Agentic AI
Global Business Services
Redesigning the Operating Model for Agentic GBS
Agentic AI transforms Global Business Services by requiring a redesigned operating model centered on end-to-end process ownership, structured and strategic work instructions, and strong knowledge governance to enable effective, consistent automation.
Agentic AI is not simply the next wave of automation in Global Business Services (GBS). It represents a structural shift in how work is executed, governed, and improved.
Many organizations are approaching Agentic AI as they previously approached RPA: as a technology layer to improve productivity within existing structures. But Agentic AI behaves differently. It does not quietly optimize broken processes; instead, it exposes them.
In Hypatos’ latest whitepaper, “How to Build An Agentic GBS,” CEO, Uli Erxleben discussed how, to embed Agentic AI successfully, the operating model must evolve in three key areas.
If procurement defines one standard, accounts payable applies another, and regional teams apply variations, the agent will surface the inconsistency immediately. It will stop and explain why it cannot proceed.
This significantly increases the importance of Global Process Ownership (GPO). In an Agentic GBS model, GPO must move beyond governance and into active process design. End-to-end standards must be defined clearly and consistently across regions.
Without this clarity, automation stalls.
Agent teams rely on structured, language-based instructions, effectively digital workbooks.
This forces organizations to articulate how work should be performed, including exception handling, policy interpretation, and escalation logic. There is a misconception that Agents are completely self learning, but if you want them to learn the right things, e.g., how exactly your company operates, then a human needs to write and own the instructions.
In many GBS environments, this process knowledge exists informally within experienced operators. Agentic transformation requires it to be documented, validated, and standardized.
Documentation is no longer administrative. It is a strategic infrastructure.
As mentioned above, large language models are powerful reasoning engines. However, they must operate on curated knowledge in regulated business environments.
Organizations must take ownership of:
If knowledge is inconsistent or unstructured, outcomes will be inconsistent.
As of today, the technology is more than capable of doing the majority of tasks GBS can set it. The constraint lies in governance and operating discipline.
Agentic GBS is therefore not just a technology implementation. It is an operating model redesign.
To learn more about How to Build An Agentic GBS, download our guide now or listen to our podcast GBS Rewired.
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