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SearchThe adoption of AI and multi-cloud models requires robust networks and unified management. This guide helps identify bottlenecks, hidden costs, and security gaps to ensure operational continuity.
The growth of an SME no longer depends solely on commercial strategy, but on the capacity of its technological infrastructure to support demand. The accelerated adoption of artificial intelligence (AI) and the migration towards multi-cloud environments have transformed business needs. According to Cristian Chinchilla, Technology Director at Telecable, "there are fewer and fewer companies that can operate without a robust technological infrastructure," since critical operations such as billing, data management, and access to AI platforms depend on stable connectivity.
This scenario presents a dual challenge: guaranteeing networks with high availability and low latency, and managing increasingly diverse environments without affecting operational continuity. Complexity has increased because many organizations have incorporated several clouds as a result of independent projects, generating what Francisco Montesinos, regional commercial manager at GBM, defines as "technological islands." The problem is not having several clouds, but managing that diversity so that each new platform does not become an isolated silo.
Despite the availability of advanced tools, there is a significant gap in technological adoption, especially in small and medium-sized enterprises. Data from the "España Empresa Digital" report by the Chamber of Commerce of Spain reveal that, although most companies have basic connectivity, only 23.2% use cloud services (cloud computing) and only 11.2% employ Big Data technologies. In companies with up to 50 employees, this use is practically residual, in contrast to the double or triple penetration in large corporations.
These deficits translate into operational inefficiencies. It is estimated that 90% of companies have difficulties growing and being efficient due to obsolete technology. This obsolescence not only hinders innovation but also increases costs and generates a competitive disadvantage. Furthermore, the lack of adequate infrastructure is one of the main barriers to the growth of the digital economy, along with talent gaps, according to studies by Huawei and Boston Consulting Group (BCG).
Business expansion usually reveals weaknesses in the infrastructure that, if not addressed strategically, lead to an increase in operating expenses. One of the most critical latent challenges is cost control. The flexibility of cloud services facilitates incorporating new capabilities, but it can also make it difficult to determine how much is consumed and the origin of that spending, a situation that is aggravated by the new loads associated with AI.
Without clear cost strategies, IT spending can get out of control. Companies that implement scalable cloud strategies manage to stay within budget while improving their capabilities. Cost optimization is fundamental to converting a capital cost into an operating cost, allowing SMEs to rationalize their investment and access cutting-edge technologies, such as dedicated servers for AI or Blockchain, at accessible prices.
Security represents another critical front. Approximately 43% of cyberattacks are directed at small businesses, and only 14% is prepared to defend itself, according to data from Gran America. Risks increase exponentially with outdated systems and the fragmentation of providers.
In multi-cloud environments, different providers may use their own mechanisms for authentication, authorization, and policy application. This increases the difficulty of maintaining homogeneous security criteria. Scalable cloud solutions offer advanced security functions that protect data and systems from modern cyber threats, but they require unified management to avoid gaps between different platforms.
To correctly size the infrastructure, SMEs must follow an assessment process that identifies weaknesses before they become operational interruptions.
AI applications require a high volume of data and real-time processing. This increases the needs for connectivity and infrastructure capable of supporting applications with higher processing and data access demands, raising the relevance of low latency and high availability.
It is a situation in which different platforms or clouds operate in isolation, with different tools, policies, and processes. This makes management difficult, increases complexity, and can generate security and cost control gaps.
Thanks to technology as a service (TaaS), SMEs can access cutting-edge infrastructures, such as servers for AI or Big Data, through subscription or monthly rental models, without the need to make large initial capital investments or have an internal specialized IT department.
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