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.

GenAI solutions include several choices and trade-offs. A critical decision is: should you build custom AI solutions in-house or buy off-the-shelf products? This session brings together a debate on the trade-offs, risk and rewards of each approach. The session will be based on scenarios and use-cases to highlight key considerations such as cost, reliability , flexibility and speed for different decisions such as LLMs vs. SLMs, RAG vs. AI agents, packaged platform capability vs. bespoke custom solution, packaged vs. open-source.

This session details how Agentic AI will impact existing data management architecture and technologies, which new use cases it enables in data management and engineering, and which skills will be needed or become obsolete. We’ll also cover how to prepare budgets, teams, and operating models for these changes. These are now valid, frequently debated questions as Agentic AI evolves.

In this volatile era of economic uncertainty, D&A leaders need to think outside the box when it comes to cost optimization ideas and cost savings programs. During this session, you will see a case study that shows how Gartner helped a client energize their savings program using a sprint-based theme approach to spark savings ideas.

Most metadata in 2025 will remain passive in approaches with stats, reports, schema and business-developed glossary terms. Yet, organizations must grow their maturity in metadata management. We start with traditional metadata techniques — passive. With AI undergoing confidence issues and the demand to reduce risk, grow AI confidence and provide data assurance, active metadata becomes key.

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.

Have you ever struggled to secure buy-in to a no-brainer MDM strategy? MDM programs exist to support business outcomes, yet business cases often focus on the “how” not the “why,” leaving stakeholders disengaged. In this session, we will explore what constitutes a strong MDM value proposition that will engage stakeholders from the business case, through execution and stewardship.

Productivity of knowledge workers is not a path to financial value. Process recalibration is a prerequisite to value creation. True, sustainable value is trapped behind legacy processes, outdated team structures and the business driven transition approach. This session provides insights to understanding practical approaches of unlock the ROI and how to lead teams through the transition.

In this session, you’ll explore a Lakehouse architecture which is becoming the cornerstone of modern data management initiatives. Through practical, step-by-step guidance, you’ll gain clarity on the purposes of data zones and the design principles of the Lakehouse architecture.

42% of organizations state they want to be more data-driven. But to what end? The next megatrend for D&A leaders to prepare for is “autonomous business,” where operations run unattended, management is heavily augmented with analytical technology, AI agents are customers, products and services are data-driven, all within a programmable economy. Attend this visionary session and walk away with a better understanding of your future.

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.

This session is designed for both first-time and experienced CDAOs who are new to their organizations. These insights will help you proactively shape and manage your initial weeks in a new role, enabling you to make an immediate impact and build a strong foundation for the future. Are you among the 61% of CDAOs considering a move within the next two years?

This session will explore how generative AI technology will evolve over the next decade, moving from large, general-purpose models to agentic, multimodal and deeply personalized systems. IT leaders will gain foresight into the architectural, ethical, and strategic shifts that will define the next wave of enterprise AI.

AI agents can upend traditional AI use cases and unlock transformative potential, but the real danger isn’t overhyping their power — it’s overestimating your organization’s readiness. D&A leaders must see past the hype, sidestep common pitfalls, and build the foundation needed for true AI success.

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.

Data quality and data observability tools provide significant capabilities to ensure good data for your BI and AI. Data observability tools give organizations integrated visibility into the health of their data, data pipelines and data landscape. Data quality tools enable business users to manage data at its sources by setting rules and policies. Together, these tools help organizations build a strong foundation in data management for BI and AI initiatives.

Leaders responsible for AI must evaluate the potential benefits and costs of new agentic AI use cases. This insight offers a framework, model and specific numbers for building and simulating total cost and key value drivers at scale for AI agent use cases.

National AI sovereignty is a nation-state’s desire to control its own AI, reducing reliance on foreign innovation, talent, and vendors. Ambition and maturity vary globally, creating commercial opportunities and risks. This session explores various nation state approaches of sovereign AI and the public policy initiatives, including global AI regulations, that support them. Attendees will leave with a blueprint to identify value creation strategies while confronting geopolitical uncertainties.

This hands-on workshop is for D&A leaders seeking to unlock AI’s full potential as a professional co-pilot. Learn why mastering prompts is the first step to true AI fluency. Through live exercises focused on real-world D&A scenarios, you will learn the core techniques to build a more efficient and impactful analytics practice. Leave with a tactical toolkit of prompt engineering skills you can use immediately and a clear vision for your strategic AI value.

AI spending continues unabated and so is the pressure on leaders. CIOs need to demonstrate the value of AI. CFOs need to calculate it. The c-suite needs to collaborate to create real value. Here we present Gartner's framework for a rigorous, repeatable approach to financial operations (FinOps) of AI initiatives. The focus is on the economics of business value, cost and risk of AI, GenAI and agentic AI.

Data management platforms emerge through the convergence of several individual data management capabilities. D&A leaders keen on data platform modernization should join this breakout session to learn about the dynamics of this emerging market and the benefits of reducing architectural silos to meet data demands for both current and innovative use cases.

There are seven key reasons organizations struggle with effective data governance. This session examines what consistently goes wrong and offers practical solutions to help make data governance work for your organization.

AI agents are fundamentally transforming traditional D&A operating models. D&A leaders must recognize this shift and adapt their operating models to integrate AI agents, ensuring AI-ready operations, enhanced value delivery and improved decision making. In this session, we will share three real client cases from Mastercard, Danone and Inspur that demonstrate how organizations have successfully made this transition.