history written on a wall in a subway
Digital asset management is readying for a new era: one where machine learning can enhance employee efforts PHOTO: Blacren

When we explore technology “eras,” it’s tempting to get lost in the minutia of years gone by. So much has changed. 

With digital asset management (DAM), we need to look at the bigger picture to understand its past, present and future.

DAM addresses an ancient problem: If we store information outside our brains, how do we make it useful? Cave walls were an answer. Libraries were another answer. With the advent of digital expression, DAM became the most compelling way.

A Walk Down Digital Asset Management Memory Lane

The Central Library Era

Canto Software launched Cumulus in 1992, inaugurating the first era of DAM: the Central Library Era. Organizations were accumulating digital files and needed somewhere to organize them. A digital library was a more elegant solution than shared drives and floppy discs.

Consumer web browsers emerged not too long after Cumulus debuted. Mosaic appeared in 1993 and Netscape Navigator arrived in 1994. Dial-up modems were painfully slow. Nonetheless, some DAM contenders placed bets on web-based DAM.

Social-Mobile-Cloud Era

By 2006, web-based DAM had won, and so began the second era: Social-Mobile-Cloud. I started at Widen in 2004 and remember when our CEO, Matthew Gonnering, returned from his first Salesforce.com conference in 2007. He was raving about the “cloud.” 

Huh? None of us knew what he was talking about. People seem crazy when they see the future that clearly.

Central libraries were becoming silos because it was easy to add content but difficult to deploy it. The cloud, by becoming the de facto destination for content, changed everything.

In 1999, there were 23 blogs, reported Webdesigner Depot. By 2006, there were 50 million. Meanwhile, the rise of Friendster (2002), MySpace (2003) and Facebook (2004) sent a message: Publishing was becoming democratized. DAMs needed to get content from rest to work more efficiently.

However, the introduction of the iPhone in 2007 changed the web. DAM had to convert and adapt images for a dizzying combination of devices, channels, and operating systems. It was like cooking for several hundred picky eaters. 

The Integration Era

By 2012, marketing technology (a.k.a. ‘martech’) had triggered an arms race among companies. The web was poised to eclipse every other marketing medium (if it hadn’t already). The audience was enormous, but the influx of content and competition made it difficult to win attention. Companies needed combinations of martech to reach people, but most systems didn’t play nice. 

DAM vendors spotted this limitation during the Social-Mobile-Cloud Era and began to address it aggressively during the Integration Era.

DAM vendors realized they’d become second fiddle to other martechs unless they could serve as a ‘central source of truth’ for all content-based platforms. These other platforms (e.g. content management systems) came with lightweight libraries that, while less powerful than a DAM, offered the basic functionality. 

In response, DAM vendors created dozens of ready-made integrations. APIs facilitated sophisticated martech stacks like those showcased in Scott Brinker’s Stackies & Hackies Awards

Getting Ready for the Fourth Era of DAM

We’re still in the Integration Era, but not for long.

The fourth era of DAM involves machine learning and artificial intelligence (AI). DAM consultant Mark Davey expects DAM to play a central role in the semantic web, where new metadata schemas will enable computers to "read" websites.      

AI-powered image recognition and metadata tagging have arrived. However, the current iterations are underwhelming. We are still in a "hype" phase.

Next-generation DAM will not minimize the importance of people. Rather, people will need to be sharper in their DAM strategy because AI scales mistakes as efficiently as it scales good ideas.

DAM is an ongoing chapter in the story of how we organize information outside our brains. The ‘manual’ work will get easier with AI, but DAM will require more mindfulness. The price and reward of ease is deeper thinking.