#agentic AI #Virtusa #Customer-Centricity

Understanding the Agentic AI Divide

In a world where Artificial Intelligence (AI) continues to reshape the corporate landscape, a recent study by Virtusa Corporation sheds light on a concerning trend: 86% of enterprises are failing to leverage customer data effectively, leading to a widening performance gap. This divide, identified in the report titled "Beyond customer obsession: Where data, AI, and empathy converge," outlines the stark differences between organizations that treat customer data as a strategic asset and those that see it merely as an operational byproduct.

The Importance of Customer Data

Virtusa's research highlights that only 14% of businesses are using customer data as the strategic engine necessary for victory in the AI era. These 'customer-obsessed' leaders witness revenue growth of 6% or more, whereas firms that are classified as 'customer-indifferent' struggle with data silos and legacy systems, leading to stagnation or declines in performance. According to Euan Davis, a senior vice president at Virtusa, the true value of data lies in its intelligent application, stating, "Leaders treat data as oxygen, not exhaust. Data is the strategic asset that fuels every decision."

The first era of AI was about enablement, but the second era emphasizes the need for companies to rethink their approaches entirely. They must redesign workflows to accommodate autonomous agents that reimagine how value is created.

The Insight Conversion Problem

A significant takeaway from the study is the insight conversion issue many organizations face. Contrary to common belief, it isn’t a scarcity of data that hampers companies, but rather the inability to transform existing data into actionable insights. Leading companies are effectively utilizing various data types at rates between 83% and 100%, while their less effective counterparts struggle with rates as low as 0% to 11%. This indicates a crucial need for data transformation processes to derive insights that can drive operational change.

The Role of Agentic AI

The emergence of Agentic AI serves as a pivotal factor in distinguishing between these two categories of companies. Results from the study indicate that 89% of high-performing firms are strategically positioned to deploy Agentic AI, while only 32% of underperformers share this readiness. The swift evolution of AI capabilities means that the opportunity for a catch-up strategy is rapidly diminishing. Over the next few years, AI agents are expected to transition from merely “thinking” roles to taking definitive actions, prompting a complete reengineering of enterprise workflows.

Data, Empathy, and Decision Making

An intriguing aspect of the research is the observation that successful organizations operate like “clairvoyants”. They effectively utilize AI to uncover subtle behavioral signals. For example, around 82% of customer-obsessed firms utilize these insights to enhance their products, in sharp contrast to only 33% of indifferent firms. This indicates the profound impact that effective data interpretation can have on product innovation and customer satisfaction.

The Hyperscaler Advantage

To manage the deluge of data, high-performing companies are increasingly relying on hyperscaler cloud platforms, such as AWS, Google Cloud, and Microsoft Azure. These leaders handle over 50% of critical tasks on these advanced platforms, which significantly boosts efficiency in areas like sales lead identification and product usage optimization.

Bridging the Trust Gap

Firms that exemplify this transformational shift include financial institutions utilizing cloud-native platforms for processing transactions at extraordinary speeds whilst combating fraud. Agentic AI, in this sense, is not just about enhancing operational processes; it aims to foster trust and smooth experiences for customers.

The Uneven Distribution of AI Value

Despite the advantages that successful firms reap from AI, the distribution of these benefits remains uneven. 90% of data-driven companies leverage AI to uplift core functions, whereas only 35% of less effective firms have made similar strides. This has evolved into a stark performance gap, no longer classified simply as an