidly while ensuring that adoption does not compromise data sovereignty or lock organisations into inflexible vendor relationships. As Latin American enterprises accelerate their digital transformation initiatives, the event provides a regional forum for discussing open source approaches to AI, hybrid cloud deployment, and operational automation.
About This Event
This in-person conference takes place at the Hotel Radisson in Montevideo, Uruguay on 15 October 2026. The programme combines keynote presentations with customer impact case studies, technical panels focused on AI implementation, live product demonstrations, and dedicated sessions with subject matter experts. The format balances strategic discussions aimed at business leaders with technical depth for architects and practitioners responsible for implementation.
Red Hat serves as the primary organiser, positioning the event within its broader Summit: Connect series that brings regional technology communities together around shared challenges in enterprise IT modernisation.
AI Sovereignty and the Freedom to Choose
The conference centres on a concept that has gained significant traction among enterprise technology leaders: the ability to deploy AI capabilities without surrendering control over where data resides, how models are trained, and which platforms underpin production workloads. This notion of sovereignty extends beyond regulatory compliance to encompass strategic flexibility—the capacity to shift workloads between environments, avoid proprietary lock-in, and adapt infrastructure as requirements evolve.
For organisations operating in regulated sectors such as finance, healthcare, and the public sector, these considerations carry particular weight. Data residency requirements, audit obligations, and sector-specific compliance frameworks often constrain where AI workloads can run and how training data can be processed. The event examines how open source foundations can provide the transparency and portability that these constraints demand.
Technical Foundations: Hybrid Cloud and Automation
The technical programme explores the infrastructure layer that supports enterprise AI initiatives. Hybrid cloud architecture—the ability to orchestrate workloads across on-premises data centres, public cloud environments, and edge locations—features prominently in the agenda. This approach allows organisations to place AI inference close to data sources while maintaining centralised model training and governance.
Red Hat OpenShift provides the container orchestration platform that underpins many of these hybrid deployments, offering consistent application management regardless of underlying infrastructure. The event includes demonstrations of how containerised AI workloads can move between environments while maintaining operational consistency.
Automation receives substantial attention as organisations seek to manage increasingly complex infrastructure without proportional increases in operational overhead. Red Hat Ansible Automation Platform enables infrastructure-as-code approaches that bring repeatability and auditability to deployment processes. When combined with AI workloads, automation becomes essential for managing model lifecycle operations including deployment, monitoring, and updates across distributed environments.
Red Hat Enterprise Linux serves as the foundational operating system layer, providing the stability and security certifications that enterprise deployments require. The relationship between these components—operating system, container platform, and automation tooling—illustrates how open source ecosystems can deliver integrated capabilities while preserving component-level flexibility.
Industry Context: Open Source in Enterprise AI
The enterprise AI landscape has evolved considerably as organisations move beyond experimental deployments toward production implementations. This maturation brings infrastructure questions to the foreground. Organisations that initially adopted cloud-native AI services are now evaluating whether those choices provide sufficient control over costs, data handling, and long-term flexibility.
Open source AI frameworks have emerged as credible alternatives to proprietary platforms, offering transparency into model behaviour and the ability to customise implementations for specific use cases. However, deploying open source AI at enterprise scale requires robust infrastructure for model serving, monitoring, and governance—capabilities that the conference programme addresses through both strategic sessions and technical demonstrations.
Edge computing adds another dimension to these architectural decisions. As AI inference moves closer to data sources—whether in manufacturing facilities, retail locations, or telecommunications infrastructure—organisations must manage distributed deployments that span multiple environments. The consistency that container platforms provide becomes increasingly valuable in these scenarios.
Security Considerations in AI Deployment
Security threads through multiple aspects of the conference programme, reflecting the heightened attention that AI systems receive from both threat actors and regulators. AI deployments introduce novel attack surfaces including model poisoning, adversarial inputs, and data exfiltration through inference APIs. Organisations must extend their security practices to address these AI-specific risks while maintaining the operational agility that competitive pressures demand.
The open source approach offers certain security advantages, including the ability to audit code, verify supply chain integrity, and apply patches without vendor dependencies. These characteristics align with zero-trust security models that assume breach and emphasise verification at every layer.
Who Should Attend
The conference serves multiple constituencies within enterprise technology organisations. IT decision-makers and technology executives will find strategic content addressing how AI adoption fits within broader digital transformation initiatives. Enterprise architects can explore reference architectures for hybrid AI deployments and evaluate how open source components integrate with existing infrastructure investments.
Developers and DevOps professionals benefit from technical sessions covering application development practices, container orchestration, and automation workflows. System administrators responsible for maintaining production infrastructure can examine operational approaches for managing AI workloads at scale.
The event draws attendees from sectors including financial services, healthcare, automotive, telecommunications, public sector, and media—industries where data sensitivity, regulatory requirements, and operational complexity make infrastructure choices particularly consequential.
Addressing Digital Transformation Challenges
Beyond AI-specific topics, the conference addresses broader challenges that organisations encounter during digital transformation. Legacy infrastructure modernisation, skills development, and organisational change management all influence whether technology investments deliver expected returns. The customer case studies included in the programme provide concrete examples of how organisations have navigated these challenges, offering practical insights that complement the technical content.
The networking opportunities embedded throughout the event allow attendees to exchange experiences with peers facing similar challenges. These conversations often prove as valuable as formal sessions, providing unfiltered perspectives on what works in practice and what obstacles organisations should anticipate.
For technology leaders evaluating their AI strategies, Red Hat Summit: Connect 2026 Montevideo offers a focused opportunity to examine how open source approaches can deliver both capability and control in an era where both matter increasingly.