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.

AI agents are permeating applications and systems across organizations. Their flexibility is valuable in unpredictable environments where real-time monitoring and control aren’t practical. However, their adaptive strength comes with nondeterministic weaknesses. Increased autonomy and complexities in multiagent systems, compounded by GenAI models, dangerously raise uncertainty, prompting the question: are multiagent systems worth it?

Unlocking the full value of AI requires more than just technology. It demands a fundamental shift in how organizations are structured and how teams collaborate. This session equips D&A leaders and CDAOs with proven strategies to navigate the complexities.

Implement your target AI governance operating model by mapping governance pillars to key AI components and differentiating AI capabilities. This model should connect with other governance bodies and extend existing governance models to AI-specific considerations of trust, transparency and diversity.

Discover the essential steps for developing a successful AI strategy. This session will provide guidance on aligning AI initiatives with business goals to drive innovation and gain a competitive advantage.

As the CDAO role continues to evolve in the AI era, organizations face critical decisions about the direction and impact of their data leadership. This session explores the future of the CDAO through three distinct archetypes: Expert, Collaborator and Pioneer. Attendees will learn how to assess and choose the archetype that best aligns with their organization’s AI ambition and strategic goals. Attendees will leave with actionable insights to define their CDAO journey and position themselves and their organizations for success in a rapidly changing digital landscape.

Overlooked risks and unintended consequences of GenAI can disrupt operations, ethics, security and value realization. CDAOs should understand the second- and third-order effects of GenAI adoption and proactively address hidden challenges to safeguard their organizations’ competitiveness and resilience.

Prioritizing data and AI literacy programs directly impacts the core measures of a firm’s financial performance. Investing in data and AI literacy is the fastest way for D&A leaders to achieve payback in their D&A maturity journey, especially in early stages of maturity.

AI is impacting everything, though often more slowly than expected. Its adoption is shaped by company politics, which leaders cannot avoid. This session offers practical insights and candid answers on navigating AI’s realities in a political environment.

Trust in data, strong risk management, robust trust models, and agentic AI are reshaping how enterprises handle data, analytics, compliance, and business value. This session explores the impact of trust on data governance and agentic AI.

Organizations struggle to scale AI governance, mitigate risk, and effect compliance while delivering value in AI deployments. AI governance programs only check the box if they are not adaptive and embedded into the fabric of the AI lifecycle. In this session, you will learn how to define your role in AI governance, assess what technology capabilities are required to govern AI at scale, and make an investment decision in an AI Governance Platform or other technology tool.

AI agents have become one of the most hyped, and most abused, terms in the technology market. Like any good counterintelligence officer, you need to be able to spot agents and assess their impact, risk and value. This session cuts through the hype to the insights you need and a framework for assessing AI agent use cases, tools and risk to help AI agents deliver value for your organization.