Monday, March 16, 2026: Agentic AI in Shared Services Bootcamp

Agentic AI is at the center of a shift in how shared services and GBS organizations operate. But what is the reality of how current organizations are deploying the technology? This session will share data from SSON Research and Analytics on what Agentic AI currently means to the industry. This insight-packed session will:

• Showcase the evolution of Agentic AI within current SSOs and GBSOs
• Explore how Agentic AI is redefining operational capabilities, enabling the transition from transactional support to strategic business enablement.
• Analyze the role of data, automation, and AI in building intelligent, adaptive service delivery models.
• Identify the most disruptive trends shaping the future of GBS, with Agentic AI at the center of next level value creation. 

Naomi Secor

Global Managing Director
SSON Research & Analytics

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The Agentic AI era is upon us, with the power to redefine the future of enterprise operations. This session explores how Agentic AI is revolutionizing shared services by driving operational efficiency, accelerating outcomes, and enabling intelligent cross-functional coordination. Attendees will gain insights into the real-world applications, implementation challenges, and governance models required to deploy these systems responsibly and effectively.

Join us to discover how to harness the power of Agentic AI to create self-directed, resilient operations that scale.

Key Takeaways:

• Understand the core capabilities and mechanics of Agentic AI
• Explore use cases in shared services functions and workflows
• Identify challenges around oversight, compliance, and goal alignment
• Learn best practices for implementation, monitoring, and control
• Prepare for the shift from automation to autonomous orchestration 

Peter Galik

Head of Innovation, Analytics and Automation
Takeda Pharmaceuticals

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As enterprises explore the transformative potential of AI, agentic AI is emerging as a powerful enabler for reimagining end-to-end business processes. In this session, we showcase how Ecolab is applying agentic AI solutions across the Lead to Cash value stream—such as cash application, customer master data management, and order-to-invoice workflows—to drive intelligent, autonomous execution at scale. These demonstrations will illustrate not just technology deployment, but how AI can fundamentally reshape process architecture. Beyond implementation, we will explore the broader operating model implications: how organizations must evolve in structure, roles, and governance to support AI-enabled process ownership and decision-making. The session aims to inspire a shift in mindset—from isolated automation to holistic, AI-led process reinvention.

Key Takeaways:

• How agentic AI can drive end-to-end process transformation across domains like cash application, customer data management, and order-to-invoice that move beyond task automation to full process execution.

• What it takes to operationalize agentic AI at scale, including technical design, deployment strategies, and lessons learned from real use cases at Ecolab.

• How to evolve your operating model to support AI-enabled processes, including shifts in organizational structure, roles, governance, and decision-making authority.

Marshall Tokheim

VP, Process Orchestration & AI
Ecolab

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Shared services have long been seen as necessary cost centers—but Agentic AI is changing that. By enabling systems to act autonomously in pursuit of defined objectives, agentic AI unlocks new levels of efficiency, agility, and strategic impact, with the potential outcome of redefining who is necessary for SSOs.

This session focuses on how organizations can leverage autonomous AI agents to move beyond transactional processing and deliver measurable business value. We’ll explore how agentic AI can optimize operations, accelerate service delivery, and surface innovation opportunities across finance, HR, IT, and procurement. Attendees will learn how to identify high-value use cases, calculate ROI, and ensure scalability, accountability, and responsible adoption.

Whether you're looking to reduce operational overhead, improve service levels, or create new strategic capabilities, this session will equip you with the vision and tools to turn shared services into a value-generating powerhouse.

Key Takeaways:

• Discover how agentic AI drives tangible cost savings and operational efficiencies in shared services
• Learn to identify AI initiatives that unlock new revenue streams and strategic opportunities
• Understand how to quantify business value through ROI metrics tied to service quality and speed
• Explore approaches to scaling AI responsibly while maximizing long-term organizational impact
• Gain tools to align AI-driven transformation with broader enterprise goals for sustainable growth 

Valquir Correa

VP, Corporate Finance
Baha Mar

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Brian O'Neil

Senior Director, Shared Services NA
TD SYNNEX

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This session will explore how Operational Excellence (OE) Agents deliver tangible value by integrating digital tools, enhancing problem solving capabilities, and driving process standardization across the organization. At Kerry, over 250 employees have adopted digital solutions that accelerate transformation and investment into 70 White, Yellow and Green Belts. Additionally, the development of more than 70 White, Yellow, and Green Belts, has significantly improved problem resolution speed and effectiveness within their business. And that is just the start. In this session, you will:

Key Takeaways:

• Learn how digital agents like OMP Assistant and CMBOT are transforming day-to-day operations
• Understand the role of Lean Six Sigma trained OE Agents in accelerating problem solving through operational excellence resolution assistants that define, measure, analyze, improve, and control
• Build scalable strategies and standardize work using tools like the standard operating procedure and work instruction coaches
• Demonstrate key metrics that show measurable value delivered by OE initiatives
• Lessons learned and success factors in deploying OE tools and training at scale 

Jesús Villalobos

Operational Excellence Lead GBS Americas
Kerry

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Hector Alderete

Head of Global Business Services, Americas
Kerry

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As Agentic AI moves from concept to capability, Shared Services leaders face a critical question: should we invest in an off-the-shelf platform or build a custom, in-house solution?

This session details the strategic, technical, and operational trade-offs of each path. Participants will explore how to evaluate organizational readiness, assess internal capabilities, and compare long-term value between buying and building agentic AI. We’ll also cover key factors like integration complexity, data governance, scalability, and total cost of ownership.

Through guided discussion and practical frameworks, attendees will walk away with clearer criteria for decision-making—plus concrete next steps for piloting or procuring agentic AI solutions tailored to their organization’s needs.

Key Takeaways:

• Understand the core differences between off-the-shelf and custom-built agentic AI solutions
• Learn how to assess your organization’s readiness and internal capabilities for AI adoption
• Explore critical factors such as integration challenges, data governance, scalability, and total cost of ownership
• Gain frameworks to evaluate long-term value and ROI for buy vs. build decisions
• Receive practical guidance on next steps for piloting or procuring agentic AI tailored to your environment 

April Russo

VP, Compliance & Transformation
USA TODAY Co.

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As shared services embrace autonomous AI agents to streamline operations, the success of these systems hinges on one key factor: data. Examine why high-quality, well-governed, and interoperable data is essential for agentic AI to function effectively across business functions. Discover how data enables decision-making, compliance, and adaptability in AI agents—and what organizations must do to prepare their data ecosystems. Real-world examples and practical guidance will help you turn data into a strategic asset for AI-driven transformation.

Key Takeaways:

• Understand the critical role of data quality, governance, and interoperability for agentic AI
• Learn how robust data ecosystems enable AI decision-making and regulatory compliance
• Discover common data challenges and practical solutions in shared services contexts
• Explore strategies to prepare data infrastructure for scalable, autonomous AI agents
• Gain examples of successful data-driven AI implementations and lessons learned 

Discover how Mercado Libre, Latin America’s most valuable company, is redefining operational agility through a finance transformation powered by agentic AI. Facing the complexity of supporting over 100,000 employees across 17 markets, the finance operations team built an intelligent automation platform and empowered business-led “ambassador” teams to design and deploy AI agents that deliver 100% end-to-end process automation across key finance functions. Through rapid in-house deployment of AI agents in procure-to-pay and order-to-cash, Mercado Libre has streamlined operations, reduced outsourcing costs, and generated $1.8 million in annual savings within three months.

Key Takeaways:

• How agile organizational structures accelerate AI-driven finance transformation.

• Ways to empower business-led teams to design and deploy automation without relying on IT.

• How a culture of continuous innovation drives sustained performance and adaptability.

• Practical strategies for scaling end-to-end automation across complex markets and functions.

• How Mercado Libre’s AI-first finance model enables hypergrowth—launching new businesses and capabilities every quarter.

1) DARIA Presentation:

From the minds of USA Today Co. comes DARIA (Digital Assistant for Rapid Issue Analysis), a Copilot-powered agent designed to assist on-call personnel by searching a curated SharePoint-based knowledge base to resolve support issues faster. Built entirely with Microsoft Copilot and requiring only a standard license, DARIA offers a practical, low-barrier entry point into agentic AI.

Presented by: Brad Meador, Director, Digital Transformation, USA TODAY Co.

2) Agentic AI Demo (Coming soon!)

Brad Meador

Director, Digital Transformation
USA TODAY Co.

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As agentic AI assumes more autonomous roles in shared services, the greatest challenge isn't the technology—it's the people.

This session focuses on how to lead through change as workflows evolve, and human-AI collaboration becomes the norm. We’ll explore strategies to reduce resistance, build trust in AI systems, and support teams as roles shift from task execution to oversight, orchestration, and strategic contribution.

Attendees will gain practical approaches to upskilling, communication, and engagement—helping leaders turn potential disruption into an opportunity for growth, empowerment, and culture change.

Key Takeaways:

• Understand the human impact of introducing autonomous AI in shared services
• Learn proven strategies to reduce resistance and foster trust in AI-driven workflows
• Explore upskilling approaches that prepare staff for evolving higher-value roles
• Gain tools for transparent communication and employee engagement during AI transitions
• Discover how to build a culture that embraces human-AI collaboration, not competition. 

Christof Fahr

Head of GBS Americas
Siemens

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As AI systems evolve from tools to agents capable of making decisions and taking autonomous actions, the stakes for data governance and ethical oversight grow exponentially. This session explores the critical question: Who is accountable for ensuring agentic AI systems operate safely, compliantly, and in alignment with organizational values?

This session will examine the roles and responsibilities across the enterprise—from executive leadership and governance boards to data scientists, compliance officers, and AI product owners. Participants will gain insight into defining accountability, key roles and responsibilities, mechanisms for self-regulation, and how to respond to possible failures.

Key Takeaways:

• Clarity on accountability roles in agentic AI systems.
• Practical frameworks for internal governance and oversight.
• Methods for measuring and enforcing compliance and ethical performance.
• Strategies for transparent reporting and remediation when AI goes off course.