In the center office model, GBS is positioned to own the corporate consumer experience, making it the nexus of transactional data and employee interactions. By pairing the two data sets, global business services leaders can use Generative AI to create hyper-personalized experiences for both internal customers and external-facing customers.

For example, the corporate customer function can revolutionize the support model by leveraging data from a full life cycle of employee interactions such as procurement data, service desk inquiries, and human resources information system (HRIS) data, ingesting and training it in an LLM.

• The LLM can be paired with a chatbot, both voice and text through conversational AI, to provide a tailored employee experience via a centralized corporate helpdesk.
• The power of existing data allows models to understand previous inquiries and understand the sentiment of an employee to ensure the specific inquiry is addressed for a positive experience.

By leveraging insights through Generative AI-enabled data models, global business services leaders have an opportunity to centralize additional functions further along on the value chain. The technology allows existing talent access to enhanced insights—insights that can unlock functions further up the value chain. By centralizing transactional, processed-based work, GBS leaders can garner the benefit of expanding the end-to-end process enablement but also the ability to deliver highly efficient solutions back to the business, at scale.

For example, product teams today may have their own decentralized research and development (R&D) teams, operating with the specific product silos.

• Generative AI can assist local teams in design, feature brainstorming, and even testing.
• This is the true creative process that Generative AI promotes through enablement and efficiency.

The latest estimate suggests that within a decade, Generative AI may affect or repurpose approximately 300 million jobs.1 While this is an initial projection, the advancements from both a technology and a functional use case perspective are consistently evolving. From an evaluation of transactional work, leveraging Generative AI for end-to-end use cases to achieve savings is the base case.

• Unlike RPA, Generative AI allows for models to search for comparisons in ambiguous data to support a wider degree of variation in processes. While transactional work is ripe for evaluation, there have been advancements in the creation of Generative AI assistant bots supported by specialized models, to support knowledge-based tasks.
• Depending on organizational maturity and governance, global business services and shared services center (SSC) leaders are well positioned to leverage Generative AI given the control and degree of centralization of common business functions.