The New Global Business Services Question: What Must Come Back Inside?

This voice experience is generated by AI. Learn more.This voice experience is generated by AI. Learn more.Scott Rottmann is President of the Global Consulting Business at professional services firm RGP. He’s advised finance leaders for 20+ years.

gettyFor years, the direction in Global Business Services (GBS) was straightforward. Find work that could be standardized, centralize it, automate what you could, and then move the rest to the location or provider that could deliver it most efficiently.

That logic transformed finance, HR, procurement, IT and other enterprise functions. It created enormous efficiencies and helped organizations build truly global operating models.

But companies are beginning to ask a different question. It is no longer simply: What work can we move out? Increasingly, it is: What can the enterprise no longer afford not to own? ​

This does not mean companies are about to reverse decades of outsourcing, dismantle global capability centers (GCC) or bring transactional work back onshore. In fact, shared services and distributed delivery remain very much part of the future.

Gartner Inc.’s 2026 research finds that 71% of IT managers expect their organizations to increase their use of shared services. At the same time, Gartner expects AI to reshape how companies source technology talent, with up to 40% of external IT resources potentially replaced by internally enabled employees.​​​

Gartner describes the emerging approach as “right sourcing.” In other words, use external providers and shared delivery for work that does not differentiate the business, while keeping strategic, value-creating capabilities inside the organization.

Data is a good example of where ownership matters.

Companies can outsource data cleansing, maintenance and other activities. What they cannot comfortably outsource is responsibility for deciding what their data means, which definitions the organization uses, who owns critical data, what quality standards apply, who should have access and whether the organization can trust that data when important decisions are being made.

Those questions become much more consequential in an AI-enabled organization.

MIT Sloan and the MIT Center for Information Systems Research have been examining this problem from the perspective of data. Their concept of data liquidity—the ability to re-use and recombine data across use cases and organizational boundaries—helps explain why ownership becomes more important as AI scales.

Making data reusable requires deliberate choices about architecture, data preparation, access and governance. MIT describes it fundamentally as a managerial challenge requiring coordination across technology, process and governance. ​

As companies distribute execution across providers, GCCs, platforms and increasingly AI, the organization itself must become better at preserving the business context behind the work.

That creates an important paradox. ​AI makes it possible for more execution to be distributed while simultaneously increasing the value of the capabilities the enterprise needs to retain.

Organizations will need to become more deliberate about which capabilities must remain close to the enterprise. End-to-end process ownership is one such capability.

Organizations may distribute the execution of procure-to-pay, order-to-cash or record-to-report across multiple delivery channels. But responsibility for designing the process, understanding its dependencies, setting standards and improving its performance increasingly needs a clear internal owner. ​

AI governance and enablement are another example. Gartner’s research (linked above) suggests that as AI becomes more distributed across the business, companies will need stronger internal ownership of the standards and governance that determine how it is used. Business teams may build more of their own AI solutions, and outside partners may help develop and deploy them, but decisions about which tools are approved, what data they can access, how risk is managed and who is accountable ultimately need to remain with the organization.

The execution of AI may be distributed. The organization still needs to own the rules around how AI operates.

Transformation capability belongs in this discussion, too. ​For years, organizations could treat transformation as episodic. Nowadays, as transformation becomes continuous, organizations must retain more of the institutional knowledge and capability required to transform themselves.

That is where the role of GBS itself starts to change. As AI and automation absorb more of the routine execution inside GBS, the jobs that remain are likely to become less transactional and more consequential.

Take traditional HR shared-service centers, for example. They will need to evolve into digital solutions and delivery teams as AI absorbs transactional work and creates new responsibilities for emerging roles such as GBS “Productization” Leads, who help redesign functional processes for more integrated, AI-enabled delivery. In other words, as less human effort is required to execute the process, more of the human value shifts to understanding, redesigning, governing and improving it.

Historically, much of the mandate of GBS leaders centered on determining where work could be delivered most efficiently. Increasingly, the job will also be to recognize where separating execution from knowledge would leave the enterprise weaker.

That means asking a different set of questions, such as: ​What should be automated? What can be outsourced? What belongs in a GCC? Where should end-to-end process ownership sit? Which capabilities require deep institutional knowledge? What decisions must remain inside the enterprise?

Rather than simple sourcing questions, shift to operating-model questions.

For decades, companies created advantage by figuring out what work they could move away from the enterprise without losing performance. The next source of advantage may come from being equally disciplined about what they cannot afford to lose: the capability, the knowledge, the ownership and the judgment. ​

Today, the most important GBS question may be what the enterprise must never stop knowing how to do itself.​

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