D&A leaders play a central role in their organization's AI success by providing the critical accelerants needed to realize value from AI. Based on your organization's data, analytics, and AI ambition and where you are today, this session will unfold the vision for data and analytics in 2030. It will describe how your capabilities, operating model and practices need to evolve to realize that ambition.

AI is moving faster than ever. AI techniques should bring adaptability to an uncertain world in constant flux. However, despite its extraordinary power and early promises, AI has not been leveraged to its full potential. What is missing? Where did we go wrong? Join us as we discuss our ambition for the future of AI and AI should do for us to deliver the value that we are expecting.

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.

Organizations now have more options to build effective RAG systems, and those options come with confusion. Many organizations are looking to capitalize on new innovations such as long context windows, knowledge graphs, reasoning models, multi agent systems, and beyond. Attend this session to learn about seven challenges with RAG systems, their associated architectural choices, and best practices to improve their performance.

This workshop will cover the end-to-end process of managing a data product, from ideation to launch. It will include product roadmap development, stakeholder management and go-to-market stra tegies.

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.

A uniform and configurable operating model ensures speed, agility, and consistency in how data and analytics teams stand up their individual implementations. D&A leaders can use Gartner’s D&A operating model framework to configure and design their own models for successful reuse across all D&A initiatives.

Despite advancements in GenAI, self-service analytics continues to fail at delivering its expected impact to organizations due to governance, trust, accuracy, scalability and adoption challenges. This presentation provides CDAOs with strategies to derive more value from analytics investments.

Join this interactive session to engage with your peers and explore proven methods for demonstrating the value of data and analytics programs. Gain new insights and ideas from the experiences of other leaders to effectively communicate positive impacts and tangible results within your organization.

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!

In this session, two experts will have a dynamic dialogue presenting how federation and self-service are reshaping data management. Together, they’ll debate the risks and rewards of centralization and decentralization, exploring how, through federation and self-service, organizations can balance control with empowerment, and offer an actionable strategy for navigating the evolving landscape of data management.

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.

Many organizations pursue data products; however, sustaining their success seems challenging. This breakout session is a compilation of several case studies and best practice recommendations for D&A leaders who seek guidance in executing their data product strategy.

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.

Join this roundtable of trailblazers and thought leaders for peer discussions on advancing women in IT leadership. Women attendees are invited to explore opportunities and challenges, and to share best practices for successfully navigating the path to IT leadership.

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.