The Rise of Virtual Employees: How AI is Transforming the GBS Workforce

AI in GBS: Enhancing Human Potential through Collaboration

The evolution of Global Business Services (GBS) has been a journey marked by strategic shifts in how organisations approach efficiency, cost management, and productivity. Initially, businesses turned to offshoring and outsourcing as a means to achieve labour arbitrage—reducing operational costs by leveraging lower-wage markets. This model created new operational efficiencies and allowed organisations to scale quickly. Over time, however, it became clear that the next frontier lay in automation. The shift from simply offshoring to automating repetitive processes within enterprise systems marked a significant turning point, as businesses sought not just cost savings but also ways to maximise productivity and drive continuous improvement. Automation started with basic in-app capabilities, but soon grew into more sophisticated solutions like Robotic Process Automation (RPA) and, later, machine learning (ML), each new technology bringing greater precision and complexity to what was possible.

Today, as automation continues to mature, we are witnessing the rise of artificial intelligence (AI), which is taking the evolution of GBS to the next level. AI is now enabling organisations to perform tasks that once required experienced human intervention, streamlining complex decision-making processes, analysing vast datasets, and even providing predictive insights. Yet, the most exciting leap in this evolution is the emergence of agentic AI—truly autonomous virtual employees capable of handling a wide range of functions with minimal human oversight. These virtual employees are poised to take on significant portions of what GBS has traditionally relied on skilled humans to do, offering organisations unprecedented flexibility and the ability to scale without limits. The future of GBS is not just about automation—it’s about empowering organisations to rethink what’s possible and to embrace a new era of productivity and innovation driven by intelligent, autonomous systems.

The Future is Now

AI is already revolutionising critical financial activities as we speak:

• Automating Repetitive Tasks: AI efficiently handles high-volume tasks like invoice processing, data entry, and reconciliation, reducing costs, errors, and employee frustration. By doing so, it creates a smoother workflow and eliminates time-consuming bottlenecks.
• Boosting Operational Efficiency: AI and robotic process automation (RPA) work together to streamline processes, eliminate inefficiencies, and improve outcomes. When combined, these technologies create a system that is both fast and reliable, capable of handling complex workflows.
• Optimising Cash Flow: AI’s predictive analytics provide real-time cash flow forecasts, helping CFOs optimise working capital and improve liquidity. These forecasts not only support immediate financial decisions but also create long-term stability in financial planning.
• Improving Forecasting: AI analyses vast datasets to provide precise forecasts, helping businesses prepare for market fluctuations and economic challenges. By offering data-driven insights, AI enables organisations to make informed, confident decisions.
• Enhancing Risk Management: AI identifies potential risks such as fraud or compliance issues by analysing transaction patterns, enabling proactive risk mitigation. This capability strengthens financial security and minimises potential disruptions.
• Scaling Seamlessly: Cloud-based AI platforms scale easily as businesses grow, integrating with enterprise systems and supporting evolving operational needs. This scalability allows businesses to remain flexible and competitive, even in rapidly changing markets.

GBS of the Future

Agentic AI is set to disrupt a wide range of processes and tasks within Global Business Services (GBS), particularly those that are routine, repetitive, or data-driven. One of the most significant impacts will be on back-office functions like finance, procurement, and HR, where AI can automate and optimise tasks that traditionally require human expertise.

In finance, tasks such as invoice processing, reconciliation, financial reporting, and budgeting are typically time-consuming and prone to errors. With agentic AI, these processes will become fully automated, with AI agents handling everything from processing transactions to generating financial forecasts based on real-time data. AI can also manage audits, ensuring compliance, and flagging discrepancies much faster than a human could. Similarly, in procurement, agentic AI can autonomously manage supplier relationships, negotiate contracts, and even predict purchasing needs based on historical data, eliminating the need for manual intervention in purchasing decisions. Procurement processes will become more efficient and data-driven, reducing costs and improving vendor relations.

In HR, AI agents could take over routine tasks like screening resumes, onboarding new employees, managing payroll, and even assessing employee performance through data analysis. Instead of relying on HR staff for these processes, AI will conduct interviews, assess candidate suitability, and provide insights into employee satisfaction or productivity, all in real time. AI could also manage benefits administration and employee scheduling, reducing administrative burdens.

Customer service operations, traditionally a large part of GBS, are also poised for major disruption. AI-driven chatbots and virtual assistants can already handle a wide range of customer inquiries autonomously, and with agentic AI, they will be able to manage more complex service requests, making decisions based on customer data and providing tailored solutions without human involvement.

Beyond these traditional areas, data management and analytics will see a major shift. AI can now automate data cleansing, processing, and analysis—identifying trends, anomalies, and insights that would have taken human analysts weeks or months to uncover. It can provide business leaders with actionable insights in real time, enabling them to make faster and more informed decisions.

In each of these areas, agentic AI will not just replace manual tasks but will enhance overall decision-making by leveraging advanced algorithms and processing power. As a result, GBS functions will become leaner, more efficient, and more capable of delivering insights and value at an accelerated pace, transforming the role of humans within these functions from task execution to strategic oversight and innovation.

What Do the Agents Mean for You

For employers, virtual employees deliver unique advantages: 24/7 operation, scalability, and unmatched accuracy and speed. These capabilities enable businesses to achieve cost savings, reduce operational bottlenecks, and empower human employees to focus on high-value tasks. In a previous article, Rohit Chandrasekhar and I examined the impact of AI for GPOs and end-to-end processes. By embracing agentic AI, organisations can reshape their operational models and unlock new levels of productivity and efficiency.

For employees and professionals, this evolving workforce model is changing the function in several key ways:

• Evolving Roles: AI is taking over routine tasks like data entry and reporting, freeing human employees to concentrate on strategic areas such as governance, analysis, and business partnering. Additionally, advanced AI systems are becoming decision-making aides by processing and interpreting complex data at unprecedented speeds.
• Creating New Positions: Roles such as “AI Governance Officer” or “AI System Curator” will become essential to oversee AI operations, optimise systems, and align technology with organisational goals. These positions will play a pivotal role as businesses scale their AI-driven initiatives.
• Upskilling Professionals: Employees must acquire expertise in AI management, data analytics, and strategic oversight to fully harness the value of AI. Training initiatives should address both technical and interpersonal skills to foster effective collaboration between human workers and AI systems.
• Reshaping Organisational Structures: As transactional roles become automated or handled by AI, the traditional pyramid structure of finance teams is being redefined. The base of the pyramid, once dominated by transactional tasks, is shrinking. CFOs must prioritise developing talent for strategic, analytical, and oversight roles that sit at the top of this new structure.

As the hybrid workforce evolves, finance departments will transcend traditional transaction-heavy tasks to emerge as centres of strategic insight, driving innovation, cost control, and business growth. This transformation positions the finance team as a value-creating engine, where humans and AI work in harmony to achieve organisational success.

GBS in the Agentic AI Era

The GBS operating model and headcount levels are set to undergo a dramatic transformation as AI and automation take over increasingly complex tasks. Traditionally, GBS functions have been structured around large, centralised or decentralised teams responsible for a wide range of back-office processes, from finance to procurement to HR. These teams have often been supported by offshore and nearshore delivery centres that leverage labour arbitrage to reduce costs while maintaining scale. However, with the rise of AI-driven automation, these traditional operating models will need to shift significantly.

In the future, organisations will require fewer human resources within their GBS functions, as much of the operational work will be handled by AI agents. As AI takes on tasks such as invoice processing, payroll management, financial reporting, and customer service, the demand for large teams of employees to manage these processes will diminish. Instead of maintaining large, labour-intensive operations, businesses will adopt a more streamlined GBS model, where smaller, more strategic teams oversee the automated systems, ensuring they are functioning optimally, addressing exceptions, and driving continuous improvement. The workforce will increasingly focus on high-value tasks like managing relationships with key stakeholders, setting strategic direction, and ensuring compliance and governance in a fully automated environment.

With the advent of agentic AI, the need for offshore and nearshore delivery centres will also be reduced. These centres were traditionally used to handle large volumes of routine, repetitive tasks at a lower cost, but as AI systems operate in the cloud and scale dynamically to meet business needs, organisations will be able to achieve similar or greater efficiency without relying on geographically dispersed human teams. Instead of relying on large offshore hubs, GBS will move toward a more decentralised, AI-powered model, with human employees focused on strategic oversight and innovation.

Ultimately, the new GBS operating model will be characterised by leaner teams, with AI agents handling the majority of tasks that were once the domain of large, human-led teams. The workforce will become more agile and data-driven, focused on value-added activities that AI cannot perform, such as interpreting complex scenarios, making nuanced decisions, and fostering relationships. While human headcount within GBS functions will decrease overall, the role of human employees will become more strategic and higher-value, centred around decision-making, exception handling, and continuous improvement of AI systems.