The convergence of natural language processing (NLP) and advanced analytics is fundamentally reshaping how businesses interact with data, moving beyond static reports to dynamic, insightful dialogues. This shift is driven by a critical need for speed and agility in decision-making, especially given rapid market innovation. Enterprise Strategy Group research indicates that a majority (67%) of organizations are planning to integrate or considering integrating AI agents into business operations,¹ underscoring a growing appetite for intelligent, proactive data solutions that create a more proactive and integrated approach.

But the current state of analytics continues to pose significant challenges for organizations aiming to improve the accuracy and timeliness of data-driven decision-making. Between the constant struggle with data silos, inconsistent data quality, and the difficulty of translating raw data into actionable strategies, it’s no surprise that an overwhelming 78% of organizations agree it takes too long for them to act on insights from business intelligence (BI) tools,² a direct cause of concern and business limitation. Further, many organizations lack the internal expertise to effectively leverage their data assets. The result? Missed opportunities and costly delays.

Organizations require analytics platforms that consolidate diverse data sets, streamline analysis, and enable fast, informed decision-making to empower all users, business and technical alike. While conversational interfaces and embedded chatbots are delivering early value, particularly when incorporating enterprise data, companies demand even more: trustworthiness, speed, and contextualized insights with explainability and strong data governance. These requirements point directly to advanced automation and proactive action. Insert: Agentic AI. Agentic AI leverages autonomous agents to perceive, reason, plan, and execute complex, multi-step tasks, enabling the automation of entire data pipelines—from discovery and transformation to quality checks and self-healing—and translating real-time insights into automated actions, thereby moving beyond reactive analysis to proactive, autonomous optimization and strategic advantage.

^1. Source: Enterprise Strategy Group Research Report, The State of the Generative AI Market: Widespread Transformation Continues, September 2024.

^2. Source: Enterprise Strategy Group Research Report, Unleashing the Power of AI in Analytics and Business Intelligence, May 2024.