“Will three-martini lunches make a comeback?” 

This was the question posed by Rob Beeler at this year’s ATS London as he discussed the potential sidelining of ad networks for a return to direct sold. While Rob’s keynote highlighted the more appealing elements of forging deals face-to-face as in days of yore, the BeelerTech founder acknowledged that the wide-scale use of ad networks to transact on inventory is ultimately going nowhere. 

Yet with the industry facing drastic changes from almost every direction, the future is far from predictable; with regulation, market fluctuations, and emerging technology all in motion, we consider what could be on the horizon for ad networks.

Regulation and data handling

Along with the entire ad tech ecosystem, ad networks will undoubtedly be reshaped by emerging regulation. There are already hints of this, with the EU Commission threatening a mandatory break-up of Google’s ad network due to alleged anticompetitive conduct. While such drastic measures may not be forced onto all, advances in privacy regulation could have a variety of impacts on ad networks. For example, as the deprecation of third-party cookies draws closer, contextual advertising has reemerged as a viable (or, debatably, superior) alternative. A resurgence in contextual advertising could prompt a rise in vertical-specialist ad networks, which can collect contextually-rich publishers. This, in turn, could result in a decline in horizontal ad networks, whose typical “one-size-fits-all” approach may struggle to capture enough useful data.

The decline of third-party-cookies and universal IDs may also present a unique opportunity for ad networks to prevail by leveraging first-party data. As the ad tech industry adjusts to privacy-centricity, first-party data has been recognised as an invaluable source of rich, relevant, and — crucially — consented-for data. As middlemen, ad networks could provide advertisers and publishers with the space to pool their first-party data. By facilitating the sharing of first-party data, ad networks could help advertisers to gain a better understanding of their customers through the publishers’ resources. A solution such as this would allow advertisers to retain access to critical data to inform their campaigns whilst toeing the line of privacy regulations.

A move to hyper-specialisation?

As mentioned previously, evolving privacy regulations could alter the landscape of ad networks, potentially giving rise to vertical ad networks over horizontal. Should ad networks lean further into specialisation, they may evolve to disproportionately serve — and by default, promote — the most lucrative segments of the market. There has, for example, been a lot of discourse around retail media and the high margins it may offer, and the medium has already attracted some high-profile ad network owners, such as Amazon. Similarly, the rise of digital video viewers in recent years could prompt a proliferation of specialist video ad networks, and as the mobile advertising ecosystem grows, we may see ad networks for the medium follow suit.

It is, of course, unlikely that horizontal ad networks will die out completely, especially considering the scale they can offer and the rise of marketers turning to omnichannel campaigns. These ad networks, however, will face more of a challenge adapting to privacy regulation in the aftermath of the deprecation of third-party cookies, however they may not have to do this alone…

AI and emerging technologies

Since the launch of ChatGPT last November, discussions around how machine learning and generative AI could impact ad tech has surged. For ad networks specifically, AI could provide innovative ways to analyse data from ads and inform targeted advertising. While programmatic ad networks already accomplish this to an extent, AI holds the potential to advance existing capabilities by collecting greater volumes of more detailed data. There’s already some evidence of this in use, a notable example being Google’s Dynamic Search Ads solution, however the proliferation of machine learning could progress the automation of ad networks on a much larger scale.

Transparency within ad networks may also be improved by the evolution of Web3 technologies. Blockchain technology, for example, could bolster transparency by providing a decentralised record of ad transactions and allowing advertisers to track their ad placements. Considering the potential headache AI-generated made-for-advertising websites could pose for ad networks, the ability to confirm that advertisers’ inventory is being displayed to real people on legitimate websites could bolster advertisers’ trust in ad networks, in addition to maximising their budgets.

Ultimately, while the evolving landscape of the advertising industry will mean change for ad networks, their future looks relatively bright. Thanks to their current use of first-party data, ad networks may not feel the full impact of cookie deprecation and be well placed to leverage the industry-wide pivot to privacy. With the correct approach, ad networks may also be able to leverage emerging technology to enhance their offerings, placing them in prime position to adapt to the developing needs and expectations of their users.