Core Insights - U.K. enterprises are increasingly adopting AI-native multicloud environments to enhance agility, compliance, and cost transparency amid economic uncertainty and tighter regulations [1][2] Cloud Strategy and Transformation - British enterprises are balancing governance, cost optimization, and innovation in their cloud strategies, with a focus on digital sovereignty and generative AI (GenAI) adoption to improve productivity and operational resilience [2][3] - The 2025 ISG Provider Lens Multi Public Cloud Services report highlights a pivotal phase of cloud transformation driven by GenAI deployments, sovereign infrastructure mandates, and automation-focused operating models, particularly in finance, healthcare, and manufacturing sectors [2][5] Automation and AI Integration - A growing number of U.K. enterprises are embedding autonomous agents into workflows, utilizing GenAI for documentation, incident resolution, and knowledge retrieval, which streamlines operations and reduces manual effort [3][4] - As agentic automation matures, it is reshaping expectations around productivity, observability, and operational resilience, making AI integral to managing and operating cloud environments at scale [3] Financial Management and Governance - FinOps is evolving from a cost control function to a core governance discipline, with increased importance on cost transparency and financial accountability in multicloud environments [4] - Enterprises are focusing on cost optimization and predictive budgeting based on service level agreements (SLAs) to manage spending effectively while sustaining AI-driven cloud adoption [4] Regulatory Compliance and Digital Sovereignty - Digital sovereignty requirements are accelerating the adoption of jurisdictional controls, with enterprises implementing Hold Your Own Key (HYOK) models and strict data residency policies to meet regulatory obligations [5] - These measures are particularly crucial for enterprises in highly regulated sectors such as finance, healthcare, and manufacturing [5] Market Trends and Provider Evaluation - The report evaluates the capabilities of 61 providers across various quadrants, identifying leaders such as Computacenter and Rackspace Technology in four quadrants each, and other notable firms like Accenture and Capgemini in three quadrants [8][9] - Rising stars in the market include Hexaware, Kainos, LTIMindtree, Mphasis, and TCS, recognized for their promising portfolios and high future potential [10]

Core Insights - Rackspace Technology has been recognized as a leader in three quadrants of the 2025 ISG Provider Lens™ Multi Public Cloud Services Report for the U.S, highlighting its capabilities in AI-driven cloud transformation and multicloud operations [1][7] Group 1: Company Positioning - Rackspace Technology is positioned as a leader in Managed Services - Midmarket, Consulting and Transformation Services - Midmarket, and FinOps Services and AI-driven Optimization [7] - The company focuses on empowering midmarket businesses through AI-led automation and security, enabling seamless management of multicloud environments [2][3] Group 2: Service Offerings - Rackspace Technology integrates AI, automation, and advanced FinOps optimization frameworks into its service offerings, which helps enterprises modernize and manage their cloud environments effectively [1][2] - The company emphasizes advisory-led transformation combined with AI-powered automation to optimize costs and enhance security for its customers [3][4]

Core Insights - Apptio, an IBM company, has launched next-generation FinOps solutions aimed at enhancing visibility and optimizing cloud costs in AI-driven environments, addressing the increasing pressure on IT leaders to manage rising costs effectively [2][3] - IDC projects that global enterprise investments in AI infrastructure will reach $571 billion by 2026, yet 55% of business leaders report lacking the necessary information to evaluate technology spending effectively [2][3] FinOps Solutions - The new FinOps solutions are designed to provide organizations with real-time visibility, financial accountability, and management of cloud costs, thereby maximizing business value and collaboration [2][3] - Cloudability Governance, integrated with HashiCorp Cloud Platform and Terraform, empowers FinOps teams by automating cost compliance monitoring and applying organizational policies within engineering workflows [5][6] Cloud Cost Management - Cloudability Governance helps teams proactively understand cloud cost implications, forecast, and comply with internal policies before deploying infrastructure, enhancing financial oversight [6][7] - Kubecost 3.0 represents a significant evolution in Kubernetes cost management, providing advanced capabilities for managing cloud costs and optimizing resource utilization [8][11] Integration and Features - The integration of Cloudability with HashiCorp Terraform allows engineers to gain visibility into infrastructure costs and optimization opportunities directly within their workflows, promoting informed decision-making [8][9] - New features include automated container right-sizing, advanced GPU monitoring, and enhanced node group sizing insights, aimed at identifying inefficiencies and optimizing costs across workloads [11]

Core Insights - The increasing workloads of generative AI are leading to higher cloud budgets, prompting IT leaders to rethink their cloud cost management strategies [3][6]. Group 1: Cloud Cost Management Strategies - CIOs are adopting a multi-faceted approach to manage cloud spending, which includes negotiating commitment-based contracts for better cost transparency and capacity guarantees [4]. - The deployment of cost management tools is becoming essential for IT leaders to track usage and optimize resources [4]. - Practices like FinOps are being increasingly utilized to analyze cloud spending [4]. Group 2: Resource Optimization - A significant strategy involves "right-sizing cloud environments" to align resource allocation with workload requirements and implementing autoscale strategies to adjust capacity based on demand [5]. - These measures are aimed at ensuring efficient consumption and aligning cloud spending with financial goals as AI adoption accelerates [5]. Group 3: Demand for Tailored Cloud Products - Enterprises are seeking more value from cloud products, moving beyond basic services to tailored solutions that meet specific business needs [6]. - Hyperscalers are responding by investing billions into their cloud and AI infrastructure [6]. - Regulatory requirements for data sovereignty are increasing the demand for specialized or hybrid cloud products [6]. Group 4: Generative AI Spending Trends - A survey indicates that 42% of firms expect to allocate over 30% of their cloud budget to generative AI within the next three years [7]. - Nine out of ten leaders anticipate that generative AI use cases will account for 10% of their cloud budget [7]. - IT buyers' spending on generative AI workloads is projected to quadruple by 2028 [7].

Core Insights - The rise of On-Demand technologies is reshaping business operations, but increasing costs, complexity, and governance gaps are jeopardizing returns [2][4][5] - Organizations are transitioning from capital-intensive IT investments to flexible, consumption-based models, with On-Demand tech expected to grow from 29% to 41% of IT budgets in the next year [3][4] - Despite the benefits of On-Demand technologies, many organizations struggle with cost management and achieving expected returns on investment [5][6] Cost and Complexity Challenges - 82% of executives report significant increases in costs associated with cloud, SaaS, and Gen AI, driven by inflation and digital infrastructure demands [6] - 76% of organizations exceeded their public cloud budgets by an average of 10%, with 68% overspending on Gen AI and 52% on SaaS [6] - Underutilized resources and decentralized procurement are major contributors to budget overruns [6] Governance and Management Issues - 60% of organizations utilize cloud cost management tools, but only 37% assess their effectiveness [7] - 76% of organizations have or plan to establish FinOps teams, yet most remain narrowly focused and operational [7] - Only 2% of organizations with a dedicated FinOps function cover cloud, SaaS, and Gen AI holistically [7] Sustainability Considerations - 53% of organizations acknowledge that suboptimal usage of On-Demand tech leads to excessive energy consumption and increased carbon emissions [8] - Only 36% have a strategy for integrating sustainability into FinOps, despite the potential for cost reduction and carbon footprint minimization [8] Research Methodology - The Capgemini Research Institute conducted a survey of 1,000 executives from global organizations with annual revenues of at least $1 billion, focusing on On-Demand technologies across 12 sectors and 14 countries [9]