Agentic-first GBS: Moving beyond labor arbitrage

Key takeaways:

• Agentic-first GBS shifts focus from labor arbitrage to business outcomes by combining AI agents with human oversight.
• AI agents can automate 25–40% of typical GBS tasks today, reducing costs while improving speed and quality.
• Moving beyond offshoring lowers exposure to geopolitical, labor, and regulatory risks while increasing control and governance.
• An AI-powered workforce enables employees to focus on higher-value, judgment-based work, improving engagement and impact.

Global business services (GBS) models that are only delivering value through labor arbitrage—transferring tasks to lower-cost, offshore workers—may no longer be enough for many companies. A new, agentic first GBS approach combines AI agents performing transactional tasks, with humans providing oversight and focusing on more strategic work. This model leverages the labor savings already delivered by GBSs with AI to further enhance delivery costs while reducing the geopolitical, branding, and control risks inherent in traditional offshore delivery models. Under human supervision, AI agents can execute many traditional GBS tasks—and they can do them anywhere, under your control, following your governance frameworks.

Agentic-first is already delivering real-world value. At one electric vehicle company, for example, AI agents have partly automated many of the tasks that might otherwise have been performed by an offshore GBS. Agents have automated forecasting workflows, reconciliation, analytics, and monitoring— helping reduce manual efforts in some instances from weeks to less than a minute. This enabled the company to maintain their current labor footprint without having to explore low-cost delivery options.

If you don’t have mature GBS capabilities, an agentic-first approach can let you quickly stand up a resilient and cost-effective delivery model, whether you choose to do so in an onshore or offshore delivery location. If you do have a GBS in place, you can start evolving your GBS capabilities to leverage an agentic-first approach—opening the door to reorganizing your current GBS workforce for even more cost-effective and risk-managed outcomes.

Whether you’re a CEO, CFO, COO, or chief transformation officer, here’s what you should know.

In our experience, AI agents can—right now—deliver between 25% and 40% of the tasks that companies often send to GBS. In an agentic-first approach, AI agents execute routine work, surface insights, and recommend or take actions. People supervise and orchestrate agents, accept or revise their suggestions, and make high-value or high-risk decisions.

Benefits can come fast, then keep growing. We helped one leading tech company, for example, use AI agents to cut 20% of its policy review business process outsourcing (BPO) spend in year one and the goal is to cut spend 70% by year three. The company’s agentic-first model, with agentic auto-reviews for its advertising portfolio, has slashed the need for people in its existing offshore delivery model, with agents conducting manual reviews, while meeting the company’s high bar for judgment and quality. It has also enabled the emphasis within its GBS to shift from labor efficiency to quality and impact. It’s a real-world example of how, by providing near-unlimited digital labor, AI agents can make many traditional operational metrics irrelevant so you can focus on business outcomes instead.

If your stakeholders worry that agentic-first GBS can be riskier than offshoring, it’s time to set the record straight: Offshoring risks are high and rising, as the US government considers new taxes and regulations and global tensions threaten continuity. In PwC’s April 2026 survey, Executive views on policy, risk, and growth, 65% of executives say that tariff policies are a moderate or serious risk to their business. The same number cite geopolitical uncertainty as a moderate or serious risk. Offshore GBS’s dependence on labor can also cause capacity bottlenecks and inconsistent quality—posing risks to customer service and your brand.

By automating services, agentic-first GBS helps lower your exposure to geopolitical, labor market, and tax risks. Since you own these capabilities, you can design and oversee them to meet your data, risk, and auditability requirements. Monitoring agents, human-in-the-loop governance, and specialized controls can all be at your disposal. And agents can let you scale quickly while upholding consistency and quality.

As AI agents execute many of the repetitive and transactional tasks that people once did, you will still need people—but their roles change and their value often rises. They’ll focus more on agent oversight and orchestration and on higher-value, judgment-based work. That usually requires new training, roles, incentives, and progression paths.

This shift offers advantages to your employees and to you. As your people address more meaningful problems with more modern tooling, time for learning, and visible impact, their value grows. With more automation and in-house work, risks such as sudden vacancies or contractor dependence often fall. And now that you’re offering people a chance to do more engaging work and grow with technology, your recruitment and retention can benefit too.

If you’re not experienced with AI, agentic-first GBS might seem like a big lift. But you can move quickly, guided by a rigorous assessment and a tested playbook.

• Pick key areas. Whether you’re looking to stand up new capabilities with AI agents or to elevate what you already have, good places to start tend to be domains with repetitive tasks and measurable value. These are often back-office functions like finance, IT, or HR that have a history of shared service delivery.
• Ground your analysis in what matters more. To compare agentic-first GBS and traditional models, consider not just labor rates, but also costs and value in key areas: implementation and transitioning, tech and data, ongoing operations, governance and risk, and people and capabilities. For agentic-first GBS, for example, consider the value of having a more capable, AI-powered workforce.
• Assess and adapt your foundation. Consider how to fold agentic-first GBS into your broader AI strategy and be sure that you have an orchestration layer that can provide AI agents with the oversight, control, and governance that you require.
• Raise your ambitions. With agentic-first, you can typically achieve greater value more quickly: AI agents’ ability to make sense even of non-standardized, unstructured data, for example, can let you “leapfrog” many modernization stages that slow other technology initiatives down.
• Execute and scale. Now that you have a chosen starting point, a reliable analysis, and suitable KPIs, you can start creating value: reimagine workflows for agentic AI, acquire the relevant tech, data, governance and risk capabilities, and offer skills, incentives, and change management to create an AI-powered workforce.

An agentic-first GBS doesn’t just lower total costs of ownership and speed up payback times. It also offers faster cycle times, higher quality outputs, less exposure to geopolitical and labor risks, and—perhaps more importantly—the ability to create a more engaged, innovative, AI-forward workforce.

The models are tested. The capabilities are mature. Compared to traditional GBSs, risks can be lower and economics superior. The time to seize this strategic advantage is now.

_{Rahul Kapoor and Adam Nemcsek also contributed to this article}

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