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.

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.

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.

AI initiatives often stall when data teams can’t keep up with business demand for fast, self-service data. Whether it’s AI agents, BI tools, or business users—everyone needs data, but the pipeline-centric modern data stack wasn’t built for this kind of agility. In this session, learn about how an Instant Data Fabric enables data teams for self-service at AI scale by instantly generating contextual Data Answers from distributed enterprise data for consumption by business teams. Discover how leading organizations are using this new data architecture to accelerate AI adoption without comprising governance and control.

GenAI systems are evolving beyond basic information retrieval and question answering, becoming sophisticated agents capable of managing multi-turn dialogues and executing complex, multi-step tasks autonomously. However, reliably evaluating and systematically improving their performance remains challenging. In this session, we'll explore methods for assessing the behavior of LLM-driven agentic systems, highlighting techniques and showcasing actionable insights to identify performance bottlenecks and to creating better-aligned, more reliable agentic AI systems.

As we enter a new era of productivity, automation isn’t about armies of robots—it’s about enabling better decisions through algorithms. For knowledge workers, the true transformation is human-centric.
While generative AI and robotics capture headlines, the real foundation of successful automation is high-quality, well-governed data. Without it, your AI initiatives will stall, and your brand could suffer.
Join Soda and LexisNexis Risk Solutions to explore how empowering your people with data governance, observability, and literacy is the key to unlocking the full potential of agents and GenAI.

Data teams are faced with increased demand for trusted data assets, but struggle to quickly and safely grant access to the most validated data. In this session, Schroders will share how they've enhanced discoverability and governance of data across the enterprise using Collibra's unified governance for data and AI to enable data consumers to easily find and access the trusted data they need. Learn how building a curated marketplace of data products has helped foster greater collaboration and increased the safe usage of data for greater advantage.

Join us for a session focused on unlocking the real potential of AI through product thinking. Dive into why AI projects aren’t taking off. Discover the most important metric for GenAI applications. We'll walk through Shape, Nail, Scale, Run – a practical framework for turning AI ideas into successful, scalable solutions. Be inspired by a real-world case study of what we did for the UK’s oldest private bank with product-led thinking. This session is perfect for product leaders, designers, and anyone looking to bring AI to life in meaningful ways.

Given the ease with which AI-based initiatives can be executed nowadays, it is no surprise that more and more enterprises are considering adopting AI-powered autonomous analytics to make well-informed decisions more economically, improve operational efficiencies, and delight customers. Achieving the true promise of AI, however, requires access to data and the execution of such analytics in real time. Join this session to learn about data processing challenges and architecture patterns fueling AI-driven businesses.

Responsible AI decisions are not black and white, they require trade-offs. Learn to make trade-offs and debate the alternatives to make AI governance and responsible AI decisions. Discuss controversial ideas in AI with your peers. Express your opinion and listen to what others are saying. Learn to ask the right questions and get the right answers to ensure responsible, trustworthy and ethical AI.

Asking your colleagues how analytics can help them often results in blank stares, defensiveness, or wildly incoherent suggestions involving AI. This session will show you how to work with your colleagues to pinpoint how you can help, identify the most helpful capabilities to build, and explain how to measure your impact.

Tech and service providers are rapidly providing new AI capabilities and features to customers and hoping for leadership. Unfortunately, customers don't really know what to do with these features and are balking at the cost. This session explores a value journey, from features to transformation using a "value accelerator" model designed to align product strategies with customer outcomes.

Data management resources face increasing challenges due to growing demand, including the need for AI-ready data. It is essential for data management leaders to make sure that data management is not misdirected and aligns with the business value. Proper alignment will maximize the value of data management initiative and support business growth.

A major shift is happening in the data space and it’s not just AI. Handling the explosive growth of data while managing costs - all without compromising performance is pushing leaders to reevaluate Data ROI. In this session, we explore how Exponential-e, a leading cloud, networking and services provider, adopted strategies to minimize TCO for data integration and to create additional value with data. Learn how they deliver intelligent systems that are better connected with automated data pipelines and how to put this data to use using managed AI agents.

Among organizations that have adopted generative AI, only 33% report implementing it into functional processes. To seize productivity gains from AI, enterprises need to get the most from their data, ensure governance, and make it easier to use. For many, that means better integration with the workforce tools already in use. Learn how companies are developing AI agents that act with greater autonomy and how they are scaling them across diverse environments to deliver impact. Discover how to manage your AI assistants and agents in a unified, adaptable experience that safeguards investments.

In the era of AI, harnessing data analytics is essential for innovation. Organizations are transforming their data strategies to harness the full potential of AI.  

Learn how organizations create powerful AI experiences by unifying their data and transforming their data strategies resulting in significant operational efficiencies.

AI is data hungry. The lack of data is the most frequently identified barrier to AI adoption. We’re not lacking in data, per se. We’re lacking data that is AI-ready. And traditional data governance practices often hinder AI project progress.

Learn how a European AI innovation leader more than halved the wait time for AI-ready data, saving hundreds of pounds per year by implementing both a data enablement culture and a data policy enforcement technology solution.

Looker’s AI-first analytics experience, with a conversational interface, enables all users in your organization to leverage trusted data and make better decisions. Discover how you can lay the foundations to deliver best-in-class conversational AI experiences. Join us, along with a cohort of your peers, to participate in discussions around foundational strategies for conversational AI and share existing use cases and experiences.

We are presently in the midst of an artificial intelligence (AI) revolution, where advances in deep learning technologies are rewriting the rules of entire industries – including how we forecast the weather and predict changes in our climate. In this session we will learn how the Met Office is successfully navigating the opportunities and challenges (both technological and cultural) of embedding AI across the organisation, and discuss how the complementary use of AI alongside traditional physics-based weather and climate models will further help people make better decisions to stay safe and thrive.

In an era where speed-to-insight defines competitive advantage, Dunelm is embracing a new paradigm: agentic analytics. This session explores how the UK’s leading homewares retailer is transforming decision-making by empowering business users with real-time, self-serve access to data—without relying solely on data teams. Learn how Dunelm is leveraging AI-powered analytics to surface insights proactively, drive operational efficiency, and reduce the time from question to answer. Whether you're modernising your data stack or looking to scale data literacy across the business, Dunelm’s journey offers a practical look at putting agentic analytics into action.

See through the hype to better understand the practical applications, risks, and aspirations of AI in the data governance industry. Find out how to position your data governance program as a leader for your organizations' AI initiatives.

AI explainability is crucial for fostering trust and creating responsible AI by providing transparency into decision-making processes, enabling accountability and mitigating biases. Join this session to know about some practices that D&A technical professionals must adopt to enhance AI explainability and trust, and ensure the responsible and accountable use of AI.