Global Business Services (GBS) is currently at an inflection point with unprecedented opportunities unlocked by AI technologies. AI is fast becoming the future of GBS technology-led transformation, and organizations that can adopt and adapt to an AI-first approach will undoubtedly accelerate their digital transformation and business growth. GBS leaders recognize that AI technologies, such as GenAI, can transform service delivery models, fuel growth, and drive substantial value. Hence, many of them are already making significant investments in AI. However, they are not turning into the proportional value that the AI-first approach could deliver.
But what does it mean to be AI-first in today’s rapidly evolving technological landscape?
In a recent roundtable discussion on “AI-Driven Transformation for Global Business Services (GBS),” organized by EdgeVerve, industry leaders from finance, travel, consumer goods, procurement, and logistics gathered to share insights on implementing AI solutions. They also shared their expectations regarding the transformative role of AI in business operations. Let’s explore what these GBS leaders seek from AI. While the blog primarily captures insights shared by leaders from specific industries, most of the shared insights might also find applicability and value beyond their industries.
What do GBS leaders in the Consumer, Logistics, and Travel Sectors Seek to Gain from AI?
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Unlocking ROI
Participants at the roundtable discussion unanimously acknowledged that while AI is generating significant buzz, the critical metric remains return on investment (ROI). A leader from a leading shipping and logistics company, for instance, emphasized the importance of this, noting that since they often operate on thin margins (~8-10% logistics costs), any AI implementation must deliver tangible cost benefits for it to be considered successful.
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Transforming data into strategic insights
GBS enterprises are increasingly evolving into strategic players, integrating a broader range of functions to drive efficiency, foster innovation, and gain a competitive edge.
Several leaders, including those from procurement logistics and finance & accounting operations, highlighted how AI can transform complex data analysis into actionable insights for strategic decision-making. For instance, one of the finance leaders anticipates that AI will be able to provide answers to complex challenges (e.g., an increase in logistics costs while witnessing declining sales).
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Connecting siloed systems and processes
As the GBS landscape evolves, the need for a connected enterprise is greater than ever—an enterprise that unites people, processes, technology, and data. EdgeVerve leaders thus stressed the importance of leveraging a unified, AI-powered platform, like EdgeVerve AI Next, to:
- Connect data, legacy systems, and technologies (e.g., ERPs)
- Process unstructured data from multiple sources (emails, PDFs, Excel sheets, etc.)
- Enable intelligent assignment and routing of tasks
- Assist human-in-the-loop workflows for complex decisions
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From people as operators to people as designers
The integration of AI is redefining workforce roles, representing a shift from “software-as-a-service” to “service-as-a-software,” where people become designers of experiences rather than frontline operators. This would enable people to focus more on tasks that drive innovation and strategic value creation.
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Talent and knowledge retention
Industry leaders from a major engineering and technology company expressed concerns about knowledge loss when experienced staff leave or when critical talent is lost. This is where upskilling and right-skilling are necessary, training employees to work with AI-enhanced processes to retain critical talent and create enduring knowledge bases. EdgeVerve leaders emphasized that AI-enabled solutions can help GBS leaders:
- Capture tacit/implicit knowledge through process observation
- Build knowledge bases that persist beyond individual employees
- Enable less experienced staff to perform more tasks earlier handled only by experienced staff
- Enhance user experience, resulting in improved job satisfaction
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Real-time data integration and model performance
Connecting real-time data sources for effective AI implementation is more critical than ever. This is particularly evident in the case of complex, global supply chains. However, connecting and reimagining supply chains is no easy task, as it requires harnessing real-time data for efficiency, customer-centric responsiveness, and data accuracy. According to EdgeVerve leaders, successful AI implementation requires:
- Access to both historical and real-time transaction data
- Training AI models with quality data from enterprise systems to improve performance/effectiveness
- Integrating with major retail and distribution platforms (like Walmart Luminate)
- Capability to process multiple data formats in real-time
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Platform approach vs. point solutions
GBS leaders prefer end-to-end platforms to enhance service delivery and efficiency over point solutions. Platform-based services are integrated, cohesive, and more scalable across operations. While some GBS leaders expressed skepticism about the feasibility of implementing comprehensive platforms across the organization, considering their enterprise readiness and other factors. EdgeVerve leaders advocated for:
- Starting with customer/employee journeys rather than departmental use cases
- Focusing on moving the needle on complete processes vs. partial workflows
- Using platforms to connect various systems and technologies
Looking ahead: AI transformation is inevitable
While cost optimization remains a top priority, GBS leaders are keen to harness the power of AI to transform operations, redefine workforce roles, and enhance operational efficiency to thrive in an increasingly evolving and competitive GBS landscape. That being said, the differentiator is not just technology but how organizations adopt and adapt to it (e.g., point solutions vs. platforms). Early AI adopters can gain a competitive advantage and achieve their transformation goals at speed and scale, provided they effectively embrace AI.
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