Will generative AI mean the death of service delivery centers?

AI in shared services is transforming the industry through co-working, autonomous tasks, and democratizing services. Utilizing natural language processing (NLP) and large language models, generative AI simplifies research for users and enables human-like customer interactions, as well augments self-service akin to full-service. Our own adoption of Generative AI, KPMG GenAI for Advisory, demonstrated a significant reduction in task time.

Generative AI can fundamentally change service delivery centers by driving better customer experiences and innovation across an enterprise, directly impacting the bottom line. By automating tasks and personalizing services, shared services can reduce costs and boost productivity with an “always-on” coverage model and on-demand services.

• Rebalancing the build-versus-buy equation
  Outsourcing providers can leverage generative AI to reduce the need for labor. Insourcing digital labor could increase efficiency, making outsourcing more scalable. Leading firms are increasingly adopting multi-vendor outsource models with traditional BPOs, AI-first specialists, and tech players that incorporate generative AI in their solutions.
• How generative AI will revolutionize service delivery centers
  Generative AI transforms service delivery centers by enhancing centralized services, lowering costs, and boosting productivity. By focusing on HR, finance and accounting, procurement, and IT, businesses can identify where generative AI fits within their organization for a successful transition and ultimately capitalize on automated tasks, insightful analyses, and more efficient services.
• Challenges to large language models adoption
  Ensuring a solid data foundation is essential, as improper infrastructure may bring unintended consequences. Companies must invest in digital literacy and responsible adoption of generative AI to succeed. Realizing the complete value of AI will require full enterprise transformation, redefining every layer of the target operating model around AI.
• Getting started with AI in Shared Services
  To implement generative AI in shared services, companies need a framework that aligns their risk tolerance, cultural dynamics, and technology investment. Key steps for successful implementation include:
  • Appointing committed leaders
  • Assessing the organization’s risk appetite
  • Aligning approach and experts
  • Identifying collaborators and vendors
  • Identifying initial use cases
  • Developing strategy for ethical AI
  • Establishing success measures
  • Encouraging an innovation mindset
  • Scoring quick wins