Month: July 2025

Overcoming AI Adoption Challenges in GBS Enterprises
Strategies for GBS, GCCs, and Shared Services to tackle AI adoption using a unified platform approach

Global Business Services (GBS) and Global Capability Centers (GCCs) are undergoing significant transformation due to evolving customer expectations and seismic technological disruption. No longer seen as mere back-office support systems, these entities are evolving into strategic partners pivotal to an organization’s digital transformation and AI innovation. Historically, GBS and GCCs were established primarily to harness talent and reduce operational costs by establishing offices in low-cost markets, such as Southeast Asia, Eastern Europe, and South America. However, the narrative is evolving; GBS and GCCs are now changing into engines of innovation, shifting from cost arbitrage models to value-driven transformation hubs.

Yet many GBS units rely on legacy service models, siloed AI pilots, and fragmented solutions. Especially concerning AI implementation, most organizations still seem to be in the “exploration zone”. According to a survey conducted by SSON, 65% of GBS organizations have yet to complete a generative AI project, with most still in exploratory or pilot phases.

How can GBS organizations unlock the true power of AI? How can they reimagine the GBS operating model, overcoming functional barriers, siloed processes, legacy systems, and others? Some of these key challenges are highlighted below.

Challenges of Current AI Adoption Approaches

  • Prioritizing Data Readiness:

    GBS enterprises today are reimagining processes with AI at the forefront. Data readiness plays a critical role in this transformation. According to a study by Appen, a global company that develops datasets for building and improving AI, nearly 80% of the total effort in AI initiatives is spent on data-related activities—sourcing, normalizing, preparing, and integrating data—emphasizing that AI success depends far more on data readiness than on modeling.

    “AI success is 80% data and 20% modeling.”

    Hence, structured, unbiased, and contextualized data is essential to enhance the accuracy and quality needed to drive the intended AI outcomes. Moreover, every successful AI transformation journey must begin with a strong data foundation that involves:

    • Digitizing legacy records
    • Improving data quality
    • Standardizing and integrating data across systems
    • Establishing strong data governance frameworks
  • The Perils of Incrementalism:

    According to SSON data, 51% of organizations are using function-specific AI apps, focusing on incremental, task-specific improvements, small-scale RPA initiatives, or isolated intelligent automation projects. This suggests that many GBS organizations are currently adopting a piecemeal approach to AI, which hinders their ability to achieve enterprise-wide transformation.

    These safe bets, rooted in legacy thinking and a tool-centric mindset, though beneficial in the short term, often create challenges such as disjointed architecture, increased technical debt, and diminished ROI.

  • Key AI Implementation Challenges:

    SSON Research shows that there are five key barriers hindering the adoption of generative AI in GBS: poor data quality, lack of expertise, privacy concerns, unclear ROI, and budget constraints.

    Tackling these barriers with siloed, point-based approaches fails miserably. Hence, GBS and GCC leaders must go beyond siloed AI pilots and adopt a unified, platform-driven strategy to fully realize AI’s transformative power. This approach includes:

    Integrated Architecture

    Bridge people, processes, data, and technology

    Scalable Efficiencies

    Unlock enterprise-wide value at scale

    Workforce Empowerment

    Elevate productivity with AI-enabled tools, workflows, and teams

    Customer Centricity

    Deliver superior, seamless experiences

    Real-Time Insights

    Gain holistic visibility and actionable insights

    Responsible AI by Design

    Embed governance, security, and compliance frameworks

The Future: Embracing a Strategic, AI-First Approach

GBS leaders must embrace an AI-first strategy, transitioning from fragmented process improvement to unified, autonomous operations. Moreover, they must challenge traditional thinking, prioritize incremental improvements, and rethink AI implementation. This is where embracing a holistic, platform-led approach, like EdgeVerve AI Next, comes in.

GBS leaders leveraging this model will future-proof their operations against AI disruptions and reshape value creation across their enterprises and ecosystems.

Do you wish to embark on your AI-first transformation journey?

Download our latest report, created in collaboration with SSON, for more insights into becoming an AI-first GBS!

Connect with our experts now.

Unlocking AI-First GBS Future: Insights from Industry Leaders’ Roundtable Featuring leaders from Consumer, Logistics & Travel

Global Business Services (GBS) is currently at an inflection point with unprecedented opportunities unlocked by AI technologies. AI is fast becoming the future of GBS technology-led transformation, and organizations that can adopt and adapt to an AI-first approach will undoubtedly accelerate their digital transformation and business growth. GBS leaders recognize that AI technologies, such as GenAI, can transform service delivery models, fuel growth, and drive substantial value. Hence, many of them are already making significant investments in AI. However, they are not turning into the proportional value that the AI-first approach could deliver.

But what does it mean to be AI-first in today’s rapidly evolving technological landscape?

In a recent roundtable discussion on “AI-Driven Transformation for Global Business Services (GBS),” organized by EdgeVerve, industry leaders from finance, travel, consumer goods, procurement, and logistics gathered to share insights on implementing AI solutions. They also shared their expectations regarding the transformative role of AI in business operations. Let’s explore what these GBS leaders seek from AI. While the blog primarily captures insights shared by leaders from specific industries, most of the shared insights might also find applicability and value beyond their industries.

What do GBS leaders in the Consumer, Logistics, and Travel Sectors Seek to Gain from AI?

  • Unlocking ROI

    Participants at the roundtable discussion unanimously acknowledged that while AI is generating significant buzz, the critical metric remains return on investment (ROI). A leader from a leading shipping and logistics company, for instance, emphasized the importance of this, noting that since they often operate on thin margins (~8-10% logistics costs), any AI implementation must deliver tangible cost benefits for it to be considered successful.

  • Transforming data into strategic insights

    GBS enterprises are increasingly evolving into strategic players, integrating a broader range of functions to drive efficiency, foster innovation, and gain a competitive edge.

    Several leaders, including those from procurement logistics and finance & accounting operations, highlighted how AI can transform complex data analysis into actionable insights for strategic decision-making. For instance, one of the finance leaders anticipates that AI will be able to provide answers to complex challenges (e.g., an increase in logistics costs while witnessing declining sales).

  • Connecting siloed systems and processes

    As the GBS landscape evolves, the need for a connected enterprise is greater than ever—an enterprise that unites people, processes, technology, and data. EdgeVerve leaders thus stressed the importance of leveraging a unified, AI-powered platform, like EdgeVerve AI Next, to:

    • Connect data, legacy systems, and technologies (e.g., ERPs)
    • Process unstructured data from multiple sources (emails, PDFs, Excel sheets, etc.)
    • Enable intelligent assignment and routing of tasks
    • Assist human-in-the-loop workflows for complex decisions
  • From people as operators to people as designers

    The integration of AI is redefining workforce roles, representing a shift from “software-as-a-service” to “service-as-a-software,” where people become designers of experiences rather than frontline operators. This would enable people to focus more on tasks that drive innovation and strategic value creation.

  • Talent and knowledge retention

    Industry leaders from a major engineering and technology company expressed concerns about knowledge loss when experienced staff leave or when critical talent is lost. This is where upskilling and right-skilling are necessary, training employees to work with AI-enhanced processes to retain critical talent and create enduring knowledge bases. EdgeVerve leaders emphasized that AI-enabled solutions can help GBS leaders:

    • Capture tacit/implicit knowledge through process observation
    • Build knowledge bases that persist beyond individual employees
    • Enable less experienced staff to perform more tasks earlier handled only by experienced staff
    • Enhance user experience, resulting in improved job satisfaction
  • Real-time data integration and model performance

    Connecting real-time data sources for effective AI implementation is more critical than ever. This is particularly evident in the case of complex, global supply chains. However, connecting and reimagining supply chains is no easy task, as it requires harnessing real-time data for efficiency, customer-centric responsiveness, and data accuracy. According to EdgeVerve leaders, successful AI implementation requires:

    • Access to both historical and real-time transaction data
    • Training AI models with quality data from enterprise systems to improve performance/effectiveness
    • Integrating with major retail and distribution platforms (like Walmart Luminate)
    • Capability to process multiple data formats in real-time
  • Platform approach vs. point solutions

    GBS leaders prefer end-to-end platforms to enhance service delivery and efficiency over point solutions. Platform-based services are integrated, cohesive, and more scalable across operations. While some GBS leaders expressed skepticism about the feasibility of implementing comprehensive platforms across the organization, considering their enterprise readiness and other factors. EdgeVerve leaders advocated for:

    • Starting with customer/employee journeys rather than departmental use cases
    • Focusing on moving the needle on complete processes vs. partial workflows
    • Using platforms to connect various systems and technologies

Looking ahead: AI transformation is inevitable

While cost optimization remains a top priority, GBS leaders are keen to harness the power of AI to transform operations, redefine workforce roles, and enhance operational efficiency to thrive in an increasingly evolving and competitive GBS landscape. That being said, the differentiator is not just technology but how organizations adopt and adapt to it (e.g., point solutions vs. platforms). Early AI adopters can gain a competitive advantage and achieve their transformation goals at speed and scale, provided they effectively embrace AI.

Want to learn how an AI-first approach can help you accelerate your transformation journey?

Connect with our experts now.