Businesses looking to support their artificial intelligence (AI) initiatives in the cloud should approach these issues strategically. The cloud has become an essential IT element for the vast majority of businesses. In fact, a 2024 Flexera study found that 89 percent of organizations have implemented a multicloud architecture. As artificial intelligence becomes an effective tool across numerous industries, the cloud will play a massive role in its adoption and use.
The Integration of AI and Cloud Computing
The integration of AI and cloud computing is transforming the technological landscape, creating new opportunities for businesses to innovate and compete. IT leaders expect this combination to create a powerful new dynamic. In 2024, Deloitte research found that 90 percent of cloud decision-makers expect the cloud, combined with other technologies such as AI, to serve as a “force multiplier” for their digital strategy. This presents businesses with a major opportunity.
Michael Brenner of Nutanix emphasized the importance of this relationship in a 2023 blog post: “Enterprise leaders should strive to understand how the rapidly expanding field of AI can build a relationship with cloud computing technology that spurs ever greater innovation.” However, for businesses to maximize this opportunity, cloud providers must be ready to meet the huge demand for AI-enabled services, and businesses must make their AI-based cloud decisions strategically.
The Demands of AI on IT Infrastructure
As AI becomes more widely used, the millions of applications that rely on it will create vast amounts of data. Nidhi Chappell, general manager of Microsoft Azure’s AI infrastructure, told The Wall Street Journal, “There is insatiable demand” for running large language models, especially in industries such as finance and manufacturing.
Organizations need IT infrastructure that can support this additional weight, including networks and storage that can handle huge amounts of data and computing chips that can meet the processing demands of AI. Steve McDowell, principal analyst at NAND Research, highlighted the operational challenges: “There’s a lot of hype around AI, and that impacts IT. [They] need to figure out how to build the infrastructure to support it because traditional compute does not account for it. We’re seeing thousands of experiments across organizations, and IT has to step up and support those often in short order, so it’s a challenge operationally.”
Cloud Providers Rising to the Challenge
Businesses can rely on cloud providers to shoulder some of this load. According to The Wall Street Journal, hyperscale cloud providers — including Amazon Web Services, Microsoft Azure, and Google Cloud Platform — are taking steps such as deploying AI-optimized server clusters to help them prepare for the demands of AI applications.
Companies looking to use the cloud to handle AI workloads must choose the right provider because many applications rely on different microservices for different functions, and a problem with one provider could have far-reaching effects. Solutions that can establish seamless connectivity between cloud and on-premises environments, such as IBM’s Hybrid Cloud Mesh, can help companies mitigate such issues.
Enhancing Staff Expertise in AI
As businesses increase their investments in AI and the cloud, they need to take steps to enhance their chances of success. To begin, they need to improve the levels of staff expertise in AI. A post on CIO.com notes, “Business and tech leaders must build for the future now. Working with people managers to develop the skills stack to support the tech stack ensures organizations can take advantage of current and future AI capabilities — all powered by data.”
Investment in training and development is crucial. According to a survey by Gartner, by 2025, 75 percent of organizations will have initiated competency development programs for their employees in AI, up from 10 percent in 2020. This reflects the growing recognition of the importance of skilled personnel in driving AI success.
Optimizing Hybrid Cloud Strategies
Businesses should also focus their hybrid cloud strategies to support their AI initiatives. A strategic approach can help companies optimize their AI workloads for efficiency and productivity. Dion Hinchcliffe of Constellation Research writes, “Bursty workloads can reside in the public cloud, while mission-critical, always-on AI workloads can be migrated to a private cloud environment, optimizing cost and performance.”
Balancing workloads between public and private clouds can significantly enhance performance and reduce costs. For example, a financial services company might use the public cloud for data-intensive AI training tasks while keeping real-time fraud detection systems on a private cloud to ensure low latency and high security.
Compliance and Regulatory Considerations
Organizations also need to consider the compliance implications of their cloud AI efforts. The European Union’s Artificial Intelligence Act, adopted in 2023, establishes rules for data quality, transparency, human oversight, and accountability in the use of AI, and sets steep penalties for noncompliance.
Navigating these regulatory challenges is essential for businesses operating in multiple jurisdictions. According to a report by Forrester, 40 percent of companies in the EU expect significant changes in their AI governance and compliance processes due to the new regulations. Ensuring compliance not only avoids legal penalties but also builds trust with customers and stakeholders.
The Role of Cloud Providers in AI Readiness
Cloud providers play a pivotal role in helping businesses achieve AI readiness. They offer the infrastructure, platforms, and services needed to support AI initiatives. However, the readiness of cloud providers to support AI workloads varies, and businesses must carefully evaluate their options.
When evaluating cloud providers, businesses should consider factors such as the provider’s AI capabilities, the availability of AI-optimized infrastructure, and the provider’s track record in supporting AI deployments. A survey by IDC found that 58 percent of businesses consider the AI capabilities of a cloud provider a critical factor in their selection process.
The Future of AI in the Cloud
The future of AI in the cloud looks promising, with continued advancements in technology and increased adoption across industries. According to a report by MarketsandMarkets, the AI in cloud computing market is expected to grow from $4.2 billion in 2020 to $22.6 billion by 2025, at a Compound Annual Growth Rate (CAGR) of 39.7 percent.
Several emerging trends are shaping the future of AI in the cloud, including the development of AI-as-a-Service (AIaaS) platforms, the integration of AI with Internet of Things (IoT) devices, and the use of AI for enhanced cybersecurity. These trends highlight the expanding role of AI in driving innovation and business transformation.
Conclusion
The combination of AI and cloud computing is creating new opportunities for businesses to innovate and compete. However, realizing these opportunities requires a strategic approach to managing the demands of AI on IT infrastructure, enhancing staff expertise, optimizing hybrid cloud strategies, and navigating compliance challenges. By carefully evaluating their cloud providers and adopting best practices, businesses can position themselves for success in the rapidly evolving landscape of AI and cloud computing. As businesses move forward with their AI initiatives, they must remain agile and adaptable, continuously assessing and refining their strategies to stay ahead of the curve. The journey to AI readiness is complex, but with the right approach, businesses can unlock the full potential of AI and drive meaningful outcomes.