Data integration is a core component of D&A, and it is continuously transforming. This session provides guidance on how best practices for data engineering are evolving to improve data integration and support AI initiatives. It also examines the trends guiding data integration technology, including how data integration tools are leveraging AI features.

Data and analytics leaders are turning to AI agents to automate data analysis and drive actionable insights with minimal human effort. The success of agentic analytics hinges on addressing the challenges of integration and reliability. In this session, discover how the model context protocol (MCP) can be used with knowledge graphs to solve these challenges and create scalable solutions.

Delve into the critical aspects of risk management and regulatory change in data, analytics and AI. Bring your questions and learn how to identify potential risks, triage and prioritize them, and implement effective mitigation strategies to safeguard your organization’s digital assets to be able to deliver AI projects.

Dive into a dynamic session spotlighting the latest innovations transforming data, analytics, and AI. Explore how emerging solutions are driving perceptive analytics and enabling increasingly autonomous business—without the hype. Watch curated vendor showcases, engage in interactive polls, and gain fresh insights into the technologies shaping the future of intelligent data and analytics.

Organizations are charged with being more productive, and while AI is an answer to many such opportunities, organization and program structure can be far more impactful on productivity than using AI. This session will weave together data and analytics governance, MDM, and data quality into one organized initiative that will simplify complexity. Join this session to learn more.

Data engineering faces increasing pressure to deliver AI-ready data that meets agentic AI requirements. This session explores changes in data engineering functions, practices, architectures and technologies.

To achieve agentic optimization, D&A leaders must invest in active metadata and data ecosystems, develop FinOps maturity, and train AI models. This foundation enables efficient, automated decision-making for deploying and optimizing D&A resources. This session explores how these areas intersect, offering a holistic view of agentic capabilities, impacts and risks. Go beyond targeted agents and think big!

As Microsoft continues to promote and enhance their Microsoft Fabric offering, many clients are asking: How does Microsoft Fabric impact my current Power BI estate? What are some strategies for successful deployment of Microsoft Fabric? How do we scale analytics in Microsoft Fabric and leverage its native AI functionality? This session provides expert insights on Power BI to Microsoft Fabric migrations.

Gartner research shows that technical excellence alone rarely shifts mindsets or drives cultural change. If you want your business to truly think differently about data, you need to stop “selling” capabilities and start “marketing” value, using the same tactics as world-class consumer brands. This session unveils a new playbook for D&A leaders to build and execute a marketing plan that transforms culture and boosts adoption, with Gartner insights and real-world examples. Learn why most D&A strategies fail, how to apply proven marketing principles, and spark enthusiasm for data across your organization.

This session discusses whether AI will replace business intelligence (BI) or simply transform it. As BI interfaces become gateways to AI analytics, trust and precision are crucial — users won’t tolerate AI errors. Join this session to explore if AI will deepen insights and automate action, or will BI adapt and survive in a changing landscape.

Generative AI technologies and techniques are evolving at an unprecedented pace, accompanied by significant hype, making it challenging for leaders to navigate this dynamic landscape. AI leaders can leverage this Hype Cycle to identify the innovations most worth pursuing as they shape and execute their AI strategies.

D&A and AI leaders, including CDAOs, continue to face challenges in demonstrating the value of D&A and AI initiatives. This session will provide a roadmap for gaining stakeholder buy-in, quantifying value and building a robust business case, learning from the successes of other organizations, and continuously measuring results and adjusting.

This session of Gartner’s top D&A predictions for 2026 will guide data and analytics leaders as they plan for the impact of AI across all aspects of data and analytics, including leadership, governance, talent, market, and the need for AI-ready data and a FinAI competency for value realization.

The role of the artificial intelligence leader has rapidly emerged as essential for enterprise survival. Gartner's AI leaders survey shows that 91% of high-maturity organizations report having dedicated AI leaders, and it is crucial for AI-driven transformation. This session discusses the essentials of the AI leader role and how it fulfills its purpose of creating an AI-first enterprise.

This session covers the use and output of Gartner’s AI-Ready Data Toolkit, which includes practices for both structured and unstructured data. The process develops metrics that “stack” as you progress from POCs to multicontext data use, operationalization and production support. The session also explains how to customize the toolkit with your own thresholds and readiness analysis.

Organizations continue to struggle to prove the value of agentic analytics initiatives, often due to a disconnect in AI's ability to connect and interpret operational metrics. To unlock the full value of AI, you need a robust metrics framework. A metrics framework provides a structured approach to measure success by aligning high-level strategy with daily operations, enabling both human and agentic data-driven decision-making. By distilling strategy into clear, simple, actionable KPIs, these frameworks enhance transparency and yield insights for strategic recommendations and measurable business value.

Many organizations are wondering how GenAI will impact their D&A governance and management tools, and by extension, their D&A governance operations. This research provides an overview of how key D&A markets are incorporating GenAI capabilities and how these will change the nature of D&A governance.

Decisions AI leaders make regarding AI investments and the patterns by which employees embrace these technologies will shape the future of work. We will explore what we call ripple effects: the downstream consequences of AI adoption that influence workforce needs, the number of employees required, the nature of their roles and how work is organized. Get ahead of blind spots so AI investments deliver.

Analytics and business intelligence (ABI) platforms are increasingly integrating AI agents to transform how data is analyzed and insights are delivered. Data and analytics leaders need to proactively understand these shifts to maximize AI's business impact and ensure organizational readiness. Join this session to learn more.

RAG has emerged as a powerful approach for building advanced AI systems that combine the strengths of large language models with external knowledge sources. However, RAG solutions struggle with reliability and require a lot of experimentation. This session will address key questions to help determine the best design pattern and optimization for RAG implementations.