Thursday, March 19th · 12:30pm – 5:00pm · Frederik Meijer Gardens & Sculpture Park
Thursday, March 19th
12:30pm – 5:00pm
(Check-in begins at 12:00pm)
Frederik Meijer Gardens & Sculpture Park
1000 East Beltline Avenue Northeast
Grand Rapids, MI 49525
Many organizations are investing significantly in AI, from careful pilots to enterprise-wide deployments. Yet most face a common challenge: AI initiatives that don’t scale, don’t get adopted, or don’t deliver expected business value.
The real problem isn’t the AI technology. It’s the data foundation beneath it.
This half-day event cuts through the AI hype to address what actually determines success: building robust data and infrastructure systems that enable AI to scale sustainably. You’ll discover why most AI initiatives fail due to data quality, governance, and infrastructure gaps, and learn a practical operating model for addressing these foundational challenges.
Through real-world examples, deep-dive sessions on data ecosystems and technology infrastructure, and conversations with local business leaders at different stages of their journey, you’ll gain concrete strategies for building the foundation that makes AI scale possible.
Discover the 8 critical dimensions where AI initiatives commonly fail and why a systematic operating model is essential for success. Understand the evolution from individual GenAI adoption to enterprise AI challenges, and why organizations that don’t build strong foundations today will be left behind as multi-agent orchestration and advanced AI capabilities emerge. Through real-world examples of both failures and successes, learn how to address the challenges preventing AI from moving beyond pilots.
Key takeaways:
Explore what AI-ready data actually requires and the common data failures that derail AI initiatives. Learn the components of a robust data ecosystem, from engineering and pipelines to governance and analytics, and discover how these capabilities deliver immediate business value through improved analytics and decision-making, regardless of your AI timeline. Understand practical approaches to strengthen your data foundation for both current business intelligence needs and future AI ambitions.
Key takeaways:
Explore the complete infrastructure stack needed to support scaled data and AI operations, including storage, compute, DevOps, integration architecture, and AI orchestration tools. Learn how to evaluate deployment options (cloud, hybrid, on-premises) for different phases and build a long-term, scalable infrastructure foundation. Pure Storage will present on modern data storage solutions designed for AI workloads and demonstrate how the right storage architecture enables AI scale. See demonstrations of AI agent orchestration capabilities and understand how these tools enable coordination and management of multiple AI systems working together.
Key takeaways:
Hear from local business leaders at different stages of data and AI maturity as they share practical insights from building capabilities in their own organizations. Engage in conversation about the challenges, lessons learned, and strategies that work in real-world implementations.
What you’ll gain:
Enjoy heavy appetizers and an open bar while connecting with fellow attendees and our engineering team while exploring live demonstrations of AI solutions in action. Experience firsthand the technologies and approaches discussed in the sessions, ask detailed questions about implementation, and discover how these solutions might apply to your specific challenges. This interactive session bridges the gap between learning and application, giving you practical exposure to working AI systems and the opportunity to build valuable connections with peers facing similar challenges.
Many organizations rush to implement autonomous AI systems without considering the full ecosystem in which they’ll operate. In our experience, technical sophistication alone rarely delivers sustainable value without thoughtful integration into human workflows and organizational processes. Building effective agentic AI systems requires balancing three critical elements: People, Process, and Technology.
President, Mutually Human
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Mutually Human
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Mutually Human
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.