DAM at Dell:

How DAM serves as a key navigational star within a broader content constellation, guiding the enterprise toward a unified, AI‑ready platform.

Delivering:

• An honest look at our “messy middle” as we consolidate tools, evolve taxonomy, and move away from fragmented processes that no longer serve an AI‑centric world.
• Practical insights, lessons learned, and the critical questions needed to connect DAM, taxonomy, and enterprise platform transformation.

• How to make the most of the time before your AI enterprise adoption - including metadata cleanup and optimization strategies.
• Key pitfalls to avoid in the early stages of AI adoption, especially when defining and implementing AI use cases.
• How to recognize where AI will truly add value versus where it only sounds promising.
• Staying aligned with emerging trends in the DAM + AI landscape.

Reality:

Governance is the backbone of an organization’s DAM program - it’s the critical mechanism that keeps everything functioning cohesively. As organizations become increasingly data-driven, prioritizing good Governance is essential. There’s no avoiding it. It’s necessary to maximize the value of data and content. Governance provides the structure that ensures program objectives are met both during DAM and throughout its operations.

The inevitable implications:

Best practices for scaling DAM across global teams and systems, connecting with other systems such as PIMs, CMSs, CDPs, and creative suites for seamless end-to-end workflows. 

Facilitator:

Panel:

What’s possible:

Brands and marketing organizations must determine what metadata fields and relationships are appropriate for AI integration with digital assets, AI may help automate tasks, including:

• Tagging
• Categorizing
• Describing

Applications that optimize asset ingestion, saving time and money. 

Problem: