The world of AI automation is one to watch. With momentum building over the last few years, we expect this growth to accelerate in 2022. Digital advertising has made a lot of exciting progress in automation, most notably with programmatic marketplaces, helping many different companies in the value chain to process, enrich, and validate larger volumes of data at scale never seen before.

IAS has made significant strides in AI automation, and we see more opportunities ahead! We build, test, deploy, and monitor in production hundreds of machine learning models — the core of AI. We constantly refine and develop our infrastructure to support new tools; for example, adding automatic capabilities to explain why models make the predictions they make.

For example, the digital advertising landscape is changing rapidly, and contextual targeting is now fundamental for the proper optimisation of campaigns. Contextual advertising has evolved into a more effective way for brands to capture the emotion of their audience. Advancements in AI and cognitive technologies, such as natural language processing, can now determine the sentiment conveyed on a given page at scale, enabling more suitable ad placement decisions.

In particular, these technologies analyse the full text and the relationships words have with one another in order to accurately comprehend the context of the page. The overall sentiment (positive, neutral, or negative) is understood along with the associated emotional classifications. It also offers increased capabilities for localisation, translating copy into different languages without losing or detracting from the sentiment of the ad campaign.

It’s one thing to say a piece of digital content is positive but determining whether it’s focused on love or humour is something else. There are now smart tools that have developed huge semantic networks covering all 500,000 concepts of language and the relationships between words, in addition to diverse emotional contexts linked to more than 60 grades of human emotion.The combination of AI, machine learning and sophisticated technologies – natural language understanding and semantic analysis – allows for human-like comprehension: such as the capacity to immediately spot the difference made by small linguistic variations, from changes in tense right down to the use of a full stop.

What all of this delivers for brands is comprehensive real-time intelligence that enables precise ad matching for multiple contextual factors including emotion, at scale. With AI technologies being sophisticated enough to control how a message is presented in various contexts, advertisers now have far greater agility when it comes to planning and executing their campaigns.


With the early hype surrounding the metaverse turning into sustained excitement, it is unsurprising that projections say that it could be worth $800 billion by 2024.



For marketers, the metaverse will throw up issues that will seem familiar – measurement, brand safety – in an environment that has many new content forms. While speculating exactly what shape the metaverse will take is tough, what is clear is that marketers will need to harness the lessons learnt in web2 to tackle new issues in web3.

The dawn of the metaverse brings with it new content forms for marketers and brands to wrap their heads around. The vision of the metaverse as a fully immersive world accessible by all may be some way off, but AR and VR-enabled experiences are already impressing. In fact, 3D measurement capabilities for in-game advertising may be the first hurdle for marketers, as it seems the more natural stepping stone into a fully immersive experience, and gaming is undoubtedly a big driver for wider metaverse adoption. In essence, enabling the capabilities for current gaming environments will still be relevant in virtual ones down the road.

While user intent now may be tracked by clicks and mouse tracking, the metaverse will be able to take into account a whole range of other signals. For example, a marketer may be able to measure a consumers’ body movement in the metaverse to gauge engagement and interest in a piece of content.

But as brands navigate this new ecosystem, they will need to remain diligent. Where consumers go, bad actors usually follow. As the industry saw with the burgeoning of the video content market just over a decade ago, ad fraud is a serious risk, leading to overinflated stats and wasted budget.

To stop these same issues repeating in web3, industry-wide quality and measurement standards should be built into the very foundation of the metaverse. It is imperative that we learn the lessons from the previous iteration of the internet and implement measures to make new digital environments safer and more secure for both brands and users from the outset.

But ad fraud is not the only problem likely to migrate from web2 to web3. The fast-moving, interactive, hyper-visual new environment of the metaverse will create further safety issues and brands may run the risk of appearing next to inappropriate content. On top of this, consumer concerns over privacy will likely grow leading to ever-tightening privacy legislation.

Brand safety and suitability solutions can be the answer to both these problems. This powerful targeting method not only keeps brands safe, but provides a cost efficient way to reach target audiences, by placing advertisements in environments that are deemed both safe and contextually relevant by advanced AI.

Ultimately, it’s still early days for a fully fledged digital advertising ecosystem in the metaverse. We’re still at the ‘test and learn’ phase, but it’s important to get a head start. Undoubtedly, if it’s where users go, marketers will follow; and the need for verification and digital media quality will not be far behind.

Making the metaverse a safer place for both brands and users will take more than tech solutions. The advertisers will need to collaborate in order to create standardised guidelines and a shared language in which to talk about brand safety and suitability in this brave new world – much like what GARM is doing now.

The metaverse offers endless possibilities for brands. But in order to take full advantage, we must take heed learnings of the past and build a new environment that all are able to enjoy.


By Tony Marlow, CMO, Integral Ad Science


About Tony Marlow

Tony Marlow is the CMO at Integral Ad Science (IAS).

Tony Marlow is the Chief Marketing Officer for Integral Ad Science, based in New York. He is an insights-driven executive and leads all aspects of corporate marketing strategy, brand development and communications for the company.

Prior to joining IAS in 2019, he was the CMO for the big data company Data Axle, and prior to that he was the Global Head and Vice President of B2B Marketing for Yahoo – overseeing all B2B Marketing, Marketing Strategy, Product Marketing, Sales Learning, and Sales Insights.

Additionally, Tony is on the Board of Advisers to social measurement startup, he co-founded mobile app development company Appy Dragon (creators of RacerTracer) and serves on the Advisory Council for Colorado State University-Global Campus (CSU-Global) to which he delivered the 2017 commencement speech. He has served on the board of directors for the IAB’s Research Council, IAB  Video Center and the Media Ratings Council. He is also an Ironman triathlete in his spare time.

Tony attended the Australian National University and the University of Wollongong, holding two Bachelors degrees (Psychology and Commerce) as well as a Masters degree in Strategic Marketing.


About Integral Ad Science (IAS)

Founded in 2009 and headquartered in New York, IAS provides advertisers and publishers with the confidence that digital ads are fraud-free, viewable by real people, in safe and suitable environments, activating contextual targeting, and driving supply path optimization. Following an IPO on the Nasdaq Stock Market last year, IAS is integrated with all of the major DSPs and ad exchanges, and provides coverage with integrations across all major proprietary and social platforms.



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