Let’s get practical about AI and digital publishing

04/24 By Dale Older
brand safety

It’s easy to dismiss catchy “Rise of the Machines” headlines that pervade mainstream and trade press as clickbait, but if you set aside sci-fi fantasizing and look deeper, it’s clear that artificial intelligence and machine learning are transforming major facets of our society and economy in tangible, meaningful ways. Digital advertising is no different. Smart algorithms have changed the way ad campaigns are planned and the way media is bought and sold. Early ad technology investments heavily favored the buy side, resulting in an ‘asymmetric’ relationship between buyers and sellers of media, leaving premium publishers at a disadvantage in the race to earn more than “digital dimes” or “mobile pennies” as audiences fragment across devices. Add to this an increasing sensitivity on the part of buyers looking for fraud-free, brand-safe, and highly viewable inventory, it’s clear AI based technology is needed to help publishers protect and grow their revenue.

Brand Safety

Divisive politics, fake news, and an ever-expanding universe of digital content have driven brand safety concerns to the top of many CMOs’ agendas. Manual solutions like adding sites and terms to inclusion lists or exclusion lists have significant limitations, especially in an increasingly global digital market. How can you be sure you’re blocking every term that indicates pornography in Hungarian? Securing brand safe inventory across languages and cultures at scale is a task that stretches human capability and this is where AI is being harnessed to help.

At IAS we employ artificial intelligence to automate our brand safety solution. Through machine learning informed by our extensive data science team, our technologies are able to continually improve their understanding of the vast digital landscape. They are capable of automatically deeming new pages as inappropriate without having to be explicitly programmed to do so. While AI gives scale to our brand safety offerings, we continuously audit and enhance our models to keep up with ever-shifting types of risky content.  

For publishers, the AI approach to brand safety is a boon. Consider the case of Ariana Grande. On May 21st, 2017 Ariana Grande was one of the worlds biggest pop stars and a major draw for publishers’ audiences and advertisers. Publishers would be well served to crank out as many posts as possible about the pop-diva. On May 22nd a terrorist detonated a bomb at an Ariana Grande concert in Manchester turning the pop-diva into a temporary brand safety hazard. AI-guided brand safety solutions can ensure that ads are blocked from hard news stories about the attack, but still free to run on stories about Grande’s upcoming album and latest sartorial decisions. AI-based approaches ensure publisher’s valuable, brand-safe, inventory can be properly monetized.

Viewability adaptability

Thanks in large part to a push by marquee advertisers like Procter & Gamble and Unilever, publishers are under pressure to deliver more viewable inventory and higher viewability rates in order to capture expanding digital marketing spend. For many publishers that means rearranging their page layouts to optimize for viewability.

AI driven technology can automatically assess new viewability levels saving publishers valuable time that would otherwise be spent uploading new page layouts to a tool or platform and move them more quickly toward generating new revenue. As viewability standards and advertiser demands continue to change, dynamic publisher tools become critical for inventory differentiation.


AI-based technology has helped advertising systems process huge amounts of data, deliver insights, and protect advertisers, increasing confidence in digital advertising and enabling rapid growth spend by major brands. Savvy publishers who use the latest AI-based technology to optimize their inventory to buyer demands for brand safety and viewability stand to gain the most from digital advertising’s rising tide.

Beyond solutions to today’s advertising challenges, AI holds the promise of unlocking new inventory for publishers. Computer vision technology, for instance, can recognize image content, providing additional context to evaluate and curate pages. Soon, advertisers will be able to buy against a comprehensive visual understanding of every page and impression opening the door to even fewer publisher pages being excluded due to content uncertainty.

For a company like IAS, which already processes hundreds of billions of impressions per month, AI allows us to continue honing our optimization products based on a new and continually expanding base of intelligence. Rather than rely on humans to create manual tools that only work in limited situations, AI creates efficiency and scale. That scale, in turn, will lead to ever-improving outcomes for every part of the digital advertising ecosystem.