Challenge:

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

• Tagging
• Categorising
• Describing

AI is used to support DAM duties such as metadata clean-up, governance documentation and reporting. Applications that optimize asset ingestion, saving time and money.

However, there are important questions that must be answered:

Rally House operates one of the most visually complex retail environments in sports merchandising, managing and delivering licensed imagery for more than 4,000 sports teams daily across email, web, and social media. At that volume, manual workflows aren't just inefficient, they're humanly impossible.

Digital asset management has traditionally focused on organizing, governing, and distributing approved content. But what happens after those assets leave your DAM?

As counterfeit goods, unauthorized sellers, and intellectual property infringement continue to expand across ecommerce marketplaces, social media, and digital channels, organizations are discovering that their DAM can play a much larger role in brand protection.

What does modern DAM look like inside two complex enterprise organizations? 

Hear two different perspectives on the same challenge from Timothy Kasper, Director of Marketing Operations Nationwide and Shayla Nastasi, Digital Asset Manager at Helen of Troy. Together, they’ll share how their teams are making content easier to find, reuse, and govern while embracing AI. 

Most DAM conversations focus on strategy, governance, metadata, AI, and transformation. Far fewer focus on what actually breaks in day-to-day operations.

This panel brings together practitioners from across the DAM ecosystem to discuss the operational realities that often remain hidden behind process diagrams and transformation roadmaps.

Panelists share candid perspectives on where workflows fail, why workarounds emerge, and what prevents organizations from achieving the outcomes they expected from their DAM investments.

The panel discusses how Generative AI and DAM are evolving and the implications for:

• The content supply chain and the growing complexity of that supply chain.
• Where the assets come from and go to.
• What other systems of record are required along the way.

Covering the latest trends and the challenges facing organizations, including:

New world: when AI is the buyer:

• When AI agents do the shopping, who still needs a product page?
• The Invisible Storefront: Rethinking DAM When the Buyer is an API.

Covering:

Covering:

The many parts of pre-implementation processes that aim to answer the question, "How do I get started?" including:

• Discovery.
• DAMS selection.
• Testing and outreach.
• Setting up guiding principles.
• Establishing processes and workflows.
• Identifying gaps in policy.

Context:

Two years ago: the SharkNinja DAM was functional but underutilized: 52,000 assets, 527 users, and a platform without a real program built around it.

What we did: a deliberate relaunch built around taxonomy, governance, training, and integrations.

The result: 261,000 assets, 2,800 global users, monthly logins up 16x, and downloads up 22x. Growth driven by program design, not the tool itself.