AI in GBS: The Gap Between Ambition and Execution
Most organizations are still early in their AI journey, with nearly half in pilot phase and only around 10% live in production. Expectations around productivity, workforce impact, and transformation continue to outpace measurable results. Drawing on SSON Research & Analytics' latest benchmarks and market research, this session establishes the baseline across adoption, investment, priorities, and outcomes to help leaders calibrate where the market stands and what matters next.
The ambition to scale AI is clear. SSON Research & Analytics found that 74% of organizations expect Agentic AI to significantly change their service delivery model. Yet only 11% have Agentic AI live in production, and none report scaling it across the enterprise. This execution gap sits at the heart of today's discussion.
The panel will examine where scaling breaks down across process design, ownership, governance, and day-to-day execution. What slows progress? What did leaders underestimate? And what has made the difference in embedding AI into core workflows and delivering measurable impact at enterprise scale?
AI is forcing GBS organizations to rethink how work gets done, but technology is moving faster than the workforce structures built to support it. Redesigning workflows has proven far easier than redefining roles, career paths, and governance models. This session explores how leaders are navigating that gap in practice, where transformation efforts are stalling, and what's keeping organizations stuck as GBS operating models evolve.
SSON Research & Analytics data shows that 85% of organizations are already committed to the GBS model, yet many are reassessing how the model should operate in an AI-enabled enterprise. As organizations modernize ERP environments, expand scope, and push for faster enterprise execution, leaders are confronting practical questions around governance, process ownership, standardization, and decision-making. Some are redesigning structures to improve agility and orchestration, while others are doubling down on centralized control and operational discipline. This panel will focus on the real operating model decisions leaders are making today, including what should remain standardized, where flexibility is needed, how ownership models are evolving, and what changes are actually helping GBS operate more effectively at enterprise scale.
What does it take to move beyond experimentation. This session walks through how one organization structured governance, aligned stakeholders, and embedded AI into existing processes rather than layering it on top. The focus is on decisions made, trade-offs considered, and what changed along the way.
Many organizations are still struggling with operational bottlenecks, inconsistent processes, and limited visibility across workflows despite years of transformation investment. As expectations around speed, efficiency, and enterprise execution increase, leaders need a clearer understanding of where work is slowing down and why. This session will explore how organizations are using process intelligence to identify inefficiencies, improve coordination across operations, and support more scalable execution across GBS.
The expectations placed on GBS by finance leadership are changing rapidly. Cost and efficiency still matter, but CFOs are increasingly looking to GBS to improve execution speed, strengthen control, and deliver greater business value. SSON Research & Analytics data shows that value creation is now considered nearly three times more important to customers than cost reduction alone. At the same time, many organizations are still struggling with fragmented processes, slow decision-making, and operational complexity despite years of transformation investment. This session will focus on the practical changes leaders are making to improve agility, standardize operations, support enterprise priorities, deliver more measurable business impact, and the interdependencies that exist between GBS and transformation.
AI agents are emerging as a new way for shared services organizations to handle repetitive work, support employees, and improve operational performance across functions. From finance and HR to IT and customer operations, organizations are beginning to deploy AI agents that can manage exceptions, work across multiple systems, and operate under centralized governance.
This session will examine where AI agents are creating measurable value, what challenges organizations are encountering, and what leaders are learning as they scale adoption across shared services.