Strong demand for generative AI and machine learning (ML) is impacting and reshaping cloud adoption strategies across industries. Companies are migrating more workloads to the cloud to leverage the scalability and processing power required to run advanced AI models.
The rise in AI-driven solutions, from natural language processing to predictive analytics, is pushing organizations to explore more comprehensive and robust cloud infrastructures—in a push to both modernizing IT and align with business objectives that prioritize innovation and data-driven decision-making.
Companies race to the cloud to fuel AI growth
Enterprises are turning to the cloud in flocks to meet their AI and ML needs. Cloud platforms offer the computing power and flexibility needed to deploy and scale AI models quickly, making them key for businesses focusing on advanced analytics and automation.
In 2024, 63% of global IT leaders reported accelerated cloud adoption, up from 57% in 2023, signaling a clear shift in priorities.
The data comes from a survey of 821 global IT leaders responsible for cloud procurement, conducted by Foundry. These leaders are at the leading edge of decision-making in cloud investments, making sure businesses have the infrastructure required to support emerging AI tech.
Growth here comes despite ongoing challenges, including tech talent shortages and rising operational costs. Many enterprises recognize that AI’s potential to improve efficiencies and open new revenue streams far outweighs the investment hurdles.
With more AI use cases emerging, especially in customer experience, automation, and supply chain optimization, businesses are intensifying their reliance on cloud services.
Cloud investments soar as companies expand IT budgets
As cloud technology becomes more central to AI and ML strategies, companies are allocating a growing portion of their IT budgets toward cloud investments. Over 25% of IT budgets are now earmarked for cloud services, despite cost pressures and talent shortages.
On average, businesses are expected to spend $95 million on cloud technology this year, reflecting the importance of cloud in their overall IT strategy.
Two-thirds of companies are planning to invest a large portion of their cloud budgets in AI and ML platforms—pointing out how cloud services are increasingly seen as key enablers of innovation, providing the infrastructure to support next-generation AI tools that are transforming industries.
Major cloud providers expand infrastructure to meet demand
The growing demand for cloud services, fueled by the adoption of AI and ML, has led major providers to scale up their infrastructure rapidly.
AWS, Microsoft, and Google Cloud, three of the largest cloud providers, are investing heavily in new data centers to accommodate the increasing workloads their clients are migrating to the cloud.
Tech titans drive data center boom as cloud use surges
In the first half of the year, AWS, Microsoft, and Google Cloud ramped up their data center construction efforts to meet the surging demand—driven largely by plummeting vacancy rates in their existing facilities, further reflecting the strong growth in cloud usage.
Leading companies have recognized that expanding capacity is key to keeping up with the rising number of organizations moving to the cloud for their AI-driven projects.
The construction boom in data centers increases capacity and improves cloud providers’ ability to offer low-latency, high-performance services, which are a must-have for enterprises running real-time AI applications.
Cloud spending grows 20% annually and shows no signs of slowing
Cloud consumption has been increasing at an impressive rate of 20% year-over-year for the past nine months—as reported by Synergy Research Group—and driven by expanding usage of cloud-based AI and ML applications across industries.
IDC predicts that this growth will continue at the same pace through 2028, with annual cloud spending projected to exceed $800 billion by the end of this year.
This steady increase in cloud spending reflects how deeply embedded cloud services have become in corporate strategies. Enterprises are migrating existing workloads to the cloud while also building new applications specifically designed to take advantage of cloud-native capabilities like AI and edge computing.
Cloud’s role grows with AI and edge technologies taking the lead
Cloud services are evolving beyond their original infrastructure-as-a-service offerings. Today, they include a wide range of solutions that incorporate edge computing, AI, and other advanced technologies to meet the changing needs of businesses.
This evolution is being driven by companies looking to deploy more intelligent, real-time applications that can process data at the edge while using cloud-based AI capabilities.
Cloud services evolve as AI and edge computing take the spotlight
Forrester reports that the traditional definition of cloud services has expanded to include cutting-edge technologies such as edge computing and generative AI-augmented services—now spanning across operations and application development to support organizations in deploying faster, more intelligent solutions.
This shift is particularly evident in industries like manufacturing and logistics, where real-time data processing is critical.
Edge computing allows data to be processed closer to where it is generated, reducing latency and improving the speed of AI-driven decision-making. At the same time, cloud-based AI services help companies scale their machine learning models quickly and effectively, providing the best of both worlds.
AI adoption skyrockets in cloud-based solutions
2024 has seen a surge in cloud-based AI product adoption, reaching what Forrester calls a “fever pitch.” Companies are integrating AI into their cloud platforms at an unprecedented rate, driven by the need to automate processes, gain deeper insights from data, and improve customer experiences.
Whether through AI-powered chatbots or predictive analytics, organizations are finding new ways to leverage cloud-based AI to improve efficiency and drive growth.
Businesses confront new challenges in rapid cloud adoption
Despite the clear advantages of moving to the cloud, businesses are facing new challenges as they accelerate their adoption of cloud services, especially for AI and ML workloads. From cost constraints to security concerns, IT leaders must manage great complexity to make sure their cloud strategies succeed.
Companies weigh their options for running AI workloads
IT leaders remain divided on the best infrastructure for running AI workloads. A survey from Parallels shows that 30% of respondents prefer public cloud, while a nearly equal percentage favor a hybrid approach, combining cloud and on-premise infrastructure. At the same time, 24% opt to run their AI workloads on private data-center clouds.
Hybrid and private cloud options offer more control over data and infrastructure, but can be more complex and costly to maintain.
Diversity in preferences here has highlighted the complexity of deploying AI at scale. Public cloud offers flexibility and scalability, but some organizations are hesitant due to concerns about data privacy and control.
Rising budgets spark concerns over cloud costs
Despite increasing budgets, nearly 50% of IT leaders are concerned about rising cloud costs. As cloud services expand and companies migrate more workloads to the cloud, costs can spiral out of control, especially if not managed carefully—prompting many organizations to revisit their cloud strategies and optimize their spending.
Security and compliance issues keep cloud leaders on edge
Cloud security remains a top concern for IT leaders, with 35% of respondents expressing worries about compliance and data protection. As businesses move sensitive data and mission-critical workloads to the cloud, they must make sure their cloud environments meet strict regulatory requirements and are protected against cyber threats.
Skill shortages and integration headaches slow cloud progress
Many organizations are struggling with IT system integration roadblocks and a shortage of cloud engineering skills. These challenges are creating barriers to full cloud adoption, as companies find it difficult to implement cloud services effectively and scale their operations.
Making sure the right talent and tools are in place is an absolute for businesses to fully realize the benefits of cloud tech.
Final thoughts
As the cloud becomes the foundation for AI innovation, the question isn’t whether your business will adopt it, but how effectively you will leverage it. Are you ready to rethink your cloud strategy, balance costs, security, and talent needs, and push your brand to the leading edge of AI-driven transformation?
