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.

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.

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.

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.

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.

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.

The buzz: “Dashboards are dead.” Yet, they remain the backbone of enterprise analytics for operational oversight. GenAI is revolutionizing the space, promising to streamline migration and inject intelligence, but only 8% of new reports use it today. Explore the “death of dashboards” narrative, along with the opportunities and pitfalls of migrating to next-gen analytics.

In this session, you’ll explore a reference architecture that serves as a blueprint for future-proofing your data and analytics environment. Through practical, step-by-step guidance, you’ll learn how to align your technology stack with business objectives — whether you're modernizing an existing architecture or building one from the ground up.

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.

Agentic analytics can deliver transformative improvements in the effectiveness and adoption of analytics for organizations that are ready to adopt it successfully. This workshop will help you assess your current readiness, identify strengths and pinpoint areas for improvement to ensure you are fully equipped to adopt agentic analytics.

AI agent adoption transforms data and analytics strategy and operations. In this session, we will examine the top trends across three key themes: agentic D&A, semantics at the core and D&A p latformization.

Urgent investments in AI-ready data and operational use cases have put the spotlight on foundational data management. The Data Fabric has emerged as a long-term data management architecture that you should now pursue for sustained data, analytics, and AI success. This session will help participants understand what data fabrics are and their implications for your data architecture. It will also address how to build and where to buy data fabrics.

Data governance has traditionally encompassed analytics governance, managing most risks and value in traditional analytics. However, AI introduces new risks and considerations that D&A governance may not be equipped for. Should D&A governance evolve to govern AI or is it time for a separate discipline with a fresh mandate? This session explores conflicting accountabilities, leadership and operating models between these disciplines.

CDAOs are often under time pressure to develop an effective data and analytics strategy that aligns with business value. Use these time-saving shortcuts to accelerate the strategy development process while also gaining business relevance and confidence in the process.