Trust models enable D&A governance leaders to understand how data, analytics and AI assets are used across their enterprise to support business outcomes. This session will help you understand what trust models are, and how they can be used to drive better business outcomes.

Data integration tools help organizations access, process, move and transform data. They support use cases like data engineering, modern data architecture, less-technical/business user support, and operational data integration. In this session, we'll present the latest Magic Quadrant for Data Integration Tools, discussing vendors and technologies to help you choose the best tool for your needs.

The biggest cause of D&A failure is that the users don't use the data, insights, or tools to drive business value. Ensuring adoption is never easy, but there are some proven techniques to drive pervasive D&A usage.

Generative AI costs can rapidly escalate due to poor architectural decisions, lack of operational know-how and inadequate governance. In this session, we outline the top ten best practices that D&A leaders can adopt to optimize costs, enabling them to achieve quicker business value and operational efficiency.

Despite the popularity of retrieval-augmented generation, organizations are struggling to optimize large language model applications based on RAG. Attend this session to get suggestions and recommendations on improving your RAG solution, LLMOps for RAG systems, and scaling considerations.

D&A leaders and teams are at an AI-driven inflection point. They are crucial to enable business value through AI-readiness but must evolve their strategy and operating model to meet their organization’s AI ambitions. Reporting from the Gartner 2025 CDAO Agenda Survey, this session reveals actions successful D&A leaders have taken to deliver business outcomes from AI, data, and analytics, and what they need to do next year.

Organizations have a lot of metrics, but few have the kind of metrics that move the needle on performance. This presentation discusses techniques you can apply to create metrics that compel users to run to their dashboards every morning.

Data products are all the rage within D&A functions as the next wave of potential solutions to reduce the business-IT friction and provide sustained means to data delivery. However, there are many challenges. This session will help D&A leaders understand and build data products, manage and govern them through contracts, and sustain them through marketplaces, governance, and ops best practices.

To position their teams as a must-have discipline that can fulfill cross-functional use cases, D&A leaders must optimize their organizational model. The optimal organizational model is one that balances enterprisewide capabilities focused on enablement with decentralized needs focused on outcomes. In this session you will learn the design principles behind the right D&A organizational model and how to balance a centralized team (focused on enablement) and decentralized needs (focused on outcomes).

Moving AI projects from pilot to production requires substantial effort for most enterprises. AI Engineering provides the foundation for enterprise delivery of AI and generative AI solutions at scale unifying DataOps, MLOps and DevOps practices. This session will highlight AI engineering best practices across these dimensions covering people, processes and technology.

With high D&A ambitions and AI pilots becoming increasingly ubiquitous, focus is shifting toward consistent execution. We will share how to continue innovating and experimenting while scaling success. In this keynote, Gartner’s perspective will guide you on preparing for the expected and adapting to the unexpected. Learn to enhance your D&A and AI capabilities on the path to success.

Data and analytics leaders and their data engineering teams are tasked with evaluating and selecting data integration tools. However, there are many options, which can be confusing. This session will explain the various types of data integration tools and technologies available in the market, and help you select the right data integration tool for your needs.

Vendors are flavoring their messaging and products with AI. But does this work for you as you need it to? What if a non-AI vendor brings it in? Are you comfortable with the unknown scenarios or is more clarity needed? Can you rely on AI Act compliance? Attendees share best practice preparations and how to increase resilience on vendor AI risk. Spoiler: you may have already done a lot.

Explaining AI models and their outputs to non-technical stakeholders can be challenging due to their complexity or business expectations. This decreases the trust and adoption of models in production. This session will discuss a few practices that can help D&A professionals enhance explainability and trust in model predictions, facilitating responsible and ethical use of AI across various domains.

How is the CDAO Role Changing?  What will it look like in 3-5 years?

Come ready to discuss these questions around the future of the CDAO leadership role with your colleagues. The room will be set up for smaller conversations of 7-10 per table, with one facilitator from Gartner. CDAO Circle sessions are not recorded to preserve your confidentiality.

Gartner's Hype Cycle for AI provides a snapshot of current AI trends and innovations mapped against their real-world applications and potential for impact in the enterprise. Find out more about how to use the Hype Cycle to track technologies and more details on individual elements that are at the innovation trigger, climbing to the peak, on their way down or have reached the plateau.

By following the steps discussed in this session, organizations can effectively assess their D&A governance platform requirements, ensuring they select a solution that address critical use cases, and overall business performance.

Successful data science teams require the alignment of technical talent, business goals and collaborative culture to drive high-impact analytics outcomes. Leaders and members of these teams have a vital role to play to ensure optimal collaboration and impact. This session highlights what modern data science teams look like, the vital and exciting work they do, and how to ensure these teams thrive.

Data fabric and data mesh are not mutually exclusive. Join this session to learn about how D&A leaders can put an end to a five-year long debate comparing fabric and mesh. You can deploy them independently, or best-case together. You will find out how you can deploy the fabric design to unify data management and mesh operating model to distribute data management in a sensible manner.

Agentic systems have become a reality. However, many IT leaders are uncertain about how they will evolve or how they can be used to gain advantage. Join this session to explore the evolution of AI agents, from simple agents to autonomous multi-agent systems.

For over a decade, we have sought a holistic, unifying theory of data management. This presentation documents the quest, and touches on the data and analytics infrastructure model (DAIM), metadata, data fabric, data ecosystems, and FinOps. Each of these is required and together they address everything from infrastructure to AI to strategy communications.

This presentation of Gartner's top D&A predictions for 2024 guides data and analytics leaders as they plan for the impact of AI on 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.

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.

This primary goal of this workshop is to equip participants with strategies and practical techniques to secure enterprisewide support for data governance initiatives. The workshop focuses on building a compelling business case, engaging key stakeholders and demonstrating the value of data governance to the organization.

"We don't need to transform" said no CEO ever. Everybody's transforming, seemingly all the time. But transformations can feel like pushing water uphill, even when people agree that change is needed. This is because most enterprises overlook findings from neuroscience, behavioural science, and psychology that describe how people change and under what conditions. This keynote focuses on how to overcome four behavioural hotspots that show up in just about every transformation.