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.

Enterprise AI platforms are at the forefront of digital transformation, enabling businesses to innovate, compete, and operate efficiently. These platforms empower organizations to streamline processes, enhance decision-making, and accelerate their AI adoption journeys by unifying data governance, model training, deployment, and monitoring in a single ecosystem. Gen AI further amplifies this by enabling dynamic automation, content generation, and personalized customer interactions. In this report, we analyze enterprise AI platforms, including their architecture, core components, and technology advances. The report highlights key trends shaping these platforms’ adoption, including the rise of Small Language Models (SLMs) tailored to specific business needs, the growing importance of ethical AI governance, and the integration of real-time decision-making capabilities. It also examines enterprise challenges in scaling AI adoption. This research offers valuable insights for businesses harnessing AI platforms for sustainable growth and competitive differentiation. Scope Industry: cross-industry Geography: global Contents In this report, we examine: Introduction to enterprise AI platforms: overview of architecture, capabilities, and definitions Technology advances: insights into gen AI, agentic AI, and governance tools shaping platform capabilities Market trends and drivers: the role of SLMs, real-time analytics, and scalable AI solutions in adoption Ecosystem evaluation: leading players across big tech, data management heritage, native AI, and specialized AI providers Challenges and strategic solutions: addressing integration, data complexity, and cost management Membership(s) Artificial Intelligence (AI) Sourcing and Vendor Management

Conversational AI has revolutionized interactions between businesses, individuals, and technologies, enhancing customer experiences, driving customer acquisition, and establishing market differentiation. In recent years, especially with the advent of generative AI and Large Language Models (LLMs), conversational AI providers are addressing the increasing demand for more sophisticated chatbot capabilities by introducing new features and enhancing existing offerings to deliver comprehensive and accessible solutions for diverse use cases. Providers are also ensuring enterprise data protection, transparency, and explainability to maximize conversational AI solutions’ benefits. This compendium provides comprehensive and fact-based snapshots of 26 conversational AI technology providers and offers insightful analysis of their capabilities. The compendium enables providers to benchmark their capabilities against their peers, while buyers can assess the providers based on their desired set of capabilities. Scope All industries and geographies Contents In this report, we feature 26 conversational AI provider profiles and include: Company overview Product Overview Recent investments and announcements Market adoption and partnership overview FTEs by function Product features, functionalities, and key enhancements Capabilities across PEAK Matrix® dimensions Key partnerships Memberships Customer Experience Management (CXM) Services, including Contact Center Outsourcing Service Optimization Technologies (SOT) Sourcing and Vendor Management

Enterprises are embracing Intelligent Automation (IA) technologies, signifying migration from standalone Robotic Process Automation (RPA) solutions to holistic automation strategies to achieve scalability. Technology providers have been instrumental in this transition by offering unified IA platforms that combine RPA, AI, process intelligence, and process orchestration. With increased stakes and investment levels, enterprise leaders strive to make data-driven sourcing decisions. Everest Group performed an independent, comprehensive cost-benefit analysis using its Total Value Added (TVA) framework. This analysis evaluates RoI realized by enterprise clients of two prominent Intelligent Automation Platform (IAP) providers. This report features TVA profiles of these IAP technology providers, detailing the RoI obtained by their referenced clients. The report includes an overview of the client organization, key drivers, provider selection criteria, TVA framework and assumptions, and financial and non-financial benefits analysis. Additionally, the report offers an in-depth look at the costs involved, the risk-adjusted RoI over three years, the net benefit following IAP deployment, and the payback period. Scope Geography: global Providers: Tungsten Automation and UiPath Product: IAP Contents This report includes TVA profiles of two leading IAP technology providers and covers the following: Client organization’s overview Key drivers and provider selection criteria Framework and assumptions Financial and non-financial benefits analysis Cost analysis Risk-adjusted RoI for a three-year term Net benefit post IAP deployment Payback period Membership(s) Service Optimization Technologies (SOT) Sourcing and Vendor Management

Conversational AI has revolutionized interactions between businesses, individuals, and technologies, enhancing customer experiences, driving customer acquisition, and establishing market differentiation. In recent years, especially with the advent of generative AI and Large Language Models (LLMs), conversational AI providers are addressing the increasing demand for more sophisticated chatbot capabilities by introducing new features and enhancing existing offerings to deliver comprehensive and accessible solutions for diverse use cases. Providers are also ensuring enterprise data protection, transparency, and explainability to maximize conversational AI solutions’ benefits. In this report, we assess 25 conversational AI technology providers featured on the Conversational AI Products PEAK Matrix® and categorize them as Leaders, Major Contenders, and Aspirants based on their capabilities and market offerings. We also identify Star Performers, which have made significant progress from the previous year. The research will help buyers select right-fit technology providers and enable providers to benchmark themselves against the competition. Scope All industries and geographies This assessment is based on Everest Group’s annual RFI process through December 2023, interactions with leading conversational AI technology providers, client reference checks, and ongoing analysis of the conversational AI market Contents This report covers: Everest Group’s PEAK Matrix® evaluation assessing 25 conversational AI technology providers The conversational AI technology provider market’s competitive landscape Remarks on the featured providers’ key strengths and limitations Membership(s) Customer Experience Management (CXM) Services, including Contact Center Outsourcing Service Optimization Technologies (SOT) Sourcing and Vendor Management

With new innovations and technologies entering the market, organizations must evolve into digital-first businesses to stay resilient and competitive. Intelligent Process Automation (IPA) leads operational transformation, revolutionizing businesses by automating mundane tasks. With generative AI taking centerstage, the scope and capabilities of automation have expanded significantly. Implementing IPA solutions strategically not only streamlines workflows but also frees valuable human resources, allowing organizations to focus on innovation and core objectives. Buyers across various sectors are swiftly adopting IPA to drive digital transformation initiatives. Meanwhile, solution providers are actively innovating and tailoring IPA solutions to meet specific organizational needs, empowering businesses to achieve greater agility and scalability in their operations. In this report, we provide an in-depth analysis of the IPA market for both buyers and solution providers. It covers IPA solution and service capabilities, the provider landscape, adoption trends, challenges, best practices, and the outlook for 2024-25. Scope All industries and geographies IPA solutions: sourcing IPA technology products, along with consulting, implementation, and maintenance services, but excluding traditional BPO services IPA services only: sourcing IPA services such as consulting, implementation, and maintenance Contents In this report, we examine: IPA market overview and its future outlook Adoption trends by industry, business function, geography, and buyer size IPA solution and service characteristics The IPA solution provider landscape Challenges and best practices Membership(s) Service Optimization Technologies (SOT) Sourcing and Vendor Management

Over the past year, gen AI has garnered significant attention due to innovations such as ChatGPT. Powered by Large Language Models (LLMs), gen AI enables human-like conversations. It has broad applications, particularly within Intelligent Automation (IA), where it enhances existing solutions such as Intelligent Document Processing (IDP) and Conversational AI (CAI). CAI, which uses Natural Language Processing (NLP) for text, voice, and video interactions, is widely adopted across industries to improve customer interactions and operational efficiency. As CAI adoption grows, providers are incorporating low-code/no-code functionalities to democratize chatbot development among enterprises. Concurrently, they are leveraging gen AI to enhance intent recognition, entity extraction, sentiment analysis, and analytics, delivering better Customer Experience (CX) and differentiating their offerings. CAI significantly enhances gen AI models’ effectiveness by improving conversational contexts and offering more accurate responses. By integrating these AI models, providers can create synergistic solutions that elevate CX. Scope All industries and geographies Functions: Customer Experience Management (CXM), CAI, gen AI, and IA Contents In this report, we examine: AI’s role in shaping today’s world CAI’s status Gen AI’s role in enhancing CAI solutions Gen AI’s implications for enterprises and CAI’s role in mitigating them AI use cases Key strategies for enterprises to adopt gen AI Membership(s) Customer Experience Management (CXM) Services, including Contact Center Outsourcing Service Optimization Technologies (SOT) CX Excellence CXM Technology  

Intelligent automation serves as the cornerstone of modern enterprises, reshaping operational landscapes and driving efficiency at an unprecedented pace. To remain competitive and efficient in today’s fast-paced business environment, enterprises seek solutions that enhance productivity and accuracy. With gen AI’s emergence, the automation spectrum has expanded, enabling enterprises to streamline complex tasks and drive operational excellence and strategic growth. Solution providers are acutely aware of the evolving enterprise needs, continuously refining their Intelligent Process Automation (IPA) offerings to meet these demands. Everest Group defines IPA as the intelligent automation of business processes through a combination of automation technologies, including Robotic Process Automation (RPA) and cognitive/AI-based automation. This compendium features comprehensive profiles of 27 top IPA solution providers, along with an analysis of their products and services. IPA buyers will find the report useful in evaluating solution providers based on their specific requirements. Additionally, it will enable solution providers to assess how their products, services, advantages, and disadvantages compare with those of their competitors. Scope All industries and geographies IPA solutions: sourcing IPA technology products, along with consulting, implementation, and maintenance services, but no traditional BPO services IPA services only: sourcing IPA services such as consulting, implementation, and maintenance This report does not cover IPA technology products that are licensed independently or embedded within broader BPO deals Content This report features 27 IPA solution provider profiles and includes: Company overview Recent deals and announcements IPA revenue and FTE mix Solutions portfolio Membership(s) Service Optimization Technologies (SOT) Outsouring Excellence

Companies aiming to maintain competitiveness and strength recognize the importance of transitioning to a digital-first business model. Manual processes present numerous challenges, prompting enterprises to seek superior alternatives in digital, automated, and intelligent business practices. With the rise of digital technologies, especially Intelligent Automation (IA), organizations can achieve heightened levels of efficiency and productivity. Generative AI has accelerated automation evolution, leading to the development of newer and improved solutions that are more customized, flexible, and efficient. Solution providers are swiftly embracing a digital-centric approach known as Intelligent Process Automation (IPA) to address this growing demand. IPA has become a vital tool for businesses to navigate the complexities of the modern market with increased agility and clarity. In this report, we examine 27 IPA solution providers and position them on Everest Group’s PEAK Matrix® as Leaders, Major Contenders, Aspirants, and Star Performers based on their capabilities, offerings, and limitations. This research will help buyers select the right-fit providers for their needs and enable providers to benchmark themselves against each other. Scope All industries and geographies IPA solutions: sourcing IPA technology products, along with consulting, implementation, and maintenance services, but no traditional BPO services IPA services: sourcing IPA services such as consulting, implementation, and maintenance This report does not cover IPA technology products that are licensed independently or embedded within broader BPO deals Content In this report, we examine: Everest Group’s PEAK Matrix® evaluation of IPA solution providers, categorizing them as Leaders, Major Contenders, Aspirants, and Star Performers The IPA solution provider market’s competitive landscape Providers’ key strengths and limitations Membership(s) Service Optimization Technologies (SOT) Outsouring Excellence

Conversational AI is a network of advanced technologies and solutions, such as Intelligent Virtual Agents (IVAs) and agent assist, that communicate with each other to share information across systems, serving as a key enabler of front- and back-office automation. Businesses worldwide are recognizing the significance of conversational AI solutions to serve customers across different industries through diverse digital channels, addressing customer needs, and supporting internal processes such as HR support, IT helpdesk, sales, finance and accounting, and marketing. This report highlights the escalating demand for self-service solutions such as conversational AI, reaching an all-time high and expected to gather greater momentum as enterprises increasingly leverage these solutions for superior customer experience, customer acquisition, and market differentiation. Additionally, the report explores recent advances in generative AI, holding the potential to significantly enhance the capabilities of conversational AI solutions, thereby making them more effective for a multitude of use cases and increasing customer satisfaction. Scope All industries and geographies Contents In this report, we examine: An overview of conversational AI solutions The impact of generative AI and LLMs on conversational AI solutions Market size and adoption trends of conversational AI solutions across buyer geography, size, industry, and business function Buyer insights, adoption drivers, and barriers to adoption of conversational AI Conversational AI provider landscape and partnership ecosystem Membership(s) Customer Experience Management (CXM) Services, including Contact Center Outsourcing Service Optimization Technologies (SOT) Sourcing and Vendor Management