The AI Adoption Gap in Shared Services: Why Only 8% Scale Beyond Automation

“90% of Global Capability Centers (GCCs) and shared services teams are experimenting with AI. Only 8% are scaling it.” This data point, highlighted in research from BCG and ISG, underscores a widening gap: most organizations are stuck at automation, while only a few are advancing into true AI adoption.

The urgency is clear: scaling AI is no longer optional. For Shared Services leaders, this divide defines who will lead vs. who will lag in the next decade.

‍

Why Shared Services Plateau at Automation

Traditional automation, mainly RPA (Robotic Process Automation) was never designed for agility. Instead of fueling transformation, it creates fragility and stalls progress.

Here’s why:

• Brittle, rules-based bots break when processes shift or data changes.
• Exception overload: ISG reports that 40% of automated workflows still need manual intervention.
• High maintenance costs erode efficiency gains and drain IT budgets.
• Limited scalability: RPA handles tasks, not enterprise-wide intelligence.

The result? Shared services teams achieve tactical cost savings but fail to move up the value chain. They remain stuck in execution rather than becoming strategic partners

‍

What the Leading 8% Do Differently

The 8% of GCCs and shared services teams that have successfully scaled AI follow a repeatable playbook.

‍

1. Build AI Centres of Excellence (CoEs)

Top performers launch AI CoEs that centralize governance, innovation, and delivery. BCG notes that over 70% of leading GCCs run formalized AI CoEs to standardize best practices and accelerate deployment.

‍

2. Go Beyond Scripts with Agentic AI

Rather than brittle RPA scripts, leaders adopt agentic AI — systems that can learn, adapt, and respond in context. This makes automation resilient and enterprise-wide, not just siloed.

‍

3. Redefine the Workforce with AI Employees

Forward-looking shared services organizations integrate AI Employees as digital coworkers in finance, HR, procurement, and analytics. These AI Employees work alongside humans, increasing agility without adding headcount.

‍

4. Measure Outcomes, Not Activities

Laggards track bot hours. Leaders track impact: faster month-end closes, improved compliance, sharper forecasts, and greater business agility.

‍

RPA Bots vs AI Employees: A Paradigm Shift

The difference between bots and AI Employees is the difference between being stuck in tactical execution and moving into strategic enablement.

• RPA Bots: Fragile, rule-based, tactical. Focused on activity.
• AI Employees: Adaptive, outcome-driven, strategic. Work alongside humans.

AI Employees: Adaptive, outcome-driven, strategic. Work alongside humans.

Upgrade from RPA Bots to AI Employees today

‍

Shared Services 2.0: From Efficiency to Agility

The future of shared services is not about cost reduction alone. It’s about agility and enabling enterprise strategy.

• Efficiency is table stakes. Every organization has RPA.
• Agility defines leaders. AI Employees are the differentiator.
• Shared Services teams evolve. No longer execution hubs, they are becoming strategic agility partners for the enterprise.

This evolution is exactly what will dominate discussions at Shared Services & Outsourcing Week (SSOW) Houston 2025. The conversation is shifting from “How do we automate?” to “How do we scale AI responsibly and strategically?

Meet us at SSO Week 2025

‍

The Opportunity: Will You Be in the 8%

Right now, 90% of shared services and GCCs are stuck experimenting. Only 8% are scaling AI. That gap is not just a risk, it’s a once-in-a-decade opportunity to leapfrog competitors.

Supervity is helping shared services leaders bridge this gap with AI Employees that transform execution into strategic agility.

‍

👉 Meet us at SSOW Houston to see how Supervity AI Employees are powering the next era of Shared Services

📌 Talk to us today: Request a demo