Point of View

Turn recurring GCC work into Services-as-Software™, not service queues

This Point of View is for CIOs and CTOs rethinking how their global capability centers (GCCs) turn recurring work into reusable Services-as-Software™ instead of scaling headcount.

CIOs and CTOs expect more from global capability centers (GCCs) without hiring more or creating smaller greenfield GCCs with larger mandates. The question is, how does the center keep creating value every time demand rises? Enterprises have pushed their GCCs beyond execution toward reinvention, innovation, and redesigned lower FTEs delivering new KPIs. A model heavily dependent on people may add capacity, but will often struggle when the enterprise expects reuse, consistency, faster turnaround, and the ability to adjust as conditions change. The answer is Services-as-Software™.

New-age LLMs have created the opportunity to merge services into software. Over time, GCCs must transform repetitive work into capabilities that software can manage, including reusable workflows, data products, agentic services, and governed platforms. The reusable assets should be scalable and can accommodate the rising demands from enterprise leaders.

62% of GCCs already run AI in production, well beyond pilots

According to the HFS GCC case studies suite, 62% of GCCs already use AI (see Exhibit 1). They run it in production or embed it into operations beyond pilots. The technologies in use include generative AI, intelligent automation, machine learning, and a growing set of agentic AI deployments.

Exhibit 1: AI is already embedded in GCC delivery, not just piloted

Donut chart splitting global capability centers into two groups by how they deliver. One segment is labeled 62% and the other 38%, drawn from the HFS Research GCC case studies suite. The report's body states that 62% of GCCs already use AI, running it in production or embedded in operations beyond pilots, with the remaining 38% not yet AI-centric. Source: HFS Research, 2026.

Sample: 174 GCC case studies, June 2026
Source: HFS Research, 2026

The case studies revealed that a few enterprises are already moving toward a Services-as-Software model, with credible outcomes in terms of agent and bot performance and cost savings. Here are a few GCC examples transforming the workflows to AI-centric:

  • A global consumer goods company built a centralized digital capability that scales product development across functions and regions, delivering over 50 digital solutions on 12-to-16-week cycles, achieving more than a 30% cost reduction and up to 5% revenue growth.
  • A multinational bank consolidated shared services to process thousands of recurring business transactions, such as invoice processing and purchase order creation, into reusable software. This enabled 81 bots to handle 18,000 transactions a day, delivering $55 million in cost savings and avoiding expenses while improving key risk indicators by 80%.
  • A global semiconductor leader created an agentic AI capability at its center that manages contract-based billing with 80% efficiency, saving 15,000 hours a year through automated accruals and resolving vendor queries twice as fast.
A human + machine model can deliver the enterprise mandates at scale

The first-gen GCC was to reduce costs, improve control, and access talent. The current approach requires a different way of executing the work. As a center moves from staff augmentation toward Services-as-Software (see Exhibit 2), the source of value shifts from people to collaborations between people and tools, and finally to work coded in software and used as a reusable capability.

Exhibit 2: Centers that stay in human-led delivery will struggle to scale reinvention

Five-stage maturity diagram titled "Execution model for GCC operations," laid out left to right along a human-to-machine spectrum and split into two eras: Current (2000 to 2025) and Emerging (2025 to 2028 and beyond). The five stages are staff augmentation, technology-enabled services, platform-led services, AI-led agentic services, and Services-as-Software. The diagram describes each stage across two rows. For design characteristics: staff augmentation is human-led delivery with limited change to the operating model; technology-enabled services is human delivery augmented by proprietary tools or accelerators; platform-led services uses embedded platforms that drive unified data, delivery, visibility, and control; AI-led agentic services is built on platform foundations where smart agents adapt tasks in real time and collaborate with humans; and Services-as-Software is encoded and delivered primarily through software with minimal human intervention. For outcome characteristics: staff augmentation fills capacity gaps quickly, drives no structural transformation, and relies on scale; technology-enabled services enhances delivery with tools but leaves value siloed and lacks adaptability or end-to-end visibility; platform-led services improves service consistency and scalability, enables orchestration across functions, and establishes a foundation for AI augmentation; AI-led agentic services learns and adapts with feedback loops, augments human decisions and execution, and reaches matured orchestration; and Services-as-Software delivers autonomous execution of outcomes, maximum adaptability and speed, and fully embedded intelligence and orchestration. An arrow beneath the stages reads "Increasing embedded intelligence, straight-through processing, autonomous, and outcome-driven orchestration." Source: HFS Research, June 2026.

Source: HFS Research, 2026

Under Services-as-Software, rising demand should drive reuse instead of hiring. In a more traditional setup, rising demand usually means more intake, more projects, more tickets, additional teams, and a heavier management burden. With a Services-as-Software approach, the same rise in demand should lead to greater reuse.

A finance close can become a workflow product, a regulatory reporting cycle can turn into a governed data and process asset, a request for customer analytics can evolve into a reusable data product, and a method for responding to cyber incidents can transform into an intelligent operating layer. It also changes the leader’s job: rather than only managing the work flowing through the center, they determine which work to eliminate, which to keep expert-led, which to automate, and which to develop into a reusable capability for the enterprise.

Providers are creating tools that help GCCs make this shift, turning their offerings into reusable software that a center can adopt rather than rebuild by request. For example, Infosys productized the EdgeVerve AI platform and Topaz, Wipro is pushing software-led services through its Fusion proposition, and Genpact transforms process expertise into agentic operations for a GCC through AI Gigafactory and AI Maestro.

The Services-as-Software model needs product discipline to create business value

Enterprises do not need to productize every service at once. A sensible starting point is the work that occurs frequently, depends on rules and data, and is important to the business. A simple matrix keeps the discussion focused on the design of the work rather than on tool selection. Sample activities in the upper-right quadrant, where high repetition meets high value, would be a great place to start (see Exhibit 3).

Exhibit 3: Productize the work that is repeatable and valuable

Two-by-two matrix plotting business value on the vertical axis against repeatability on the horizontal axis, sorting GCC work into four quadrants. The top-left quadrant, high value and low repeatability, is labeled "keep expert-led" and includes strategic FP&A and M&A analysis, complex cyber incident response and threat hunting, enterprise architecture and solution design, and major audit and litigation support. The top-right quadrant, high value and high repeatability, is labeled "productize into Services-as-Software" and flagged "start here," and includes financial close and record-to-report, regulatory and compliance reporting, recurring customer and operations analytics, payments processing and reconciliation, and KYC and AML checks. The bottom-left quadrant, low value and low repeatability, is labeled "eliminate or simplify" and includes one-off manual data pulls, ad hoc spreadsheet reconciliations, and duplicate or redundant status reporting. The bottom-right quadrant, low value and high repeatability, is labeled "automate" and includes password resets and access provisioning, invoice data entry and matching, standard report generation and distribution, and ticket routing and categorization. Source: HFS Research, 2026.

Source: HFS Research, 2026

Most GCCs already have tech infrastructure; what they often lack is true product ownership. A center pursuing Services-as-Software benefits from product roadmaps instead of a steady flow of project intake from product owners. It also needs investment models that support reusable capability rather than just annual capacity, along with a commitment to managing workflows across functions, since software-led services rarely stay within organizational boundaries.

The Bottom Line: The recurring problem on your desk today is the choice: productize with a Services-as-Software model, or staff it again next quarter.

Recurring work compounds. If you send it back into a queue, you will eventually hand the asset over to a provider’s platform or an automation vendor. If you encode it as governed, reusable software, the GCC becomes something the business builds around instead of optimizing away.

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