With Artificial Intelligence (AI) infrastructure spending projected to exceed $200 billion by 2028, it is essential organisations reassess their current infrastructure to accommodate increasingly resource-intensive workloads.
New AI workloads demand scalable storage solutions and low-latency environments for optimal performance. They also require increased scrutiny following the introduction of new regulations, such as the EU AI Act, which imposes stringent requirements for transparency, risk management and regulatory compliance. This adds another layer of complexity for businesses relying on cloud services.
As businesses look to navigate these new requirements, it has become clear that flexibility is the number one priority. Traditionally, businesses have relied on hyperscalers, and while this has dominated the cloud landscape for a long time, solely relying on individual hyperscalers is no longer sustainable. Instead, organisations must transition to a (hybrid- or) multi-cloud approach.
The challenges of a single cloud approach
Relying on a single cloud provider can present challenges, primarily the risk of vendor lock-in. This occurs when organisations become overly dependent on a single cloud provider, making it difficult and costly to migrate workloads to another cloud platform due to proprietary technologies, data transfer costs, compatibility issues, and compliance. It also limits the ability to adapt to changing needs or negotiate better terms.
Furthermore, dependence on a single cloud provider makes organisations vulnerable to the provider’s performance and reliability. This reliance not only restricts flexibility, scalability and innovation but exposes businesses to risks such as service outages, security vulnerabilities or unexpected pricing changes that can disrupt operations.
To address these challenges, organisations must adopt a (hybrid- or) multi-cloud approach, which allows them to have the freedom to distribute their workloads across multiple providers. This reduces dependence on any single vendor, enhancing resilience against outages and pricing fluctuations.
Embracing multiple cloud environments for AI workloads
As AI adoption accelerates, organisations must strategically distribute workloads across multiple cloud environments to address challenges such as resource scarcity, cost optimisation and performance variability. Unlike single-cloud or hybrid approaches, a multi-cloud strategy offers unmatched adaptability and resource diversity. Multi-cloud architectures enable businesses to select the infrastructure optimised to the needs of their workloads, ensuring uptime and redundancy through diversification. This flexibility allows organisations to adapt to changing business needs by switching providers when necessary.
A multi-cloud strategy extends beyond cost efficiency; it enables organisations to build an infrastructure that supports AI initiatives, drives innovation, and secures a competitive edge. These strategies empower organisations to utilise AI services from different providers while avoiding vendor lock-in and ensuring compliance with evolving regulations. By distributing AI workloads, organisations can improve resilience, reduce latency and optimise efficiency in real-time.
The benefits of an AI-driven multi-cloud approach
AI is not the end goal – rather, AI-powered capabilities are a means for organisations to manage and optimise resource performance and spend, while governing operations to ensure compliance. Here’s how:
Enhanced Agility
A significant benefit of an AI-driven multi-cloud approach is enhanced agility. AI can automate tasks, optimising resource allocation and enabling rapid deployment of applications and services. This agility allows organisations to adapt to changing business needs, ensuring they remain competitive and responsive to market demands.
Improved cost optimisation
Cost management is a critical concern for organisations operating in a multi-cloud environment. AI-driven predictive analytics allows organisations to accurately anticipate future cloud expenses based on current and historical usage trends. This approach ensures that cloud investments are fully optimised, eliminating any unexpected expenses and identifying cost-saving opportunities. By enhancing resource utilisation across the multi-cloud environment, AI ensures that spending aligns with business objectives.
Better security and resilience
AI plays a crucial role in enhancing security and resilience by proactively detecting and responding to potential threats. By utilising predictive analytics tools across multi-cloud platforms, AI can automate security responses, significantly reducing risks and ensuring business continuity even during potential outages.
Optimised AI workloads
An AI-driven multi-cloud strategy also ensures the optimisation of AI workloads. AI can identify the most suitable cloud platforms for specific AI workloads, leading to improved performance and efficiency. By matching workloads to the most suitable environments, organisations can maximise the potential of AI. This includes optimising costs through dynamic resource allocation and ensuring scalability without manual intervention.
By embracing an AI-driven multi-cloud approach, organisations can maximise their operations and create an environment that promotes continuous innovation.
Unlocking potential with an AI-driven multi-cloud strategy
AI is transforming cloud infrastructure by driving demand for intelligent automation and seamless integration across platforms. Organisations that continue to rely solely on single-cloud solutions risk inefficiencies, higher costs, limited innovation, and non-compliance with evolving regulations.
Beyond addressing technical demands and regulatory challenges, an AI-driven multi-cloud approach serves as a catalyst for innovation due to its ability to adapt to market changes. Adopting this approach empowers organisations to unlock unparalleled flexibility, scalability and resilience which is a strategic advantage for businesses seeking long-term competitiveness.
Dmitry Panenkov
Dmitry Panenkov is CEO and founder of emma – the cloud management platform.
