Just because you’ve been using the cloud for years doesn’t mean you have a cloud strategy. Here are the areas companies should review before taking the next step toward AI.

According to the INE, 44.3% of Spanish companies use cloud services, but most of these continue to consist of basic services such as storage, email, collaboration tools, and SaaS applications. Many of these services were implemented in response to needs such as remote work.

These implementations currently coexist with new business demands, generative AI projects that require very different computing capabilities, and a more complex regulatory environment. Before continuing to expand capabilities or incorporate new AI projects, it is worth taking a moment to review five factors that could shape many of the technological decisions in the coming years.

 

1. Governance and ownership of the cloud environment

The cloud makes it easier for different departments to quickly procure services, deploy new environments, or integrate tools tailored to their specific needs. This can result in a technology landscape that is difficult to manage without a comprehensive overview.

Services procured outside the IT department’s control—known as shadow IT— can account for as much as 30% to 40% of technology spending in large companies. The consequences can range from environments that remain active even though they are no longer in use to duplicate subscriptions or redundant services.

More and more companies are creating roles such as the Cloud Owner to maintain an up-to-date inventory of active services, validate new contracts, and establish common criteria. This ensures visibility and governance over the cloud environment to drive AI projects that are either underway or in the planning stages.

 

2. Financial Management and Cloud Spending Optimization

According to the latest report from Spain DC, installed capacity in data centers in Spain increased by 24% in 2025 and could reach €66.9 billion in investment by 2030. As companies move more workloads to the cloud—particularly those related to AI—their cloud service bills are rising.

The problem is that cloud spending doesn't always grow at the same rate as the value it generates. This is where the FinOps approach comes into play. Beyond serving as a cost-control mechanism, it aims to align cloud consumption with business objectives.

To achieve this, three elements are required: real-time visibility into usage, shared responsibility among the teams using the resources, and ongoing assessment of whether each service delivers the expected value. This enables AI projects to be scaled sustainably and their return on investment to be accurately evaluated.

 

3. Cloud architecture for artificial intelligence environments

Companies often discover the limitations of their cloud infrastructure when they deploy an AI project into production: data scattered across multiple systems, difficulties accessing up-to-date information, excessive application latency…

An AI-ready architecture requires verifying that the following requirements are met:

• A data governance strategy that makes it possible to know where the information is located, what its quality is, how it is updated, and who can use it.
• A flexible computing layer designed to handle different workloads.
• MLOps processes—that is, procedures and tools for managing AI models once they move from the pilot phase to production environments.

Furthermore, these factors have direct implications for digital sovereignty and regulatory compliance in multi-cloud environments. As a result, many companies are adopting distributed architectures that combine multiple providers to strike a balance between performance, data control, and regulatory requirements.

 

4. Data sovereignty and regulatory compliance

Many companies signed their cloud contracts with a focus on availability, scalability, and price. Since then, the landscape has changed: it is no longer enough to know whether data is in the cloud, but exactly where it is, under which jurisdiction, and what happens when it is used to train or feed artificial intelligence systems.

The AI Act, which will take effect in 2026, along with the Data Governance Act and stricter rules on international data transfers, has meant that decisions previously made by the IT department now require legal justification.

It is necessary to review where data is stored based on its type, what the clauses regarding the outsourcing of data processing in cloud contracts stipulate, and how AI systems are classified based on risk. The information needed to meet these requirements is often scattered across various departments, vendors, and platforms, which means the issue shifts from a legal one to a management one.

 

5. Operational Resilience and Business Continuity

According to Eurostat, one in five European companies has experienced cybersecurity incidents in the past year that have affected their systems or data. However, only one in three had formal procedures in place to manage them. While system availability is usually restored quickly, challenges arise when it comes to restoring critical services within the expected timeframe.

It is necessary to review when the recovery plans were last tested, whether maximum recovery times have been established for each critical service, what dependencies exist between applications, and who is responsible for coordination.

Resilience and business continuity do not depend on the chosen cloud architecture or the provider behind it. The key is to have a proven plan in place, with clear responsibilities and staff capable of executing it when necessary.

Review and plan your cloud strategy at Cloud & AI Infrastructure 2026

The five areas we have discussed (governance, spend management, AI architecture, sovereignty and compliance, and business resilience and continuity) will be key topics at Cloud & AI Infrastructure Madrid, taking place on November 4 and 5 at IFEMA Madrid as part of Tech Show, the largest professional IT event in Southern Europe.

With more than 60 exhibitors, nearly 60 speakers, and an expected attendance of over 3,000 professionals, the event brings together executives and leaders in technology, infrastructure, data, and business to discuss real-world case studies on multicloud, AI cloud platforms, automated FinOps, cloud resilience, and data governance, among other topics.

If you’re reviewing your strategy in 2026, Cloud & AI Infrastructure 2026 is the perfect forum to compare approaches, learn from other companies’ experiences, and understand the direction in which cloud strategies are evolving across all sectors.