As enterprises embed LLMs into customer service, decision support, and content generation workflows, a new realization is emerging: success depends not just on the model’s intelligence, but on its ability to understand context. This shift makes model contextualization a strategic priority, defining how LLMs interpret user inputs, apply external knowledge, and generate responses that are grounded, trustworthy, and ready for action. This Viewpoint traces the evolution of contextualization techniques – from static, training-time fine-tuning to dynamic, real-time techniques such as prompt engineering and retrieval-augmented generation. It explains the growing relevance of long-context window models, which allow richer reasoning by holding more information in memory, and highlights the rise of protocol-based contextualization, including Anthropic’s Model Contextualization Protocol (MCP), IBM’s Agent Communication Protocol (ACP), and Google’s Agent-to-Agent (A2A), which enable persistent, interaction-aware agent ecosystems. The report breaks down contextualization strategies and their trade-offs across latency, costs, and reasoning depth, and maps each approach to its ideal use case. Enterprises can use it to design context-aware LLM workflows that reduce hallucinations, improve response quality, and adapt in real time, paving the way for more dependable and intelligent AI systems.

Enterprises across North America are advancing their data and AI strategies while grappling with infrastructure, governance, and talent-related challenges. As generative AI adoption gains momentum, organizations focus on scalable, business-aligned solutions that deliver measurable impact. To navigate this evolving landscape, they are turning to specialist service providers with deep domain expertise and advanced AI capabilities. In response, providers are strengthening their offerings through investments in generative AI, cloud-based AI platforms, and industry-specific accelerators. In this report, we evaluate 32 providers featured on Everest Group’s Data and AI Services Specialists – North America PEAK Matrix® Assessment 2025.  

Enterprises are increasingly identifying gaps in their data ecosystems as they seek to harness generative AI’s full potential. To address these gaps, businesses are prioritizing their data strategy to build AI-ready data ecosystems. AI advances have amplified the importance of robust data management and governance. When scaling their AI initiatives, they are realizing the value of trustworthy data to ensure quality, consistency, and security. The focus has shifted to realizing value, with enterprises aiming to drive tangible business outcomes from their data initiatives. Enterprises demand their data strategies to deliver measurable business outcomes, leading to productivity gains, operational efficiencies, and unlocking new revenue streams. Data initiatives are now vital investments that directly contribute to building a competitive advantage in the market. This compendium provides detailed profiles of 31 service providers to assist D&AI service buyers in selecting providers that can serve their needs. The report helps enterprises choose the best-fit provider based on their sourcing considerations and empowers providers to benchmark their performance against their peers. Scope All industries and geographies This assessment is based on Everest Group’s annual RFI process for the calendar year 2024, interactions with leading D&AI providers, client reference checks, and an ongoing analysis of the D&AI services market Contents In this report, we: Examine the D&AI services market Classifies providers into Leaders, Major Contenders, and Aspirants on a capability-market-impact matrix Assess providers’ key solutions, delivery centers, investments, and use cases Lending operations technology solutions/tools: brief descriptions of key technology solutions

Enterprises are increasingly identifying gaps in their data ecosystems as they seek to harness generative AI’s full potential. To address these gaps, businesses are prioritizing their data strategy to build AI-ready data ecosystems. AI advances have amplified the importance of robust data management and governance. When scaling their AI initiatives, they are gradually realizing the value of trustworthy data to ensure quality, consistency, and security. In addition, the focus has shifted toward realizing value, with enterprises aiming to drive tangible business outcomes from their data initiatives. Enterprises demand their data strategies to deliver measurable business outcomes. This has led to a sharp focus on driving productivity gains, operational efficiencies, and unlocking new revenue streams. Data initiatives are increasingly seen as a vital investment that directly contributes to building a competitive advantage in the market. In this report, we analyze 31 providers featured on Everest Group’s Data and AI (D&AI) Services for Mid-market Enterprises PEAK Matrix® 2025, highlighting their strengths and limitations. The study will enable buyers to choose the best-fit provider based on their sourcing considerations, while providers will be able to benchmark their performance against each other. Scope All industries and geographies The assessment is based on Everest Group’s annual RFI process for the calendar year 2024, interactions with leading D&AI providers, client reference checks, and an ongoing analysis of the D&AI services market Contents In this report, we examine: D&AI provider landscape D&AI Services for Mid-market Enterprises PEAK Matrix® Assessment 2025 characteristics Enterprise sourcing considerations Membership(s) Data & Analytics Artificial Intelligence (AI) Sourcing and Vendor Management

The Data and Analytics (D&A) and AI market continues to grow rapidly, fueled by expanding enterprise data and AI-ML advances. Organizations are turning toward D&A and AI solutions to drive digital transformation, enhance decision-making, and scale operational efficiency. At re:Invent 2024, AWS showcased its commitment to advancing the D&A and AI ecosystem with impactful updates to its platforms and tools and introducing new generative AI foundational models. These enhancements emphasize scalability, multi-model flexibility, and enterprise readiness, addressing the complete AI life cycle, from data processing to model deployment, while maintaining a strong focus on security and governance. In this report, we analyze AWS’ latest announcements from re:Invent 2024, identifying growth opportunities, enterprise challenges, and the company’s competitive positioning. The report further delves into AWS’ 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 AWS re:Invent 2024 event Contents In this report, we: Key themes driving and inhibiting enterprise demand for D&A and AI AWS’ current positioning in the D&A and AI market Announcements from AWS re:Invent 2024 Membership(s) Data & Analytics Artificial Intelligence (AI) Sourcing and Vendor Management

What is the Everest Group AI Top 50™? Everest Group AI top 50™ is a global list of largest AI-first technology providers. The listing is based on multiple objective parameters including their Artificial Intelligence (AI) revenues, cumulative funding, share of funding received in the past two years, and valuation. This 2023 is the inaugural release of this list – the first of what will become an annual event. Why the Everest Group AI Top 50™? In today's rapidly evolving technological landscape, it is increasingly vital to understand the dynamic AI landscape. With its groundbreaking innovation, AI continues to reshape industries, optimize processes, and redefine human-machine interactions. The technology itself has garnered substantial interest, giving rise to more than 5,000 AI technology providers in the past decade alone, according to our estimates. Some are focused on a particular domain or geography, while others are broad-based. Some are listed; others are privately held. This list helps enterprises to identify technology providers in this space that have reached significant scale. It also helps AI-first technology providers to compare themselves against others in the industry. How is the Everest Group AI Top 50™ determined? The analysis was initiated with a list of more than 2,000 AI technology providers, further narrowed down to 250+ providers based on preliminary assessments. Qualification criteria: AI-first: listed companies develop and integrate AI as a central component in their products and solutions to a degree that – without it – their offerings would be fundamentally incomplete. The listing  excludes, for example, providers that have AI as a feature that helps them improve their current offerings, such as automation-first vendors.  Software-first: listed providers develop and provide software-based AI solutions as their primary offering. The list excludes pure-play hardware and service-based AI providers. B2B focus/offerings: those on the list offer software products and solutions to meet other businesses’ technology needs. The list excludes providers that exclusively offer AI solutions for B2C   purposes. Rank determination: technology providers are ranked based on their overall AI revenue, total funding received, share of funding received in the past two years, and valuation.

Enterprises adopting outcome-based analytics and Artificial Intelligence (AI) are unable to maximize the technologies’ benefits because of data-related challenges, analytics and AI talent’s shortage in the market, and organizational unpreparedness. To address these challenges, they are looking for specialist providers with strong domain expertise in advanced technologies. Analytics and AI services specialists are well-positioned to help enterprises adopt and scale initiatives due to their proactive investments in data-engineering capabilities, in-depth experience in catering to domain- or industry-specific analytics requirements, and investments in acquiring and upskilling advanced analytics and AI talent. In this report, we provide detailed profiles of 26 analytics and AI services specialists featured on Everest Group’s Analytics and AI Services Specialists PEAK Matrix® 2024. The profiles offer each specialist’s comprehensive overview, including an operational overview, geography focus, industry focus, buyer size, delivery locations, solutions offered, investments, partnerships, and case studies. Scope All industries and geographies Services across the analytics and AI services value chain – strategy and consulting, business intelligence and reporting, advanced analytics and insights, data engineering, AI, and generative AI Contents In this report, we analyze the global analytics and AI services specialists’ landscape and focus on: 26 specialists’ strengths and limitations Specialists’ leadership, presence across geographies and industries, revenue estimates, and buyer size focus Analytics and AI services delivery locations Analytics and AI services Intellectual Property (IP) overview, along with a deep dive into flagship IP and key partnerships across the analytics and AI services value chain Investments in analytics and AI services across talent, infrastructure (centers of excellence / labs), acquisitions, research, academic partnerships, and solutions Case studies, with detailed solutions Membership(s) Artificial Intelligence (AI) Data & Analytics Sourcing and Vendor Management

Generative AI adoption is gaining momentum across horizontal functions such as IT security, HR, marketing, and legal, with technology-centric functions such as IT and security leading in enterprises’ gen AI spend. Key use cases include automated code generation, enhanced cybersecurity, and customized learning and development. Industry-specific applications vary, with finance leveraging gen AI for fraud detection and personalized financial advice, while retail focuses on personalized marketing and supply chain management. CIOs face challenges such as a lack of clear success metrics, a rapidly evolving technology landscape, budget constraints, and talent shortages. Key risks in gen AI adoption involve data security, privacy, interpretability, ownership, responsibility, bias, and ethical concerns. In response, organizations are implementing their own guardrails while regulators develop legal frameworks. The future of AI is marked by core technological shifts: AI compute moving to the edge, the rise of small language models (SLMs) due to resource efficiency challenges, and the need for model orchestration. In this report, we explore generative AI adoption trends across horizontal business functions and industries. We examine the top challenges CIOs face with gen AI adoption and key risks in its implementation. Additionally, we discuss future outlook trends, including shifts in core technologies and gen AI’s impact on productivity and adoption trends. Scope All industries and geographies Contents In this report, we examine: Horizontal function-specific use cases and adoption trends Industry-specific use cases and adoption trends Top challenges that CIOs face with gen AI adoption Key risks in adopting gen AI Corporate guardrails for gen AI Future outlook Membership(s) Artificial Intelligence (AI) Vendor and Sourcing Management

The data and analytics market is evolving rapidly due to a surge in data volume and advances in AI and ML. Businesses are increasingly using data analytics to gain insights, improve decision-making, and drive innovation. Key trends include integrating big data, real-time analytics, and predictive modeling. Google is among the top three cloud providers, offering platforms such as BigQuery for data storage, AI-driven analytics, and ML platforms. Innovations and updates from Google Next 2024 will directly impact how enterprises manage data and streamline their analytics processes. In this report, we examine Google’s latest updates from Google Next 2024 on data and analytics. It explores growth areas and challenges in the field, outlines Google’s current offerings, highlights unique features, and suggests ways Google can further improve its offerings. Scope All industries and geographies The assessment is based on Everest Group’s participation and tracking of announcements at the Google Next 2024 Contents In this report, we examine: Key enterprise issues and objectives Google’s current positioning in data and analytics Google Next 2024 announcements Everest Group’s review of Google Next 2024 product launch Membership(s) Data & Analytics Sourcing and Vendor Management

Amid the macroeconomic headlines, many enterprises seek a proven RoI track record before committing to investments in Analytics and AI. Additionally, a stringent regulatory environment is prompting enterprises to cautiously approach the adoption of generative AI. These enterprises are seeking assistance from analytics and AI services specialists to run pilot projects and scale up implementations. This demand is driving providers to invest in deepening their data, analytics and AI capabilities and expanding their industry knowledge. In this report, we assess 26 analytics and AI services specialists featured on the analytics and AI services specialists PEAK Matrix® 2024. Scope: Industry: data and analytics Geography: global The assessment is based on Everest Group’s annual RFI process for the calendar years 2022 and 2023 H1 (January-June), interactions with leading analytics and AI services specialists, client reference checks, and an ongoing analysis of the analytics and AI services market Contents: This report features detailed profiles of 26 analytics and AI services specialists and includes: Everest Group’s PEAK Matrix® evaluation of analytics and AI service providers, categorizing them into Leaders, Major Contenders, and Aspirants Providers’ key strengths and limitations Membership(s) Data & Analytics Artificial Intelligence (AI) Outsourcing Excellence