In 2026, cloud strategy will be pulled in two directions at once: AI-driven demand for fast, reliable data access, and tighter expectations on sovereignty and control.
Experts suggest that tension will reshape decisions about where data lives and when it should move back closer to home. They also expect cloud-first operating models to keep spreading across communications and customer experience, with infrastructure gaining a “voice” through AI-driven optimization.
Underneath it all, networks are shifting toward more flexible, on-demand capacity designed for cloud and AI traffic.
AI and sovereignty push cloud strategies toward repatriation
Fred Lherault, Field CTO EMEA/METCA, Pure Storage
“The dual issues of AI and data sovereignty are driving concerns about where data is stored, and how organizations can maintain trust and guarantee access in the event of any issues. In order to extract value from AI, it’s critical for organizations to know where their most important data is and that it’s ready for use.
“Adding to this are concerns about data sovereignty, which are driving more organizations to reconsider their cloud strategy. Rising geopolitical tensions and regulatory pressure will shape nations’ data center strategies in 2026 to combat this. Governments in particular want to minimize the risk that access to data could be used as a threat or negotiating tactic.”
Cloud-first becomes the default operating model for communications
David Fischer, Chief Sales Officer, Luware
“With the rise of cloud-first strategies, enterprises will reshape how they approach communication infrastructure in 2026. As enterprises move away from legacy on-premises systems, the emphasis will be on shifting toward scalable, agile, and globally deployable cloud environments that support hybrid and remote workforces.
“This evolution enables faster deployment, simplified management, and seamless integration across collaboration ecosystems, allowing organizations to future-proof operations while delivering a more connected customer experience.”
AI gives infrastructure a “voice” and drives self-optimising platforms
David Fischer, Chief Sales Officer, Luware
“It will be up to the market to recognize the benefits of all the cloud-based technologies we already have. The integration of AI into ecosystems offers countless opportunities because users can actively ask “their infrastructure” how it can be better optimized, more secure, or more cost-effective.
“There is industry momentum behind deploying these specific LLM integrations to help users communicate with something that typically lacks a voice. While AI is imperfect, efforts like this help level the playing field.
“Cloud platforms are entering a new era of adaptive, AI-powered infrastructure – systems capable of learning, predicting and optimizing themselves in real time. In 2026 and beyond, these platforms will move beyond automation to true intelligence, dynamically allocating resources, anticipating demand, and routing interactions before customers even make contact.
“Providers that can merge scalability with predictive insight will redefine customer engagement, transforming the contact center into a proactive, self-evolving ecosystem that continually enhances experience and efficiency.”
Capacity becomes on-demand: “adaptive networks” for cloud-era bandwidth
Wayne Lotter, Head of International Networks, Telstra International
“Adaptive networks are the future for cloud-driven demand.”
“Looking ahead to 2026, we’re going to see a further shift in how carriers, enterprises and hyperscalers consume high-bandwidth capacity for their cloud and data center needs. The industry is moving towards “capacity as a service” models (or “adaptive networks”), where customers subscribe to flexible pools of capacity that can be deployed wherever needed across subsea and terrestrial routes.
“This is a significant change from the traditional model of placing individual capacity orders. Instead, customers will work under outcome-based agreements designed to meet the demands of AI and Cloud services. By shifting capacity dynamically across different networks, enterprises will start to get the flexibility and speed-to-market they need.
“As AI and machine learning increasingly enable networks to operate autonomously, offering capacity as a service will become more valuable for customers, since it can quickly and flexibly respond to changing capacity requirements.”
