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Artificial Intelligence (AI) has become a core business imperative for virtually all organisations. The coming wave of Agentic AI will further solidify the urgency of deploying these transformative technologies. However, the reliance on hyperscale public clouds for sensitive AI workloads often introduces unacceptable risks regarding data sovereignty, intellectual property (IP) control, and regulatory compliance (e.g., EU AI Act, GDPR). Furthermore, the unpredictable nature of public cloud consumption models, coupled with soaring data egress costs, creates major barriers to achieving sustainable, enterprise-wide AI at scale. The question facing CIOs is clear: How do you build a secure, compliant AI factory that delivers predictable ROI without sacrificing performance?

How can you maintain complete control, ensure compliance and keep costs under control while unlocking the transformative power of AI, tailored to your specific needs? Join us during this exclusive CIONET Round table for a peer-to-peer dialogue focused on key questions such as:

• Data Sovereignty & Risk: Is Private AI infrastructure the only viable path for CIOs to achieve true data sovereignty and eliminate unmanageable regulatory risk when running sensitive AI workloads?
• Investment & Predictability: At what point does the Total Cost of Ownership (TCO) of a private, dedicated AI solution yield better returns than the unpredictable, scaling usage fees and egress costs of a public cloud model? When do you want to opt for private pay per use models? Help us analyse the trade-off between large initial capital expenditure and the long-term, predictable Total Cost of Ownership. 
• Performance & Implementation: Can managed services and customised infrastructure (GPUs, network fabrics) accelerate the time-to-value for mission-critical AI applications demanding ultra-low latency and seamless integration with existing enterprise IT systems?