What Clients Can't Fix Alone - The Last Mile of DAM

The problems clients live with daily but rarely solve on their own

Observation:

Often, the hardest parts of digital asset management aren't technical; they're organizational and behavioral, like driving real adoption, building governance that survives turnover, proving ROI to a skeptical CFO, applying consistent, accurate metadata, and taming rights at scale.

AI for Your DAM - the Roles of Metadata, Trust and Authenticity

Challenge:

Brands and marketing organisations 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.

Ensuring Robust Digital Media and Content Supply Chains - the Future of Digital Media is Being Hotly Debated

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:

How AI Creates Space for the Work That Matters Most

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.

Rethinking Enterprise DAM: Infrastructure, Integration, and Innovation

Context:

Twenty years after launching its digital asset management program, the National Gallery of Art is exploring what comes next for a mature enterprise environment.

As DAM continues to evolve from a repository for collection assets into an enterprise platform supporting a broad range of institutional content and creativity, the organization must balance scalability, sustainability, governance, and ongoing innovation.

What we are doing and how:

What I Learned Inheriting a 20-Year-Old DAM - A Survivor’s Guide

Context:

Just been tasked to manage a DAM with no governance documentation, no contact list, and zero onboarding? Where do you go from here?

Lessons learned:

Practical steps on how to get started managing a DAM - a 90-day action plan to:

Pack Light, Find Everything: How We Went from Slide Chaos into a Well-Organized DAM System

Context:

At Rick Steves’ Europe, inspiring travelers begins long before they arrive at their destination – it starts with sharing stories, images, and informative content that brings those experiences to life. As that content has grown, so has the challenge of managing it.

What we’ve done:

Quantum Business Archaeology™: The Playbook for Intelligent Content Operations

The Challenge:

Organizations are racing to add AI, automation, and intelligence to their DAM ecosystems. Yet many continue to struggle with the same operational challenges that existed long before AI arrived.

A Candid Conversation:

Your DAM’s Future as an Intelligent Responder - Getting to DAM 4.0

Context:

• As organizations scale AI initiatives, expand omnichannel experiences, and manage growing volumes of content, DAM is being pushed far beyond its traditional role as a repository for files.
• Leading enterprises are discovering that legacy DAM architectures can no longer support the speed, complexity, and intelligence required by modern content operations.

Exploring: