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  • Tech Launch Perspective

    June 30, 2025
    In May 2025, Google Cloud expanded its sovereign cloud offerings to address increasing demands for data sovereignty and operational autonomy. It launched Google Cloud Air-Gapped, a fully isolated environment designed for sectors with stringent data security requirements, such as defense and intelligence. This solution operates without external network connectivity and is authorized to handle US government Top Secret data. Google Cloud Dedicated, developed in partnership with Thales, a French leader in cybersecurity, offers region-specific services operated by local partners to meet national compliance standards, such as France’s SecNumCloud. The Google Cloud Data Boundary service expansion now offers customers granular control over data residency and access, complemented by the User Data Shield, which incorporates Mandiant’s security assessments to validate application security postures. While these initiatives demonstrate Google Cloud’s commitment to offering flexible, secure, and compliant cloud solutions, challenges remain. These challenges include the limited geographic availability of certain services and complexities in integrating sovereign solutions with existing multi-cloud architectures. Enterprises must carefully assess these factors when considering Google Cloud’s offerings for their sovereignty objectives.
  • FEATURED
    Webinar

    June 12, 2025
    Watch a dynamic preview of our new conference, Elevate – Dallas 2025, where services and technology providers gained actionable growth strategies as they navigated today’s complex market landscape. In this engaging session, we unpacked what to expect at Elevate – Dallas 2025 and shared insights on how to grow existing accounts, shape new deals, and establish thought leadership in an increasingly AI-driven world. Our speakers also examined the rise of Agentic AI and how it could be a powerful catalyst for growth with the right mindset, skillset, and toolset to take advantage of it. Watch us to gain early access to what industry leaders discussed at this quickly approaching conference and explored the key themes and trends shaping the industry in the year ahead, along with expert perspectives on what it takes to stay competitive in this next wave of transformation. What questions did the webinar answer? What are the key growth themes for providers in today’s challenging macro environment? What immediate actions will drive growth in the next few quarters? What are the new mindsets, skillsets, and toolsets needed to help enterprises scale AI in their operations? What to expect from Elevate – Dallas 2025, and why you should be there
  • Tech Launch Perspective

    June 04, 2025
    At Google Cloud Next 2025, Google unveiled a reimagined application development experience centered around AI assistance, visual design, and unified lifecycle management. The announcements reflect a strategic shift toward abstracting infrastructure complexities and enabling developers to operate at the application level – a move that aligns with enterprise priorities around speed, maintainability, and developer productivity. Key launches included the Application Design Center (a visual canvas for application infrastructure design), Cloud Hub (a centralized control plane for application operations), and expanded integration of Gemini Code Assist and Gemini Cloud Assist across development and management workflows. Google also introduced updates to Firebase Studio, providing an agentic environment to prototype and test mobile apps, and announced enhancements to Kubernetes Engine and FinOps tooling to support performance and cost optimization. In this report, we analyze Google’s 2025 announcements in the context of prevailing enterprise application development priorities, including AI augmentation, platform cohesion, cost controls, and integration flexibility. We evaluate Google’s strengths in technical innovation and end-to-end AI integration, while also addressing ongoing challenges around ecosystem maturity, enterprise mindshare, and platform extensibility. Scope All industries and geographies This assessment is based on Everest Group’s review of announcements made at Google Cloud Next 2025 Contents In this report, we: The key themes influencing enterprise demand for next-generation application development Google’s positioning and product strategy The announcements from Google Cloud Next 2025 Strengths, differentiators, and potential enterprise friction points
  • Tech Launch Perspective

    May 27, 2025
    The AI market continues to grow rapidly, fueled by advancements in foundation models and increasing enterprise demand for scalable, domain-specific AI solutions. Organizations are prioritizing AI to drive automation, improve decision-making, and modernize operations across hybrid environments. IBM remains a key player in the AI space, with its Think 2025 announcements reinforcing a focus on modular, enterprise-grade AI through platforms such as watsonx, open-source Granite models, and agentic automation tools. New product updates highlight IBM’s efforts to deliver flexible deployment, secure infrastructure, and orchestration of gen AI at scale. In this report, we examine IBM’s latest announcements from Think 2025, identifying growth opportunities, enterprise challenges, and the company’s competitive positioning. The report further delves into IBM’s key offerings, major differentiators, and areas where additional refinements could enhance its value proposition. Scope All industries and geographies The assessment is based on Everest Group’s participation in, and monitoring of announcements made at the IBM Think 2025 event Contents In this report, we examine: Key themes driving and inhibiting enterprise demand for AI IBM’s current positioning in the AI market Announcements from IBM Think 2025
  • Tech Launch Perspective

    May 22, 2025
    As AI models become more complex and resource-intensive, enterprises must modernize their infrastructure to support high-performance, scalable, cost-effective workloads. Core challenges in modernization include integrating multimodal data, enabling autonomous agents, and optimizing the AI stack across diverse environments. Enterprises also aim to deploy AI in hybrid and edge settings, requiring flexibility, low latency, and data sovereignty. At Google Cloud Next 2025, Google announced AI infrastructure upgrades, including Ironwood TPUs for inference at scale, AI Hypercomputer improvements, expanded VM families, and re-architected networking with multi-shard architecture. Google also emphasized hybrid and distributed AI deployment with support for air-gapped environments and on-premises inference using NVIDIA Blackwell systems. These updates show Google’s intent to deliver an integrated AI stack, combining custom hardware, orchestration tools, and productivity platforms. However, these offerings also raise questions around interoperability with third-party tools, operational complexity, and cost transparency. In this report, we analyze Google’s AI infrastructure announcements at Google Cloud Next 2025, assessing their alignment with enterprise needs across performance, scalability, and deployment. The report covers key enterprise priorities, Google’s positioning, detailed product reviews, and Everest Group’s perspective on strengths and gaps of announced AI infrastructure-related products, offering a clear view of Google’s AI infrastructure maturity. Scope All industries and geographies Contents In this report, we examine: Key AI infrastructure-related products launched at Google Cloud Next 2025 Google’s current positioning and alignment in the AI infrastructure market AI infrastructure-related products’ specifications, benefits, and challenges
  • Webinar

    May 13, 2025
    Led by Everest Group experts Chirajeet (CJ) Sengupta, Managing Partner, and Abhishek Singh, Partner, this forward-looking webinar explored how Systems of Execution (SoE)—powered by generative and agentic AI—are set to disrupt the traditional software industry and redefine how software delivers value to customers. Watch this insightful session as we examined why the software market is at an inflection point, and what it takes for product companies to adapt and lead in this next wave of disruption. Attendees came away with a deep understanding of the SoE opportunity, what it means for product development and go-to-market models, and how to create competitive advantage in a rapidly changing landscape. With AI reshaping customer expectations and the value delivered by software, this is a generational opportunity for product companies to reimagine their strategies, products, and positioning to drive long-term impact. What questions did the webinar answer for the participants? What will generative and agentic AI do to the software industry? What are Systems of Execution, and why should you care? What is the market opportunity for SoE? How can you prepare for a world shaped by SoE? What does it take to succeed in a Systems of Execution environment?
  • FEATURED
    Viewpoint

    March 19, 2025
    Systems of Execution (SoEs) represent the critical missing layer in enterprise AI adoption, transforming isolated AI experiments into a scalable, autonomous execution framework. Traditional enterprise systems store and display information but do not bridge the gap between AI-driven insights and real-time execution. SoEs fill this void by integrating AI-driven decisions directly into operational workflows, ensuring seamless automation at scale. By adopting SoEs, enterprises can enhance real-time responsiveness, operational efficiency, and data-driven agility, unlocking new levels of automation and intelligence across business functions. Everest Group developed this research to address a pressing opportunity: enterprises are investing heavily in AI, yet many have not realized its full potential as it remains primarily an analytical tool rather than an execution engine. The shift toward agentic AI – where AI makes and executes decisions independently – demands an execution layer that integrates data, decision-making, and automation in real time. As organizations look to enhance competitiveness and agility, adopting SoEs will enable them to transform AI from an advisory tool into an active business outcome driver. This shift positions enterprises to scale their AI investments effectively and maximize their impact.
  • Provider Compendium

    Feb. 28, 2025
    Decentralized and hybrid designs add more complexity to clinical trials, generating vast data volumes from diverse sources. This complexity creates significant data management challenges. In response, sponsors are adopting unified clinical Data and Analytics (D&A) platforms to centralize and standardize clinical data for actionable insights, offering real-time monitoring, predictive analytics, and risk management. These platforms transform disparate datasets into cohesive, structured formats, helping stakeholders detect outliers, predict adverse events, and generate on-demand dashboards and reports. D&A platforms offer centralized repositories, Risk-based Quality Management (RBQM), and seamless integration with Electronic Health Records (EHRs), wearables, and medical devices. These features improve data access and interoperability, contributing to more informed decision-making and enhanced quality and risk oversight. To meet sponsor needs, clinical D&A platform providers are integrating AI and generative AI to automate repetitive tasks, generate insights, and strengthen quality and risk management. In this report, we analyze 18 clinical D&A platform providers’ capabilities and offerings. The report empowers buyers to select the right provider for their sourcing considerations and enables providers to benchmark themselves against their competition. Scope Industry: life sciences Geography: global Contents In this report, we: Examine the clinical D&A platform provider landscape Assess clinical D&A platform providers on their capabilities and market success-related dimensions Membership(s) Clinical Development Technology Sourcing and Vendor Management
  • Viewpoint

    Feb. 21, 2025
    The clinical trial landscape is fundamentally transforming with generative AI adoption. Historically, trials have relied on manual processes for protocol design, database lock, and regulatory documentation, often leading to inefficiencies, rising costs, and prolonged development timelines. Growing clinical data volume and increasingly stringent regulatory requirements pressure pharma companies to optimize costs and accelerate drug development. Generative AI is uniquely positioned to address these challenges by synthesizing fragmented datasets, automating routine tasks, and enabling real-time data analysis and predictive modeling. By streamlining trial workflows, supporting adaptive trial designs, and enhancing decision-making, it is helping sponsors improve operational efficiency while maintaining data integrity and compliance. Integrating generative AI into clinical trials requires redefining core processes, reimagining stakeholder roles, and implementing new workflows that allow AI-driven insights to be seamlessly embedded into trial operations. This Viewpoint explores how sponsors can effectively adopt generative AI, key implementation considerations, and the best practices to ensure successful clinical development integration. Scope Industry: life sciences Geography: global Contents In this report, we examine: How generative AI addresses inefficiencies and drives innovation in trial processes Strategic changes required to integrate generative AI, including redefining roles and optimizing workflows Key considerations and best practices for successful adoption and organizational goal alignment Membership(s) Clinical Development Technology Sourcing and Vendor Management
  • Provider Compendium

    Feb. 14, 2025
    Electronic Data Capture (EDC) systems are integral to clinical research, enabling clinical data collection, storage, and management. EDCs mark a significant shift from paper-based case report forms to digital and web-based trial data collection. The COVID-19 pandemic further emphasized EDC systems’ importance as the need for remote and decentralized clinical trials surged. The pandemic highlighted the need for robust, flexible, and secure data capture solutions to support treatments’ and vaccines’ rapid development and approval. These platforms have evolved to centralize data collection, improve data quality, and enable real-time clinical trial monitoring. They now integrate complex clinical data sources, such as electronic health records, laboratory data, clinical trial management systems, connected devices, and real-world data. Overall, EDC systems have significant benefits in clinical data collection, storage, and management. In this report, we assess 20 EDC product providers. The report enables buyers to choose the best-fit provider based on their sourcing considerations and empowers providers to benchmark themselves against their peers. Scope Industry: life sciences Geography: global Contents In this report, we: Examine the EDC product provider landscape Assess clinical EDC product providers on their capabilities and market success-related dimensions Membership(s) Clinical Development Technology Sourcing and Vendor Management