Cloud Computing

Technical

Cloud computing is the delivery of computing services -- servers, storage, processing power, databases, networking, and software -- over the internet on a pay-as-you-go basis rather than owning and maintaining physical infrastructure. Cloud computing provides the scalable, elastic...

Detailed Explanation

Cloud computing is the delivery of computing services -- servers, storage, processing power, databases, networking, and software -- over the internet on a pay-as-you-go basis rather than owning and maintaining physical infrastructure. Cloud computing provides the scalable, elastic infrastructure that most enterprise AI workloads require: the ability to spin up hundreds of GPUs for a training run and release them when finished, to scale inference endpoints up and down with demand, and to access managed AI services without building everything from scratch. The major cloud providers (AWS, Azure, Google Cloud) offer comprehensive AI/ML platforms that reduce the infrastructure burden on organizations. However, cloud dependency creates vendor concentration risk and ongoing cost obligations that transformation leaders must manage through multi-cloud strategies and AI FinOps practices.

Why It Matters

Understanding Cloud Computing is essential for organizations pursuing responsible AI transformation. In the context of enterprise AI governance, this concept directly impacts how organizations design, deploy, and oversee AI systems particularly within the Technology pillar. Without a clear grasp of Cloud Computing, organizations risk creating governance gaps that undermine trust, compliance, and long-term value realization. For AI leaders and practitioners, Cloud Computing provides the conceptual foundation needed to make informed decisions about AI strategy, risk management, and stakeholder engagement. As regulatory frameworks such as the EU AI Act and standards like ISO 42001 mature, proficiency in concepts like Cloud Computing becomes not merely advantageous but operationally necessary for any organization deploying AI at scale.

COMPEL-Specific Usage

Technical concepts map to the Technology pillar of the COMPEL framework. They are most relevant during the Model stage (designing AI system architecture and governance controls) and the Produce stage (building, testing, and deploying AI solutions). COMPEL ensures that technical decisions are never made in isolation but are governed by the broader organizational context of People, Process, and Governance pillars. The concept of Cloud Computing is most directly applied during the Model and Produce stages of the COMPEL operating cycle. Practitioners preparing for COMPEL certification will encounter Cloud Computing in coursework aligned with the Technology pillar, and should be prepared to demonstrate applied understanding during assessment activities.

Related Standards & Frameworks

  • ISO/IEC 42001:2023 Annex A.5 (AI System Inventory)
  • NIST AI RMF MAP and MEASURE functions
  • IEEE 7000-2021