In a clear signal of artificial intelligence's deepening integration into the enterprise, the upcoming Gartner Data & Analytics Summit 2026 will feature a significantly expanded agenda focused on AI, underscored by the prediction that by 2027, half of all business decisions will be either augmented or automated by AI agents.[1][2][3] This projection represents a fundamental shift in organizational operations, compelling leaders in data, analytics, and AI to navigate a landscape of increasing complexity and innovation. The summit is being positioned to directly address these challenges, providing a roadmap for executives tasked with harnessing the transformative power of AI while mitigating its inherent risks. The agenda is set to move beyond theoretical discussions, aiming to provide practical guidance on scaling AI initiatives, managing governance, and ultimately delivering tangible business value.[4][5]

The 2026 summit will place artificial intelligence at the core of its program, dedicating an entire track to the subject.[2] This specialized track will offer sessions covering a wide spectrum of AI-related topics, from high-level strategy and responsible AI principles to the technical nuances of generative AI, large language models, retrieval-augmented generation, and prompt engineering.[2] A key focus will be on the rise of "agentic AI," where intelligent agents are tasked with executing complex workflows and making decisions with increasing autonomy.[4][6][7] Recognizing that the successful implementation of AI extends beyond technology, the summit will also introduce a spotlight track on AI leadership.[2] This program is specifically designed for executives responsible for building and scaling AI teams and capabilities within their organizations.[2] It will explore real-world use cases, effective delivery models, and the critical importance of robust governance frameworks to ensure the safe and ethical deployment of AI technologies.[8][2]

A central theme emerging from the summit's agenda is the concept of "decision intelligence," a discipline that combines data, analytics, and AI to support and automate complex judgments.[9][10] Gartner predicts that AI agents will be pivotal in advancing decision intelligence by managing the intricate analysis and retrieval of data from diverse sources.[11] This move towards AI-augmented and automated decision-making is not about replacing human oversight but rather about creating a synergy between human expertise and artificial intelligence for optimal outcomes.[11] However, experts caution that AI agents are not infallible and their use must be coupled with effective governance and risk management.[9][10] The emphasis is on equipping human decision-makers with the necessary data and AI literacy to work alongside these sophisticated systems.[1][9] The implications for businesses are profound, with Gartner forecasting that organizations prioritizing AI literacy among their executives could see their financial performance improve by as much as 20% compared to their peers.[1][10]

Despite the immense potential, the path to AI integration is fraught with challenges that the Gartner summit aims to address directly. One significant area of concern is the management of synthetic data, which is often used to train AI models. Gartner predicts that by 2027, 60% of data and analytics leaders will experience critical failures in managing synthetic data, which could compromise AI governance, model accuracy, and regulatory compliance.[1][9] Effective metadata management is highlighted as a crucial mitigator of these risks, providing the necessary context and lineage to track and verify synthetic data responsibly.[9] Another critical aspect is the quality of data used to train AI, particularly generative AI models. Poor semantics in AI-ready data can lead to hallucinations, increase computational costs, and reduce model accuracy.[1] Conversely, organizations that focus on improving semantics could see up to an 80% increase in their GenAI model accuracy.[1][9] The summit will also tackle the perennial challenge of articulating the business value of data and analytics initiatives, offering strategies to build business cases, measure return on investment, and demonstrate the impact of AI on achieving organizational goals.[4][12]

In conclusion, the expanded AI agenda for the Gartner Data & Analytics Summit 2026 signifies a pivotal moment for the industry, as AI transitions from a niche technology to a core component of business strategy and decision-making. The bold prediction that half of all business decisions will be AI-influenced by 2027 serves as a powerful catalyst for this shift, urging organizations to accelerate their adoption of AI-driven technologies.[1][13][14] The summit's focus on practical application, leadership, governance, and addressing key challenges like data quality and risk management reflects a maturing understanding of what is required to successfully integrate AI into the enterprise. For data, analytics, and AI leaders, the imperative is clear: to develop the skills, frameworks, and strategies necessary to guide their organizations through this transformative period, ensuring that the adoption of AI is not only innovative but also responsible, ethical, and value-driven. The discussions and insights from the summit are poised to shape the direction of enterprise AI for years to come, offering a crucial forum for leaders to connect, learn, and validate their strategies for the AI-powered future.[4][5]