Digital labor is changing the boundaries of shared services, and its impact extends far beyond automation and efficiency. Organizations are exploring how AI enhances existing services and unlocks entirely new categories of services that can be centralized, scaled, and delivered through shared services. What began as a back-office optimization effort is evolving into a strategic engine for enterprise innovation.
By harnessing AI’s analytical and generative power, shared services are redefining their value proposition from process execution to enterprise enablement. They are becoming providers of insight, intelligence, and new digital capabilities that can be leveraged across functions.
To capture these opportunities, organizations must implement an expanded portfolio that includes AI-enabled services and a reimagined talent model with new roles that define who governs, trains, manages, and continuously improves digital labor.
What New Services Can AI-Enabled Shared Services Deliver?
AI’s capabilities make it possible to centralize and scale non-traditional services within shared services, broadening the scope of what these organizations can deliver. These services become scalable because digital labor can execute work consistently at volume, allowing shared services to expand beyond traditional transaction processing and inquiry resolution. Enhanced services fall into three categories:
Insights & Intelligence
Analytics & Insights-as-a-Service
Predictive and Prescriptive insights embedded into business workflows
Dynamic Knowledge & Policy Advisory
Real-time guidance and policy interpretation, continuously updated
AI enables: Enterprise-wide intelligence delivered at the point of need.
Autonomous & Proactive Services
Proactive Support & Issue Prevention
Issue identification and resolution before users raise them
Autonomous Workflow Orchestration
Agentic AI transaction execution and coordination of end-to-end processes
AI enables: Reduced reliance on manual intervention and exception-based work
Experience & Service Expansion
Cross-Functional Service Delivery
Seamless handling of requests across HR, IT, Finance, and beyond
Personalized Experience Enablement
Tailored, context-aware interactions at scale
AI enables: Unified service and personalization without added headcount
Collectively, these services shift shared services from efficiency engines to enablers of enterprise intelligence and agility, offering capabilities that directly influence growth, decision quality, and customer experience. The new offerings can identify cost savings and expand the impact of business partnering through the use of digital labor.
Why Digital Labor Requires New Shared Services Roles
As shared services expand their AI-enabled portfolio, new capabilities are required to deliver and sustain the services and operations. These offerings demand roles that blend technical acumen, data stewardship, and governance expertise. The future organization evolves to include designers, trainers, and stewards of intelligent operations.
Delivering analytics, automation, and digital knowledge services requires new skill sets, governance structures, and blended human and digital roles that ensure trust, quality, and adaptability. These new roles can be addressed as an expansion or evolution of responsibilities without necessarily adding headcount, by leveraging the capacity made available through digital labor and training employees to perform these roles.
Roles Needed to Govern and Scale AI Effectively
1. AI Operations and Governance
As AI-enabled work scales, organizations need clear accountability for model accuracy, data quality, compliance, and responsible use. These roles help ensure digital labor operates within defined standards and remains aligned with business requirements.
| Role | Purpose |
|---|---|
| AI Trainer/Content Curator | Teaches AI models, curates enterprise knowledge, and ensures systems stay current with policy and program updates |
| Data Steward/Data Analyst | Manages data quality, consistency, and compliance for enterprise AI systems; interprets AI insights and communicates findings |
2. Digital Workforce Management and Enablement
Once governance standards are in place, organizations need roles that translate those standards into day-to-day digital labor performance by deciding where AI is deployed, how exceptions are handled, and how human and digital labor work together.
| Role | Purpose |
|---|---|
| Digital Workforce Manager | Manages digital labor as a workforce by overseeing performance, resolving exceptions, and optimizing how work is executed across human and digital resources; Defines what work shifts to digital labor over time |
| AI Platform Architect/Solutions Engineer | Designs and integrates AI technologies into service delivery architecture, ensuring scalability, interoperability, and security |
3. Transformation Leadership and Value Creation
Shared services also need leaders who can convert AI-enabled capabilities into measurable enterprise value by prioritizing use cases, driving adoption, and embedding continuous improvement across the service portfolio.
| Role | Purpose |
|---|---|
| AI and Automation Change Leader/Value Champion | Identifies and drives new AI opportunities, manages change adoption, and upskills teams for future work |
These roles exist to manage a blended workforce of human and digital labor. They represent the foundation of an AI-enabled talent ecosystem, one that combines operational discipline with digital fluency. Shared services become hubs of enterprise capability, nurturing talent that blends process expertise with AI literacy and data-driven thinking.
Key Takeaways
AI is redefining the strategic role of shared services and GBS, shifting the focus from back-office efficiency to delivering insight-driven services that improve enterprise performance. As AI expands what can be centralized and delivered at scale, shared services will increasingly provide capabilities like analytics, automation, knowledge management, and advisory support that directly shape business performance.
Shared services’ value will come not just from what services they offer, but from how effectively they manage and scale digital labor. To scale that value, organizations need a clear service portfolio, defined ownership for digital labor, and new roles that govern, improve, and sustain AI-enabled operations.
- Digital labor expands shared services’ capabilities by making analytics, knowledge support, advisory services, and workflow orchestration more scalable across functions.
- New services require new operating discipline, including governance, data stewardship, model oversight, and performance management.
- The workforce model must evolve to include new roles focused on AI training, digital workforce management, platform architecture, and value realization.
The next generation of shared services will serve as the digital core of the enterprise by providing a platform that orchestrates digital labor, data, processes, and enterprise knowledge across functions. With governance, orchestration, and continuous learning at the center, these organizations will lead not only in operational excellence but also in enterprise transformation.
How ScottMadden Can Help
We help shared services and GBS organizations unlock the next level of value through AI-enabled service offerings and role expansion. Our work focuses on three outcomes:
- Defining new service opportunities – Identifying where AI can expand shared services scope and business impact from analytics-as-a-service to elevated customer experiences
- Designing AI-enabled operating models – Developing governance, data, and role frameworks that define how work is allocated across human and digital labor to scale AI-enabled services securely and effectively
- Building digital capability – Upskilling teams, establishing AI centers of expertise, and embedding responsible AI practices to sustain performance and innovation
With this approach, we help clients transform shared services and GBS from process operators into enterprise innovators, creating intelligent, insight-driven organizations ready for the future.
