Artificial intelligence, specifically generative AI, is the latest technology to send marketers into a frenzy of creative experimentation. But only a year ago, Web3 was emerging in a similar way, as brands launched NFT projects, appeared in virtual worlds and engaged with crypto communities. 

It may be tempting to believe generative AI has replaced Web3 as the new fad, but industry veterans have made it clear that Web3 isn’t going anywhere.

Meanwhile, against the backdrop of a possible recession, brands are already cutting costs and having to make tough decisions over where to invest ad dollars. Their next choice may very well impact innovation budgets and pit AI against Web3, Martha Bennett, VP and principal analyst at research company Forrester, told Ad Age.

So how should marketers reconcile the two spaces? Are they competing technologies or complementary?

AI and Web3 have very different origins and use cases in advertising. AI has been an integral feature of ad tech for over a decade, enabling recommendations, powering programmatic ad buying and structuring customer data. Web3, on the other hand, is less of an automation and more a set of principles, which are manifested in technological tools. NFTs, DAOs and blockchain democratize digital ownership, participation and record-keeping.

“AI is not on a parallel development course with Web3,” said Jeff MacDonald, social strategy director at agency Mekanism. MacDonald pointed to the centralized reality of the AI space, which is currently run by sizable, for-profit companies supported by even bigger ones. Microsoft, for example, just invested another $10 billion—on top of $3 billion in previous investments—in ChatGPT and DALL-E creator OpenAI.

This landscape starkly contrasts with that of Web3, or at least with the goals of Web3, which aspire to decentralization and de-emphasize walled gardens. But while the two technologies differ in their advertising functions, there are ways that marketers can combine them for a potentially greater outcome.

Consumers trying out Web3 sometimes face hurdles in the onboarding process, but brands could ease this confusion by leveraging AI tools, MacDonald said. A possible use case would be a generative AI platform gauging user interest and steering them toward dApps (decentralized applications) based on those preferences. 

Inversely, Web3 tools can help package, personalize and deliver creativity afforded by AI, said Chris McGarry, founder and chief executive of Authentic Artists. The company oversees an AI platform that creates original music, and last year dropped an NFT collection that paired pieces of unique instrumentation with digital avatars—ownable as a single asset. 

A similar process could be used by marketers dealing with images, text or video. Hardee’s, for example, created 10,000 unique burger images with DALL-E; then by packaging and disseminating the images as NFTs, the brand could bring fans deeper into the campaign.

Authentic Artists also builds AI-powered virtual musicians (think virtual influencer Lil Miquela as a DJ). In their most common form, virtual influencers—the supposed tastemakers of the metaverse—are still curated and maintained by humans. But AI technology could streamline this upkeep while generating a steady flow of content for a designated audience.

Competing for ad dollars

Brands looking to adopt AI tools may have to consider doing so at the expense of their Web3 budget. This is especially possible for brands still in the experimentation stage of Web3 and who have yet to establish a robust strategy for the space, said Forrester's Bennett.

For most brands, AI and Web3 are fascinating innovations but are not yet must-have components of a marketing strategy, such as social media. This means they require testing and plenty of caution to see how—or whether—they make sense to use. But advertising is a fickle budget, especially with regard to the more experimental efforts. Amid economic uncertainty to boot, some brands will have to choose between investing in Web3 or AI.

Bennett sees ample reasons for prioritizing AI. There are already numerous ways that marketers are using generative AI to their advantage, and the verdict is in: these tools can really improve productivity. Web3, on the other hand, is less obviously useful to advertisers, said Bennett, and is limited to only select brands who have reasons for activating NFTs or engaging crypto communities.

There is also a shortage of experienced Web3 companies that can help brands navigate the space, by virtue of the industry’s incipience. A number of Forrester clients are indeed looking to replace their NFT partners with more proven ones, Bennett said.

In the AI space, the companies that could help brands are tried and trusted, such as Google and Microsoft. Even the startups in the industry, though not all equal, have years of experience with their technology, Bennett said. That’s more than can be said for many Web3 startups.

Shared uncertainties 

Regardless of whether a brand chooses to invest in AI, Web3 or both, either space poses similar uncertainties that could affect how their technologies evolve. 

Regulation is one area. In Web3, there has yet to be a significant push at the federal level for how NFTs and crypto should be considered under the law. While a number of cases have emerged in areas like insider trading and fraud, there remains a lack of established precedent. The way in which the chips fall will undoubtedly impact how brands interact with the assets, and the space at large.

AI also is an industry in need of regulation. The wellspring of generative bots has raised questions over copyright; for example, when DALL-E slightly manipulates a famous painting, is that a violation of the painting’s copyright? Or, given the bot is trained on reams of data, what rights do that data have over the bot’s output? 

Earlier this month, Getty Images sued AI image generator Stable Diffusion over this very issue, alleging the platform unlawfully scraped millions of images from its site. It’s a similar notion that has been brought up with regards to NFT art and the ownership of its underlying IP.

Web3 and AI are also both condemned because of their dependence on mass quantities of computing power. Web3 relies on arduous processes like crypto mining, while generative AI can only improve through larger models and datasets. Both of these systems inevitably result in high carbon emissions.

Related: Why brands are cutting back on sustainability marketing

But whereas Web3’s footprint is largely public through its reliance on blockchains, that of AI can only be estimated, since centralized companies don’t have to reveal that information. This will be an important issue for sustainable advertising in 2023, said Mekanism’s MacDonald. 

As both Web3 and AI work to hash out their problems, brands will inevitably experience collateral damage in the form of a lack of brand safety. This, of course, is the double-edged sword of activating new technologies. But for marketers, the payoffs could very well outweigh the potential fallout. Deciding which payoffs are worth pursuing will be the next step in brands’ strategies.