Accelerate AI-Led Transformation with EdgeVerve AI Next for GBS

Global Business Services (GBS) enterprises today are no longer just about streamlining operations and optimizing costs; they are evolving into unified, intelligently connected enterprises geared at unlocking more value for their parent organizations. Technology is already playing a significant role across diverse types of GBS setups—be it Shared Services, Global Capability Centers (GCC), Centers of Excellence (CoE), or hybrid.

In the current scenario, embracing technology and effectively using it is pivotal to accelerate transformation and sustain business growth and differentiation. Furthermore, recent advancements, including GenAI and Agentic AI, have unlocked unprecedented possibilities for operational excellence, workforce augmentation, and enterprise-wide visibility.

However, as these service delivery models transition from traditional, cost-centric approaches to more value-driven strategies, they face various challenging questions, including below:

The Journey to a Value-Centric and Transformative GBS Model

Per a Hackett Group report , the top priority for GBS leaders in 2024 was “being a strategic partner to the business.” Other priorities included retaining people with critical skills, supporting enterprise growth strategies, delivering GBS digital transformation, and delivering business insights through analytics.

The priorities highlight the need for these organizations to transform themselves by:

The leading GBS organizations recognize the urgency of moving to a value-centric and transformative GBS model, which is reflected in their growing interest and investments in transformation initiatives. For instance, per a KPMG study , about 60% of GBS activity during 2024-2026 is expected to be devoted to transformational services (vs. transaction services). Transformational services are those that mark a fundamental shift in the way an organization does business, delivering significant strategic, financial, or operational value. The significant ramp-up in next-gen technology investments is evident from the fact that 98% of GBS organizations are undertaking or planning GenAl deployments within the next 12 months.

GBS organizations today are transitioning from being “arbitrageurs” focused on traditional transactional services—characterized by cost, volume, and task-based processing—to becoming “transformers” and “integrators”—described by customer-centricity, competitive advantages, and revenue growth.

However, this transformation is not easy as enterprises face significant challenges related to costs, value, talent, technology, and more. Per a BCG study , only 5% of companies have reached the highest level of Global Business Services (GBS) transformation. This statistic highlights the magnitude of transformation challenges and the opportunities for GBS enterprises.

Roadblocks to Achieving GBS Transformation

Here are some of the key challenges that GBS organizations face during their transformation journey:

Value-centricity vs. cost optimization: GBS organizations must take on higher complexity and business-critical responsibilities to shift to a value-centric model. At the same time, they need to maintain or elevate the experiences for their internal stakeholders and customers. Balancing all this while striving to grow profitability margins becomes extremely difficult.

Employee turnover and skills shortage: A Hackett Group’s 2024 study reveals that 50% of GBS executives are concerned about skills and worker shortages. Organizations need to proactively attract, engage, and empower talent to address these challenges. It might need rethinking and prioritizing their experiences from onboarding, upskilling/right-skilling to effective engagement and delivery.

Low success rates of AI projects and scaling challenges: Although GBS enterprises are actively planning and implementing GenAI projects, their success rates still lag far behind. For instance, about 70% of them failed to move from POCs/pilots to the production stage in 2024 due to several factors, including a lack of needed tech, data quality, and skilled talent. Moreover, legacy technologies often pose significant challenges for GBS organizations, from fragmented systems to poor integration and optimization, which hinder their ability to fully utilize innovations like AI, specifically GenAI and Agentic AI, at scale.

With all the above challenges, the transformation journey for GBS enterprises will not be smooth if they continue to rely on traditional approaches and incremental technology changes—they can’t cut it. Progressive GBS organizations are leaning toward a more unified approach that not only connects people, processes, data, and technology but also accelerates the entire transformation with speed and scale.

Step Up Your Game with EdgeVerve AI Next for GBS — A Comprehensive, Unified, and Modular AI Platform for GBS

To tackle the above challenges, EdgeVerve, with its parent Infosys, has worked extensively with the leading GBS enterprises to curate an AI platform dedicated to enterprise transformation. Operations & Service Management (OSM), powered by EdgeVerve AI Next, is a purpose-built solution to drive AI-led transformation of Global Business Services at speed and scale. Packed with Agentic AI workflows and other next-gen features, OSM is a flexible and scalable solution that’s future-ready and highly adaptable for agile and dynamic GBS environments.

How EdgeVerve AI Next for GBS Helps Drive AI-Led Transformation

OSM enables transformation by reshaping all pillars of the Operational model across the value chain, including people, processes, data, and technology. Some of the ways how EdgeVerve OSM helps drive AI-lead transformation include the following:

A Proven Platform for GBS Transformation

Built with EdgeVerve’s & Infosys’ decades of combined experience driving GBS digital transformations, OSM has proven its value by driving the transformation of GBS enterprises across industries, including banking, shipping & logistics, aerospace, healthcare, telecom, and more. These impressive transformations include F&A transformations across 65+ countries, saving $16M in 3 years, 80% faster process discovery, up to 25% hyper-productivity improvements, significant headcount capacity expansion, and others.

Read more on EdgeVerve AI Next for GBS customer transformational stories here.

Way Forward: AI-Led Transformation of Global Business Services

As the GBS landscape evolves rapidly, reinvention is becoming the default strategy wherein organizations that effectively leverage the new wave of technologies can move up in the value chain for their business or risk hitting a growth plateau or becoming obsolete. Enterprises need to rewrite their playbooks with an AI-first approach. Driving AI-led transformation with a more unified approach and embracing value-centric and transformative approaches could be a great differentiator for GBS enterprises of tomorrow.

Want to know how you can take an AI-first approach to GBS transformation with EdgeVerve AI Next for GBS – OSM?

Realizing the Potential of Agentic Process Automation: Strategic Approaches for Successful Implementation

Imagine a team of tireless, intelligent assistants, each capable of understanding context, making decisions, and adapting to the ever-shifting sands of your business processes. This isn’t science fiction; it’s the promise of Agentic Process Automation (APA). In our previous blog, we’ve already touched upon this exciting frontier, envisioning a world where operations move beyond the predictable scripts of RPA, like upgrading from a simple calculator to a powerful AI co-pilot. But unlocking this potential isn’t as simple as flipping a switch. Just as a skilled pilot needs a flight plan and instruments, enterprises navigating the agentic AI airspace face significant turbulence. Let’s explore the headwinds and map out the strategic approaches to ensure a smooth and successful journey for the enterprises.

Challenges in Transitioning to Agentic Process Automation

As powerful as agentic AI can be, there are some inherent constraints that can’t be overlooked. Organizations adopting agentic AI to transform their business operations must overcome several key challenges:

Agentic AI systems require comprehensive, clean, and sufficient data to train models effectively. Before launching agentic AI projects, enterprises must ensure proper data availability, which often involves:

While generative AI can assist with synthetic data generation, significant effort is still needed to provide the right samples for model development. Many organizations underestimate this foundational step, only to discover their AI agents perform poorly due to inadequate training data.

As agentic AI consumes vast amounts of data, privacy and security concerns become paramount. Organizations must implement robust data governance by:

Without proper governance, organizations risk regulatory violations, data breaches, and erosion of customer trust—potentially undermining the very value they seek to create.

For agentic AI that will act on behalf of the organization, implementing Responsible AI principles becomes non-negotiable. These principles include:

Explainability deserves special attention, as stakeholders need to understand how and why AI agents make specific decisions. Organizations should select AI platforms with built-in explainability techniques like LIME, SHAP, or DeepLIFT to ensure decisions remain traceable within the model.

Transforming processes with agentic AI requires organizations to provide the right contextual inputs, including:

Without this intelligence layer, even the most advanced AI agents will struggle to deliver meaningful improvements or could optimize for the wrong outcomes.

Implementing agentic automation workflows requires significant time and effort across multiple dimensions:

Organizations frequently underestimate these implementation challenges, leading to delayed timelines and unmet expectations.

Agentic AI models are inherently probabilistic and not ideally suited for business tasks requiring a very high degree of accuracy. When forcing AI agents into such tasks, organizations often fall into the trap of overengineering by:

This overengineering can defeat the purpose of agentic AI, resulting in systems that are brittle, difficult to maintain, and unable to adapt to changing conditions.

Why a Platform like EdgeVerve AI Next is Critical for a Successful Transition

As discussed above, while agentic AI offers tremendous value, implementation faces significant challenges and requires thorough preparation. Organizations need a comprehensive platform that supports their transition across all dimensions.

EdgeVerve AI Next provides the complete foundation required for organizations to build effective agentic AI workflows:

Agent Functionality
Agent Lifecycle Management
Human-in-the-Loop Integration
Model Flexibility
Tool Standardization
Responsible AI Framework
Enterprise-Ready Controls

By providing these capabilities in a single, cohesive platform, EdgeVerve AI Next enables organizations to overcome the challenges of agentic AI adoption while accelerating time-to-value for their transformation initiatives.

The Strategic Imperatives for Agentic AI Success

As enterprises embark on their journey from RPA to APA, several strategic imperatives emerge:

Enterprises that approach the agentic AI revolution with these principles in mind will be well-positioned to realize its transformative potential—moving beyond the bot to create truly intelligent, adaptive systems that deliver sustainable competitive advantage in an increasingly complex business landscape.

Ready to orchestrate your enterprise’s AI transformation? Contact EdgeVerve AI Next to discover how our platform can help you seamlessly transition from Robotic Process Automation to Agentic Process Automation and lead the AI revolution.