Executive Summary: ISG Provider Lens™ Multi Public Cloud Services - U.S. 2024
17 Dec 2024
The individual quadrant reports are available at:
ISG Provider Lens™ Multi Public Cloud Services - FinOps Services and Cloud Optimization - U.S. 2024
ISG Provider Lens™ Multi Public Cloud Services - Managed Services - Large Accounts - U.S. 2024
ISG Provider Lens™ Multi Public Cloud Services - Managed Services - Midmarket - U.S. 2024
ISG Provider Lens™ Multi Public Cloud Services - SAP HANA Infrastructure Services - U.S. 2024
AI-led innovation and cost optimization have become integral to cloud service engagements
Until last year, we saw public cloud services grow mainly due to innovation, faster time to market and improved customer experience. But, in the last four quarters, we saw AI technologies driving the growth of cloud services in the U.S. As enterprises increasingly recognize the transformative potential of AI, they are turning to cloud platforms to access the necessary computing power, storage and tools to develop and deploy AI applications. The ability to scale resources on-demand, combined with the wide range of AI-specific services offered by cloud providers, has made cloud computing an attractive option for enterprises seeking to leverage AI. This increased demand for cloud services, fueled by AI adoption, drives significant growth in the U.S. cloud services market, benefiting both cloud infrastructure providers and service providers.
Additionally, hyperscalers are investing heavily in AI-specific infrastructure and services, further accelerating the adoption of AI in the U.S. This symbiotic relationship between AI and cloud computing is expected to continue driving significant growth in the future.
When it comes to generative AI (GenAI), it is still in its early stages. However, it is rapidly gaining traction as service providers and hardware manufacturers are investing significantly in this space. Companies such as NVIDIA, Google and Microsoft are leading the charge with billions allocated to AI research, infrastructure and hardware development. Enterprises, meanwhile, are cautiously exploring the potential of GenAI, primarily through proofs of concept (POCs), to better understand its practical applications and potential implications on business and society. Many enterprises
are testing GenAI in areas such as content creation, customer service automation and personalized marketing. However, adoption remains tentative, with enterprises focused on validating use cases before committing fully to broader implementations. Enterprises are turning to service providers to help guide them through these early stages with pilot projects and demonstrate value. Although AI and GenAI technologies show potential across various sectors, ranging from finance and healthcare to media, it is clear that enterprises are still in an experimental phase. The combination of high initial costs, unproven long-term benefits, and ethical concerns around AI-generated content keeps many of them from fully embracing GenAI at this time. Nonetheless, as technology matures and success stories emerge from early adopters, GenAI is poised to transform how enterprises operate in the coming years. It will also boost the overall cloud infrastructure services market, which is poised to reach $1 trillion in the next few years.
Based on ISG’s recent estimates, we have observed that the overall cloud services market in the Americas has grown by approximately 15 percent in Q2 2024 compared to last year, reaching an ACV of $7.4 billion. However, when we look at the global figures, cloud services growth was 11 percent during the same period. This indicates the Americas outpaced the global average in cloud services growth for the quarter. In the ISG Index™ report for the Americas market, ISG reported that the combined market (managed services and XaaS) witnessed a 10 percent increase in Q2
2024, with the ACV reaching $12.1 billion. We also observed that the demand for managed services is sluggish, with ACV rising only 3 percent to $4.7 billion in the second quarter. The number of managed services contracts decreased by nearly 6 percent from the prior year, totaling 347 deals. Within Managed Services, the ITO market declined by 4 percent to $3.4 billion, while the BPO market surged by 25 percent.
Recently, ISG rolled out the Star of Excellence™ program, which is based on the Voice of the Customer concept. Here, providers are rated on six parameters, namely Service Delivery, Governance and Compliance, Collaboration and Transparency, Innovation and Thought Leadership, People and Culture Fit, and Business Continuity. The scores and data come from the Star of Excellence™ study that measures CX with providers based on direct client feedback. ISG found that the average provider CX score for the public cloud domain in North America was 67.37 in 2023. Persistent Systems, HCLTech, LTIMindtree, PwC and Cognizant were the top five providers with above-average CX scores. PwC won the overall cloud computing Star of Excellence™ award for 2023.
In today’s highly competitive and rapidly evolving market landscape, cost optimization remains a top priority for enterprises. With the widespread adoption of cloud technologies, businesses are under increasing pressure to optimize their IT spending while ensuring scalability and performance. Enterprises are looking for immediate cost-saving strategies to balance the growing demands of digital transformation with tight budgets. This urgency is driven by several factors, including the need to maximize ROI, mitigate economic uncertainties and stay ahead of competitors.
While public cloud infrastructure offers immense flexibility and innovation potential, it often leads to complex billing structures and unexpected costs if not managed effectively.
As a result, enterprises actively seek ways to reduce these expenses by optimizing resources through FinOps principles of accurate allocation, rightsizing workloads and eliminating underutilized assets. Moreover, the rise of FinOps frameworks and principles for cloud financial management has highlighted the importance of cross-functional
collaboration between engineering, finance and operations teams to drive continuous cost optimization. Organizations can achieve significant cost savings by implementing best practices such as automated cost monitoring, adopting reserved or spot instances, and optimizing storage and computing resources.
GreenOps and sustainable FinOps: We also see a growing trend toward GreenOps and sustainable FinOps in the future. Sustainable FinOps extends the typical cloud resource optimization approach toward integrating sustainability metrics into financial decisions, ensuring that cloud spending is cost effective and environmentally conscious. In a sustainable FinOps model, enterprises track not only the financial impact of their cloud infrastructure but also its carbon footprint. This encourages U.S. enterprises to adopt practices that reduce energy consumption by following several methods such as choosing energy-efficient cloud regions and data centers, leveraging serverless computing and auto-scaling to minimize unused resources, and optimizing workloads to reduce computational waste. By aligning cloud spending with sustainability goals and GreenOps philosophies, enterprises can make informed decisions that reduce the impact and cost of IT and cloud operations and contribute to their environmental, social and governance (ESG) commitments.
VMware exit strategies: Enterprises were also reaching out to us to get guidance on tackling the higher licensing costs and support fees for VMware solutions after its acquisition by Broadcom. Additionally, Broadcom’s focus on
cost-cutting could lead to reduced innovation and slower development of VMware’s products. Enterprises heavily reliant on VMware are also worried about vendor lock-in, especially as Broadcom’s future direction remains unclear.
Furthermore, there is anxiety about possible reductions in customer support, which could affect business continuity for those deeply embedded in the VMware ecosystem. To address these concerns, service providers are helping enterprises develop exit strategies from VMware by guiding cloud migrations to public cloud platforms such as AWS, Microsoft Azure and Google Cloud. Hybrid cloud and multicloud strategies are being introduced to reduce reliance on VMware, while open-source virtualization alternatives such as KVM are being explored to avoid vendor lock-in. Service
providers are also promoting containerization technologies as modern alternatives to traditional virtualization, ensuring greater flexibility. Additionally, comprehensive exit planning and managed services are offered to assist businesses in transitioning smoothly and efficiently from the VMware ecosystem.
GenAI for cloud operations: As GenAI becomes more popular and in demand, we see that providers leverage this to their advantage in managing public cloud operations by automating tasks, improving efficiency and enhancing decision-making capabilities. It can help in the following ways:
● It can automate infrastructure management by dynamically optimizing resource allocation and provisioning based on usage patterns and demand while offering cost-optimization strategies by analyzing consumption data and generating savings recommendations.
● In security, AI can detect threats in real time and generate proactive responses.
● It can also automate DevOps workflows by generating code, scripts and testing scenarios, accelerating development cycles.
● AI-driven monitoring enhances cloud performance by predicting maintenance needs and reducing downtime.
● AI can personalize cloud service recommendations, manage hybrid and multicloud environments, and improve
disaster recovery planning by simulating failure scenarios and generating optimized recovery strategies.
GenAI enables enterprises to optimize costs, enhance security and scale operations efficiently, making it a powerful tool for modern cloud environments.
Hindrances to GenAI-led operations: There are also challenges to the benefits mentioned above. Some key issues are the unpredictability and potential for inaccurate outputs, leading to misconfigurations and inefficiencies in resource allocation or security settings. Additionally, the lack of human oversight and explainability in AI-driven decisions raises concerns about accountability, trust and compliance, especially with regulatory requirements such
as GDPR or HIPAA. Security is one of the major concerns, as AI could unintentionally expose vulnerabilities or mismanage access controls. GenAI may also struggle to optimize cloud performance dynamically and risks overprovisioning or under-provisioning resources, leading to cost overruns. Furthermore, GenAI models can suffer from biases, data limitations and difficulties integrating with legacy systems while potentially placing users in vendorspecific solutions. Lastly, as cloud services rapidly evolve, AI models require constant updates, adding to the complexity of managing infrastructure effectively and, most importantly, the high costs to run these power-hungry
advanced systems, which are taking a toll on the environment and people.
While GenAI helps in the above-stated benefits, we also need to be cautious about how this can backfire; therefore, it must be used with a thorough and thoughtful approach that looks at the long-term horizon.
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