IBM at Gartner Data and Analytics Summit

The rapid advances in generative AI are fueling great excitement. Within just a few years, one-third of generative AI interactions are expected to utilize autonomous agents, propelling a new wave of productivity for enterprises. However, this potential can only be realized if the challenges surrounding AI trustworthiness, inferencing costs, domain-specificity, and effective and secure leveraging of quality enterprise data can be overcome.

Data and AI leaders require a practical approach to accelerate AI adoption. Discover actionable techniques to maximize the value of your data for AI, learn from Lockheed Martin’s real-world examples of data and AI-driven innovation in defense and aerospace, and gain insights into fostering greater AI productivity across your teams with IBM watsonx.

Speakers: Bruno Aziza, Vice President, Data, AI & Analytics Strategy | Mike Baylor, VP and Chief Digital and AI Officer, Lockheed Martin

The business impact of generative AI has grown to unprecedented levels. Foundation models drive this impact bringing enormous potential to increase productivity and performance through adaptive learning and automation of repetitive, time-consuming tasks.

However, generative AI brings new risks and complexities. AI requires governance whether using generative or predictive ML models.

In this session, Tarun Chopra, IBM Vice President of Product Management for Data and AI Software, will lead an AI governance discussion on critical questions to address when adopting AI.

Speakers: Camilo Rojas, Data and AI WW Sales Director watsonx | Shobhit Varshney, VP and Sr. Partner, Americas AI Leader

Enterprises that possess high-quality data and governance can attest: the trust-worthiness of their data among stakeholders has doubled the ROI from their AI.

Learn how leading organizations are implementing an open and trusted data foundation to secure and maximize the value of both their structured and unstructured data, accessing siloed data across hybrid cloud, cost-optimizing growing data workloads, and preparing and delivering high-quality, governed data for AI with a new approach to a data fabric architecture.

Speaker: Edward Calversbert, Vice President, Product Management—watsonx Platform

Data matters. And a strong data foundation is key to successful AI implementations. IBM data fabric architecture optimizes secure real-time access to high-quality governed data across your enterprise.

As the trusted IBM data foundation for AI outcomes, this architecture is composable, allowing IBM to meet clients wherever they are in their data journey. Join IBM, clients and partners in a discussion about taking your AI implementations from experimentation to production with enterprise data.

Speakers: Edward Calvesbert, Vice President, Product Management—watsonx Platform | Tony Giordano, Senior Partner, Practice Leader

As organizations scale AI, data and AI leaders are under pressure to quickly secure and manage different data and AI systems to avoid costly risks. But without the right tools or structures in place, it's hard to balance meeting these demands with trusting the AI's results.

Explore the key pillars of AI governance to automate time-consuming risk and compliance workflows, govern any model, and deliver a robust, secure and trustworthy AI framework. Learn real-word examples of how enterprises have adopted AI responsibly to accelerate AI adoption at scale.

Speaker: Heather Gentile, Director of watsonx.governance Product Management, IBM Data and AI