Next Gen GBS and Its Role in Accelerating AI Adoption
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April 30, 2026
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As AI investment accelerates across industries — Gartner forecasts $2.52 trillion in 20261 — a critical question emerges: which operating model is best positioned to drive enterprise-wide AI adoption while managing risk and maximizing ROI? The answer increasingly points to Global Business Services (“GBS”).
Over time, shared services has evolved from a single-function, cost-efficiency model into a multi-functional, enterprise-wide capability. Today’s GBS organizations serve as strategic transformation engines — delivering standardized, scalable and cost-effective transactional and knowledge-based services across complex, global businesses.
For large corporates and private equity-backed portfolio companies navigating growth, margin pressure and digital acceleration, AI presents a unique opportunity. GBS sits at the center of this opportunity — uniquely positioned to both enhance financial and operational performance and act as a catalyst for accelerating AI adoption across the enterprise.
The Evolution of GBS and Synergies with AI
GBS has evolved significantly in the past few decades, but we are now at an inflection point. Two trends are converging to shape the future of GBS and the enterprise-wide adoption of AI:
- Companies continue to expect more from their GBS operations, increasingly pushing the boundaries of lower cost delivery while also expanding GBS into more knowledge-based services to drive insights and revenue opportunities.
- AI can now provide a level of orchestration, execution and insights which not only creates touchless execution of transactional activities but also proactively identifies and assesses opportunities and risks far faster than human capabilities allow.
The urgency of this evolution is evident in the data: 69% of CFOs in 2026 claim to have operational AI capabilities in development, or planned as high priorities; 44% identified AI leverage as a top enterprise value driver.2
Before discussing why GBS is uniquely positioned to accelerate AI adoption, it is essential to understand how GBS has evolved. The table below illustrates this progression from cost-focused operations to strategic transformation platforms for the enterprise:
| Generation | Time Period | Operating Model | Technology Enablement | Value Proposition |
|---|---|---|---|---|
| GBS 1.0: Corporate Hub | Early 1980s | — Pure captive (in-house, centralized) | — Manual processes and basic ERP with minimal automation | — Centralization — Process standardization |
| GBS 2.0: GBS | 1990s | — Captives and emergence of scaled offshoring and outsourcing providers | — ERP becomes more pervasive — Early workflow tools |
— Labor arbitrage — Process standardization |
| GBS 3.0: Multi-function GBS | 2000s–2010s | — Hybrid (in-house captive + outsourcing) | — Basic automation/RPA — Cloud migration — Early analytics |
— Labor arbitrage — Service quality |
| GBS 4.0: Digital Business Services | 2020–Present | — Hybrid global network combined with nearshore/offshore, — AI/digital-enabled |
— GenAI/Agentic AI — Predictive analytics — Integrated data platforms — Digital backbone |
— Strategic transformation enabler — Touchless transactions — Decision-making pace — Revenue growth support — Agility |
How GBS Can Successfully Enable and Accelerate AI Adoption
Tactically, when defining an AI strategy, most organizations establish some form of AI Center of Excellence (“CoE”). In our experience, GBS is a natural home for a high-performing AI COE, as it offers five key structural and capability advantages as discussed below.
- Cross-functional visibility enables identification of the highest ROI uses cases: With oversight and tactical involvement across multiple functions and domains, GBS can identify AI opportunities that span multiple functions, allowing for the implementation of use cases with the highest value potential.
- Data foundation and governance: Since GBS manages large volumes of enterprise data (critical for training and deploying effective AI models), it is in a unique position to establish and test the AI governance, ethics, compliance, and controls to ensure the safe development and scaling of AI solutions across the organization.
- Centralized pilots and platform for scaling: GBS is a logical platform to lead early AI pilots. GBS can test AI use cases in high-volume, and work on standardizing processes before broader rollout. Proven solutions can then be scaled enterprise-wide, reducing risk and duplication.
- Innovation and value creation hub: Forward-looking GBS operations are increasingly expanding their scope to support complex, knowledge-based use cases around sales support, revenue growth and operations, in an effort to drive growth, agility, innovation and competitive advantage. Many of these more strategic activities are ideal use cases for AI.
- GBS as a change agent: GBS can act as a strategic catalyst for AI enterprise-wide adoption by leading the way and building momentum. It can not only identify and implement high value use cases but also demonstrate measurable ROI, positioning itself as the natural change agent and capability center for AI deployment.
Conclusion
The convergence of AI capabilities and GBS maturity represents a pivotal moment for organizations seeking competitive advantage through digital transformation. GBS provides the centralized governance, process and data discipline, and cross-functional visibility required to de-risk AI adoption while accelerating measurable business outcomes.
For CFOs and operational leaders, the strategic imperative is clear: position GBS as a critical hub for AI enablement. Organizations that act decisively are best-positioned to unlock immediate efficiency gains and to establish the foundation for sustained value creation in an increasingly AI-driven marketplace.
Footnotes:
1: “Gartner Says Worldwide AI Spending Will Total $2.5 Trillion in 2026,” Gartner (January 15, 2026).
2: “2026 Global CFO Survey Report,” FTI Consulting (2026).
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Published
April 30, 2026
Key Contacts
Senior Managing Director, Leader of AI & Digital Transformation
Senior Managing Director