As AI continues to reshape work, Global Business Services (GBS) leaders are examining what skills and capabilities are needed for the future operating model. AI enablement is shifting roles away from transactional work toward higher-value activities such as human judgement and strategy.
At Shared Services & Outsourcing Week (SSOW) in San Diego, sessions highlighted the importance of human judgement, domain expertise, and digital fluency in empowering people to work alongside AI. Here are my top takeaways:
AI Fluency: An Essential Skill for the GBS Workforce
AI implementation starts with people. Employees need the confidence and support to use AI effectively in their day-to-day work.
For Dan Melchior, Director, Shared Services, at San Diego State University, that means making training accessible across the workforce: "We have made training available for all employees, regardless of what their job is," he said. This approach positions AI literacy as an enterprise-wide capability, rather than a skill confined to specialist teams.
Sessions also highlighted the value of practical examples to help turn training into understanding. Showing employees how AI can support tasks such as Excel analysis and professional communication makes its potential tangible. Building that understanding is the first step towards AI fluency.
Why Process Expertise Matters for AI in GBS
However, AI fluency must be matched by process expertise. Bo Senu-Hodo, Global Source-to-Pay Transformation Leader at Astellas Pharma, noted: "I don't think AI reduces your disputes; your processes reduce your disputes."
True end-to-end process expertise means:
- Seeing the whole process: understanding what happens before and after each task.
- Connecting the handoffs: recognizing dependencies across teams and systems.
- Finding root causes: identifying weak points before adding automation.
- Managing exceptions: knowing where human judgement is needed.
- Focusing on outcomes: connecting each activity to customer needs and business results.
Process expertise starts with judging what needs to change before AI even comes into the picture.
Problem-Solving and Critical Questioning in AI-Enabled GBS
Employees must continue to question whether a process is effective and whether outputs make sense. For example, discussions emphasized defining the business need before selecting technology. That discipline provides a basis for ongoing review:
- Are we solving the right problem?
- Has the context changed?
- Does this exception require human intervention?
- Does this exception require process redesign?
Human judgment therefore connects process understanding with continuous improvement. The skill is about knowing when to challenge the answer – and when to rethink the work itself.
Adaptability and Change Appetite for AI Adoption
Adaptability is a critical competency for AI implementation: employees need support to learn new tools, redesign workflows, and adjust to evolving roles. Navigating change and tackling change fatigue was a key focus at SSOW.
Delara McManus, Director, IT Finance, Keurig Dr Pepper, observed: "I think we are all going to laugh about how long it took us to convince everyone to use AI." Helping people understand why work is changing (and what that means for them) is central to adoption and success.
Putting that into practice also requires teams to collaborate. As Michele Turner, Head of Global Business Resilience and Program Services at Marriott International, put it: "Resilience is really a team sport; we cannot do this in our siloes."
Adaptability is a collective capability, built on trust, communication, and collaboration.
The Future of GBS Workforce Skills: Bringing People and AI Together
Preparing the GBS workforce for the AI era means developing more than technical competence. AI fluency needs to sit alongside end-to-end process expertise, critical questioning, and human judgement. Adaptability connects these skills, helping teams make sense of changing roles and evolving work.
For GBS leaders, the workforce development priorities are to:
- Make learning accessible
- Maintain a strong focus on process expertise
- Empower enterprise-wide AI fluency
- Connect AI to business needs
- Support people to challenge outputs
As AI reshapes shared services, leaders need to keep asking "What do our people need to become capable of next?"
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