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
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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
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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.
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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!