In my conversations with enterprise leaders across industries, one thing is clear: Agentic AI is poised to fundamentally transform how organizations design and operate their centralized functions and shared services. Conversations among business leaders are not on "if" but rather on "how soon."
Shared services have long been a pillar of enterprise efficiency, delivering scale, standardization, and functional excellence. Technology, for example, is perhaps the most well-known and mature shared service model. Over time, organizations extended this approach even further, centralizing not only core functions like procurement and finance, but also supporting activities such as trade shows and promotions within marketing, or "source-to-settle" processes within procurement, often complemented by captives and BPO relationships.
The trade-off was predictable: operational efficiency improved, but day-to-day responsiveness and proximity to business users and their needs declined. Collaboration overheads increased across the enterprise.
Agentic AI flips this equation. It promises the best of both worlds: preserving the efficiency of shared services, while empowering business units with new levels of speed, autonomy, and precision.
What is an AI Agent?
An AI agent brings three essential capabilities together:
- Autonomous: Operates independently within a defined scope with no need for constant human oversight.
- Intelligent: Understands complex business contexts, learns from interactions, and adapts intelligently.
- Actionable: Initiates and completes tasks, not just offering advice, but driving outcomes.
Case Study: Pharma R&D and the Future of Shared Services
Consider a reasonably tech-savvy pharmaceutical client we work with. If an R&D leader needs procurement support (for example, to find a supplier who can assess patent holdings and consult on production techniques for a new drug), the process is slow and bureaucratic: multiple briefs, RFP rounds, negotiations, and coordination across sprawling centralized teams.
A typical large pharma's procurement organization may number in the thousands, supported by an IT team of 50–100 people, with SaaS and BPO partnerships totaling $50–100 million annually. Yet despite this scale, these structures often struggle to flex to the specialized needs of different business units.
Now, imagine the future. Instead of pushing every need through centralized workflows, procurement support becomes driven primarily by a network of specialized AI agents, each built to autonomously perform specific tasks like supplier identification, patent database scanning, RFP generation, negotiation advisory, and compliance checks.
These agents work semi-autonomously today, with a "human-in-the-loop" model where subject matter experts oversee, guide, and approve their actions, ensuring quality and managing exceptions. Over time, as trust, capability, and sophistication grow, many of these AI agents will evolve into fully autonomous actors, executing entire procurement workflows end-to-end with minimal human intervention.
In this new model, the embedded procurement SME shifts from managing transactions to strategically orchestrating a fleet of intelligent agents: setting priorities, handling complex escalations, and focusing on high-value, judgment-driven decisions.
The result? Faster sourcing, smarter decision-making, and a procurement capability that is global in scale, locally responsive, and increasingly self-driving.
The Broader Shift: Dynamic, Distributed Enterprises
Agentic AI isn't just about making shared services faster; it's about reimagining them completely, a foundational reinvention of organization’s processes and value streams.
Tomorrow's enterprises will be larger yet more agile, standardized yet highly personalized, cost-efficient yet deeply market-responsive. Centralized teams won't disappear, but their roles will evolve: from controllers to orchestrators, from executors to enablers.
As Agentic AI matures, leaders must rethink, not just organizational structures, but governance, talent models, and vendor ecosystems.
The future of shared services is already taking shape: smarter, faster, more autonomous, and profoundly more empowering for the businesses they serve.