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Generative AI for global business services leaders
Gaining a strategic advantage in the data race
How can global business services (GBS) leaders tap into the strategic, creative, insight-generating power of Generative AI? Discover three ways organizations can leverage the technology to gain a competitive edge in the data race.
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Generative AI: Opportunities for global business services leaders
Artificial intelligence (AI) is poised to materially accelerate the global business services journey and enhance GBS’s role in organizations by:
- Facilitating the creation of hyper-personalized internal and external customer experiences.
- Enabling the democratization of insights and expertise—moderating the need for deep experience to execute and manage business processes.
- Allowing for greater scale and automation to be achieved where, previously, organizations were limited by a lack of process standardization.
The key to unlock these advancements for global business services and the entire organization will be data. The output quality of a large language model (LLM) is directly related to the data used to train and fine-tune the model. Having access to swaths of enterprisewide data—customer, operational, transactional, and financial data—GBS organizations are uniquely positioned to take advantage of Generative AI.
As organizations begin to prepare for Generative AI, the landscape of work will evolve from a focus on processing to an emphasis on enhanced data-driven insights. How can Generative AI help global business services leaders forge a strategic path forward?
Generative AI vs. robotic process automation (RPA)
Generative AI is designed to generate new content—intended to be original, creative, and indistinguishable from content created by humans. At the foundation of these multimodal LLMs are petabytes of data, texts, images, and audio training the model to absorb different patterns. The ingested data is evaluated for patterns to derive new content based on the learnings. On the other hand, RPA requires significantly less data as bots rely on predefined rules. There is generally less decision-making involved and, therefore, less flexibility in RPA usage. Generative AI thrives in ambiguity to generate insights while RPA excels at routine, rule-based tasks.
Generative AI strategies for global business services

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.
Explore the next steps global business leaders can take with Generative AI in our full report.
Endnotes
1 Goldman Sachs, “Generative AI could raise global GDP by 7%,” April 5, 2023.
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