Executive Summary: ISG Provider Lens™ Contact Center-Customer Experience Services - Global 2025
30 Oct 2025
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ISG Provider Lens™ Contact Center-Customer Experience Services - Digital Operations - Global 2025
AI redefines contact centers as strategic hubs fueling customer trust and enterprise growth.
Market Scenario
Contact centers are rapidly evolving from traditional, transactional hubs focused on query resolution and support into strategic CoEs that play a pivotal role in driving business growth. This evolution is fueled by advanced technology that is redefining the scope and capabilities of contact centers, pushing enterprises to keep pace with the rapid industry changes. KPIs are swiftly shifting from simply measuring resolved queries to proactively identifying opportunities, strengthening client relationships and shaping brand perception. As contact centers ascend the value chain, they are becoming essential drivers of loyalty, innovation and long-term business success.
These trends are significantly influencing the changing roles of agents, who are evolving from transactional operators to brand ambassadors and relationship managers vital for customer retention and engagement. This transformation underscores the critical importance of upskilling and reskilling the agent workforce to meet the demands of this dynamic environment and ensure they can adeptly handle the complexity and sophistication of modern customer interactions while seamlessly adapting to changing technologies. Increasingly, humans will remain at the core of all conversations, but the nature of conversations will see a significant shift.
AI is rapidly transforming the CX industry, with growing maturity and expanding use cases that showcase the art of the possible. Use cases such as GenAI-based call summarization and agent assist have moved beyond POC to production. As the technology matures, enterprises increasingly embrace AI to unlock productivity gains, operational efficiencies and scalable innovation across their service ecosystems. Enterprises are also actively partnering with service providers to accelerate these implementations.
In the first half of 2025, the ACV for CX stood at $764 million, reflecting a decline compared to the same period last year. However, the number of awards remained strong, more or less on par with the previous year,indicating that enterprises are still actively leveraging their partners, especially to drive their AI agenda and transform their contact centers.
At the same time, enterprises are encountering several challenges on their AI journey within contact centers. These include integrating AI seamlessly into legacy systems, managing data quality and availability and ensuring responsible deployment. Additionally, organizations must navigate change management, reskill their workforce and clearly define the value AI brings to both customer and agent experiences to ensure successful adoption.
Successful PoC but enterprise-scale deployments are unsuccessful: AI has made significant inroads into the contact center industry, with promising use cases delivering substantial outcomes at the PoC stage. However, many enterprises face challenges in moving beyond the PoC phase. Key concerns include determining how to initiate and scale AI adoption while maintaining the same impact, ensuring data security, minimizing hallucinations, managing outcomes, integrating with existing systems and planning for large-scale rollouts.
Cost dynamics of AI: While AI adoption is widely acknowledged as a strategic imperative across the contact center landscape, it is increasingly evident that AI is neither a quick fix nor an inexpensive endeavor. Despite the enthusiasm surrounding AI, many organizations face significant financial constraints, with transformation budgets historically presenting challenges, even for well-funded contact center units. As a result, enterprises often find themselves in a state of prolonged evaluation or pilot paralysis, hesitant to commit their limited annual budgets without a clear path to scalable, measurable outcomes.
GenAI versus traditional AI: The rapid evolution of technology, from RPA and traditional AI and ML to GenAI and agentic AI, adds to whether the future lies in embracing the more advanced potential of GenAI and agentic AI. This uncertainty further complicates decision-making, as organizations must weigh technological maturity, integration feasibility and business impact before committing to a direction.
A well-defined AI approach: Before embarking on the AI journey, one of the most critical yet often overlooked aspects is data and knowledge management. Effective knowledge management forms the foundational layer for any successful AI initiative. Without a formalized, well-documented workflow, enterprises risk significant knowledge gaps, which can severely hinder the effectiveness and scalability of AI solutions.
Continuous and reusable platform approach: It is often perceived that a single solution is the key to a successful AI project. However, this mindset impedes scalable AI projects. A productized AI platform is not a single solution built for a single use case; it is rather an integrated system of models, data pipelines, orchestration components and governance mechanisms that can support a portfolio of use cases across different functions and industries. The productization of GenAI is not a continuation of the pilot, but a new design challenge that demands modularity, repeatability and maintainability.
Talent building: The AI-driven transformation journey necessitates fundamentally reimagining talent strategy. Organizations must proactively reshape their workforce to meet evolving technological demands, moving beyond the conventional contact center agent profile. Building a diverse talent pipeline with expertise in AI, analytics and digital tools is becoming increasingly vital. At the same time, reskilling existing employees to understand, embrace and effectively apply AI has emerged as a strategic imperative.
How are partners responding?
Contact center service providers are going through their share of shifts in the market.
The BPO industry is evolving significantly, transitioning from traditional service delivery models to integrated BPO and tech orchestrators. This shift reflects a broader mandate to manage operations and embed automation, analytics and AI-driven platforms that enhance agility, scalability and client value creation.
To meet the surging demand for AI, providers are making substantial investments in specialized talent, particularly in data engineering, data science and AI and ML expertise, while simultaneously expanding their solution portfolios to address evolving client needs. Many engage in strategic mergers and acquisitions to accelerate this growth, acquiring niche technology firms or pursuing larger consolidations to enhance capabilities.
Providers are actively redesigning their organizational structures to enhance agility and accelerate decision-making, particularly by empowering local and regional leadership. This decentralized model facilitates rapid responses to market dynamics, cultural alignment and more nuanced client engagement.
AI helps reduce location dependency for enterprises by enabling accent neutralization, where providers actively leverage partnerships with companies such as Sanas to implement the solutions, effectively blurring geographic boundaries and facilitating seamless communication.
The coming years promise dynamic shifts across the industry, driven by technological innovation, evolving location strategies, renewed confidence in AI-enabled gain-share models, the resurgence of voice as a strategic channel, increased provider consolidation and a clear transition from transactional services to strategic partnerships.
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