NEWS AND PERSPECTIVES

Is your infrastructure ready for AI?

An in-depth analysis of how companies are adopting generative AI, the challenges they face and the strategies for building solid, secure and cost-effective technology infrastructure.

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Introduction: From Curiosity to Practical Implementation

Generative Artificial Intelligence (generative AI) has moved beyond a futuristic promise to become a strategic pillar for companies. What used to be simple curiosity and experimentation now translates into practical implementation with a direct impact on business.

According to a recent Google Cloud report (2025), which surveyed more than 500 global business leaders, 98% of organizations are already experimenting with, developing or using generative AI in production. This widespread adoption is redefining IT strategies and confirms that robust, optimized AI infrastructure is essential to compete in the future.

Finding 1: Generative AI as a Strategic Pillar Across All Sectors

79% of technology leaders consider generative AI to be ‘very or extremely important’ to the continuity of their operations. This view is shared across various industries:

  • IT consulting (91%)
  • Software and hardware (88%)
  • Financial services (72%)
  • Manufacturing (75%)

Investment in generative AI focuses on two fronts: optimizing internal processes and improving the customer experience. In fact, 64% of companies have already achieved a strategic balance by applying it in both areas.

Main current use cases:

  1. Data analysis (50%): turning massive amounts of data into practical information.
  2. Customer service automation (40%): faster, more personalized responses.
  3. Internal process automation (40%): greater productivity and operational efficiency.

Finding 2: The Challenges of Adopting Generative AI

AI-based digital transformation has its challenges. The three main ones are:

  • Security and privacy (62%) Protecting intellectual property and complying with regulations such as the GDPR is a critical priority.
  • Data management and quality (70%) Without reliable data, AI cannot generate valuable results. Integration and availability are key factors.

Cost efficiency (83%) Although AI reduces expenses in the long term, the initial investment in cloud processing resources is high. Strategies such as FinOps and Google Cloud optimization help maintain profitability.

Finding 3: The Ideal Infrastructure for the AI of the Future

To realize the full potential of generative AI, organizations are prioritizing:

  • A solid, scalable platform (45%) The ability to support different hardware (CPU, GPU, TPU) and software environments, adapting to data scientists and developers.
  • Hybrid cloud as the preference (74%) Combining on-premises infrastructure with public cloud offers flexibility and control over sensitive data.
  • Edge computing on the rise (73%) Deploying models at the edge (IoT, mobile, manufacturing, healthcare) to reduce latency and improve privacy.
  • Managed cloud services (98%) Infrastructure complexity drives companies to rely on cloud providers such as Google Cloud, which provide scalability, security and expertise.

Conclusion: Your Next Strategic Move

Generative AI is no longer an option; it is a necessity. Business success will depend on building flexible, secure, scalable and cost-effective AI infrastructure.

Technology leaders must make strategic decisions today to ensure their organization is prepared for a future driven by Artificial Intelligence. The key lies in partnering with reliable cloud providers such as Google Cloud, which can support companies at every step of digital transformation.

Source: Google Cloud (2025). The State of AI Infrastructure. Survey of more than 500 global business leaders conducted between August and September 2024.

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