Showing 50 results
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Viewpoint
Closing the Adoption Gap with Digital Adoption Platforms (DAPs) in the AI Transformation Era
Oct. 28, 2025AI is transforming business operations, yet its potential often outpaces adoption. Despite rising investments in AI and agentic AI, many organizations struggle to translate these into measurable business outcomes due to limited people readiness. Digital Adoption Platforms (DAPs) are emerging as essential enablers, evolving from simple onboarding tools to intelligent systems that guide, educate, and empower users within their workflows. By embedding contextual guidance, analytics, and compliance guardrails, DAPs bridge the gap between technology and human capabilities, making AI more intuitive, accessible, and effective. This report examines how enterprises can leverage DAPs to overcome adoption challenges and accelerate AI-driven value realization through a structured 6R framework. It also explores role-based use cases across IT, HR, and sales, highlighting how DAPs enhance productivity, compliance, and user engagement. Finally, it provides guidance to evaluate AI-ready DAP providers, positioning DAPs as a cornerstone of sustainable, user-centric AI transformation.
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Oct. 27, 2025As AI becomes central to enterprise strategy, a striking reality is emerging: most organizations are limited not by their AI investments, but by their data foundation strengths. Fragmented systems, inconsistent governance, and siloed ownership continue to undermine AI success, leaving only a small fraction of enterprises truly ready to scale. This Viewpoint unpacks what it means to be data ready in the AI-first world. Drawing on a survey of 123 enterprises and in-depth data and AI leader interviews, it explores how trusted, high-quality, and well-governed data has become the defining factor separating AI ambitions from enterprise-wide adoption. The report introduces Everest Group’s seven pillars of data readiness spanning strategy, quality, accessibility, governance, foundation, culture, and data products and provides a practical framework to operationalize these capabilities across technology, talent, and governance dimensions. It also identifies the most common execution pitfalls and emerging risks that enterprises must navigate as AI adoption accelerates. By combining market data, best practices, and enterprise case study-based insights, the report offers business and technology leaders a clear roadmap to close the readiness gap and build resilient data
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Viewpoint
Rewriting the Rules of Data with AI
Oct. 24, 2025AI is rapidly redefining the rules of enterprise data management. Traditionally viewed as a manual and resource-intensive function, data management often struggled to keep pace with evolving business demands, the surge of unstructured data, and the need for real-time insights. Today, AI and data are becoming deeply interdependent. High-quality data enables stronger AI outcomes, while AI enhances the way data is managed, governed, and utilized – creating a virtuous loop that drives greater efficiency, innovation, and trust. Organizations are beginning to realize tangible gains by embedding AI across the data life cycle, from ingestion and transformation to storage, governance, and orchestration. However, while AI is proving to be a catalyst for productivity, innovation, and compliance, scaling these capabilities across complex data ecosystems comes with certain challenges. Success depends on taking a structured approach: carefully planning initiatives, embedding robust governance, and applying AI responsibly and strategically, as outlined by the SOAR framework in this paper.
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Oct. 24, 2025Enterprises are rapidly exploring agentic AI to create more autonomous, context-aware workflows. While initial efforts have focused on single-agent systems, these often fall short in adaptability, reliability, and scale. Multi-agent systems represent the next frontier, enabling specialized agents to collaborate dynamically across tasks and environments. But unlocking their full potential requires orchestration: the capability to coordinate diverse agents around shared objectives, execution patterns, and governance frameworks. This report provides a strategic overview of why orchestration is essential and how enterprises can architect intelligent, scalable agentic systems. Key focus areas include the layered architecture of multi-agent systems, orchestration strategies based on execution and control models, and the core building blocks – from perception handling and task decomposition to agent discovery and reasoning. It also explores emerging communication protocols such as MCP, A2A, and ACP that enable secure and scalable agent collaboration. Importantly, the report outlines policy enforcement, feedback loop, and governance mechanisms – ensuring enterprise-grade trust and resilience. Readers will gain a roadmap to deploy agentic intelligence that is both adaptable and aligned with business goals.
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Viewpoint
The Rise of Agentic AI
Oct. 14, 2025Agentic AI marks the next major evolution in enterprise AI, shifting from assistive, prompt-driven systems to autonomous, goal-oriented agents capable of delivering measurable business outcomes with minimal human intervention. Unlike traditional automation, which is often rule-bound and siloed, agentic AI combines contextual awareness, adaptive reasoning, and real-time decision-making to operate across complex enterprise environments. This report examines the rise of agentic AI and its potential to fundamentally rearchitect enterprise execution. It explores how industries such as BSFI, HLS, manufacturing, and RCPG are applying agentic AI to enhance agility, scalability, and resilience. It also delves into the rapidly evolving technology provider ecosystem, mapping out the major provider categories and their strengths, as well as the strategic considerations to select the right partner. With adoption still in its early stages, the report addresses the organizational, technical, governance, and operational challenges that enterprises must overcome to scale agentic AI effectively – from RoI clarity and workforce readiness to data integration and regulatory compliance. It also offers a strategic framework to align agentic capabilities with business priorities, orchestrate multi-agent workflows, and ensure secure, ethical, and compliant deployment. As enterprises move toward the agentic era, success will hinge on building new human-agent collaboration models, redefining roles, and shifting RoI focus from efficiency gains to adaptability and resilience. This report provides a roadmap to navigate this transition and unlock sustained competitive advantage.
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Oct. 09, 2025The global Off-highway Vehicle (OHV) segment is advancing toward autonomy. Industries such as agriculture, mining, and construction are leveraging automation to counter workforce shortages and improve operational safety and precision. Unlike on-road systems, off-highway autonomy demands ruggedized sensors, terrain-adaptive perception, and high-performance edge compute to enable real-time decision-making in remote and harsh environments. OEMs, including John Deere, Caterpillar, and Komatsu, are investing heavily in autonomous solutions that combine software, data platforms, and hardware retrofits. Retrofit kits are accelerating adoption by reducing upfront capital costs and allowing integration across existing fleets. Simultaneously, digital ecosystems are evolving through platforms such as Deere Operations Center and Caterpillar MineStar, which enable remote management, data monetization, and predictive maintenance. New commercial models such as autonomy-as-a-service are redefining how automation is deployed and monetized. Pay-per-acre and pay-per-ton frameworks are shifting autonomy from a one-time investment to an operational expenditure model. Engineering service providers and technology specialists are emerging as essential partners, supporting OEMs in simulation, validation, and system integration. Together, these trends signal a broader shift toward scalable, connected, and sustainable autonomy in the off-highway domain.
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Viewpoint
The AI Advantage in Retail
Oct. 09, 2025The retail industry is at an inflection point, shaped by rapidly evolving customer expectations, omnichannel complexity, and mounting competitive pressures. This Viewpoint explores the need for retail enterprises to embrace comprehensive, AI-driven transformation of their customer experience (CX) strategy through an end-to-end CX approach. It focuses on the cohesive orchestration of traditionally siloed business functions, such as merchandising, marketing, sales, and supply chain, to deliver frictionless, consistent, and emotionally resonant experiences across both digital and physical touchpoints. The report highlights key enablers of this transformation, including an integrated CX technology architecture that unifies data across channels, a dynamic KPI framework to measure both experience and business impact, and a representative 360-degree customer insights dashboard for retail enterprises. It also underscores the strategic role of CXM providers and ecosystem partnerships in empowering retailers through innovative engagement models, AI-led personalization, and operational excellence that bridges human empathy with automation. Additionally, it outlines key factors to consider when selecting the right CXM partner. Ultimately, this Viewpoint presents a roadmap for retail enterprises to move beyond isolated experience enhancements toward a connected and intelligent customer ecosystem, where every interaction is optimized for value, empathy, and agility.
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Oct. 09, 2025Finance and Accounting (F&A) teams are expected to do more than ensure compliance – they must now manage a growing array of risks while enhancing resilience and business value. Traditional risk management methods, such as periodic audits and retrospective controls, are no longer sufficient in today’s environment of macroeconomic volatility, digital transaction complexities, and heightened regulatory scrutiny. This Viewpoint introduces Finance Risk Intelligence (FRI) as a dedicated, AI-powered capability designed to embed continuous, predictive, and autonomous risk monitoring across the F&A value chain. FRI represents a distinct evolution in the F&A technology stack. These solutions function as an intelligence layer that integrates with ERP and process execution platforms to ingest financial transaction data, apply layered AI models for anomaly detection, and enable near real-time intervention. The report outlines the FRI architecture, comprising data processing, intelligence, and action layers, and details how enterprises can use FRI for use cases across procure-to-pay, order-to-cash, and record-to-report processes. It also presents the emerging provider landscape and provides practical adoption guidance, including imperatives to align people, processes, and technology.
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Sep. 30, 2025Investment banking enterprises face mounting pressure from volatile macroeconomic conditions, fee compression, disintermediation through special purpose acquisition companies and direct listings, and increasingly complex regulatory mandates such as Basel III/IV, MiFID II, and Dodd-Frank. Traditional human-led models, patchwork systems of record, and fragmented engagement layers constrain scalability, personalization, and responsiveness. This Viewpoint introduces Systems of Execution (SoE) as intelligent, agent-driven layers that unify data, automate workflows, and enable real-time, autonomous execution across the investment banking value chain. SoE moves beyond static systems of record and engagement by embedding orchestration directly into high-stakes workflows, allowing investment banks to proactively adapt to regulatory shifts, market changes, and client demands. The report details a phased adoption framework from agent-readable data fabric and embedded orchestration to oversight, governance, and scaled orchestration. It presents enterprise use cases where SoE can reduce friction in onboarding, KYC, suitability reviews, pitchbook preparation, and regulatory filings. A Bridgewater Associates case study illustrates how SoE-enabled orchestration, powered by Amazon Bedrock and Anthropic Claude, accelerated research workflows, compressed cycle times, and democratized access to insights across analyst teams. The report concludes with a strategic roadmap that positions SoE as structural enablers of scale, compliance, and growth in capital markets. Investment banks adopting SoE can transition from fragmented operations to intelligent execution that reshapes how deals are sourced, structured, reviewed, and closed.
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Sep. 29, 2025As enterprises confront the growing demand for instant responsiveness, data streaming is becoming an essential business agility and intelligence enabler. Traditional batch-based systems are giving way to zero-lag infrastructures that continuously process and act on data as it flows. From fraud detection and hyper-personalization to predictive maintenance and real-time supply chain visibility, streaming is moving from pilot projects to enterprise-wide transformation. This report examines the rise of streaming as a foundation for real-time intelligence. It provides a clear view of why enterprises are embracing data in motion, where adoption is gaining momentum across industries and functions, and how technology providers are responding with new capabilities and platforms. It also looks at the organizational and technical challenges that continue to limit scale and identifies practical best practices to build resilient, scalable streaming architectures that drive measurable business impact. By combining a structured overview of the ecosystem with insights into use cases, market dynamics, and scaling practices, this report equips business and technology leaders to reimagine how decisions are made in the moment, and how enterprises can move from being reactive to predictive in the digital era
